海量研报在线阅读 高效提升商业认知
需求方数据和能效指标--国家路线图设计指南Demand-side data and energy efficiency indicators
战略咨询
2023-02-26
Demand-side data
and energy eiciency
indicators
A guide to designing a national roadmap
The IEA examines the
full spectrum
of energy issues
including oil, gas and
coal supply and
demand, renewable
energy technologies,
electricity markets,
energy efficiency,
access to energy,
demand side
management and
much more. Through
its work, the IEA
advocates policies that
will enhance the
reliability, affordability
and sustainability of
energy in its
31 member countries,
11 association countries
and beyond.
This publication and any
map included herein are
without prejudice to the
status of or sovereignty over
any territory, to the
delimitation of international
frontiers and boundaries and
to the name of any territory,
city or area.
Source: IEA.
International Energy Agency
Website: www.iea.org
IEA member
countries:
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Japan
Korea
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Republic of Türkiye
United Kingdom
United States
The European
Commission also
participates in the
work of the IEA
IEA association
countries:
Argentina
Brazil
China
Egypt
India
Indonesia
Morocco
Singapore
South Africa
Thailand
Ukraine
INTERNATIONAL ENERGY
AGENCY
Demand-side data and energy efficiency indicators Abstract
A guide to designing a national roadmap
PAGE | 3
I EA. CC BY 4.0.
Abstract
Energy efficiency indicators are key to tracking energy efficiency progress for a
variety of purposes (e.g. policy making, monitoring targets, making energy
projections, developing scenarios and planning, and benchmarking). This guide is
for professionals and decision makers, describing options and good practices for
the collection of energy end-use data and the development of energy efficiency
indicators at the national level. In parallel, it can also be used as an assessment
tool, helping countries/economies to locate their starting point, and to identify
appropriate targets according to their respective national interests and priorities.
The roadmap presented here encompasses the results of a consultation exercise
across countries and presents good practices and practical tips. It acknowledges
that there is no single solution, but a number of possible pathways instead,
depending on national contexts and priorities. The roadmap is a strategic
document looking at the whole value chain in the development of efficiency
indicators, from the initial point where the need for data and indicators arises up
to the later dissemination and data use stages, and is meant to be a useful
resource for practitioners across the globe in the development of energy efficiency
indicators.
Demand-side data and energy efficiency indicators Acknowledgements
A guide to designing a national roadmap
PAGE | 4
I EA. CC BY 4.0.
Acknowledgements, contributors
and credits
This report was co-ordinated by Domenico Lattanzio (Energy Data Centre), with
guidance from Roberta Quadrelli, and based on the valuable input provided by
Mafalda Coelho da Silva (INEGI Institute of Science and Innovation in Mechanical
and Industrial Engineering, Portugal). The authors are indebted to the support and
guidance of Nick Johnstone (IEA Chief Statistician).
Thanks also go to the IEA Energy Efficiency Division for their inputs, particularly
to Melanie Slade, Edith Bayer and Cornelia Schenk and to the IEA
Communication and Digital Office for their help in producing the report, particularly
Astrid Dumond, Isabelle Nonain-Semelin, Clara Vallois, Gregory Viscusi and
Therese Walsh. The manuscript was edited by Justin French-Brooks.
The IEA is grateful to the following contributors, who kindly gave their time to
provide input:
Valerija Tot, Nisha Dutta, Shamim Ahmad, Andrew Starr – Department of
Industry, Science, Energy and Resources (DISER), Australia
Felipe Klein and Carla Achão – EPE; Samira Sousa and Alexandra Maciel –
Ministry of Mines and Energy (MME), Brazil
Mónika Forgo, Taran Singh, Joe Wang, Naima Behidj, Fumiko Yamada,
Liu Yantao and Robert Blain – Demand Policy and Analysis Division, Office of
Energy Efficiency, Natural Resources Canada (NRCAN)
Hernán Sepulveda, Charlotte Pertier Navarrete, Luis García Picart – Ministerio de
Energía, Chile
Victor Bazán and Catalina Villalobos – Energy Planning Secretariat (SEPSE),
Costa Rica
Leena Timonen and Virve Rouhiainen – Statistics Finland; Lea Gynther – Motiva
Ltd, Finland
Niklas Herzig – Federal Ministry for Economic Affairs and Climate Action,
Germany
Electrical and Mechanical Services Department of the Government of Hong Kong,
China
Demand-side data and energy efficiency indicators Acknowledgements
A guide to designing a national roadmap
PAGE | 5
I EA. CC BY 4.0.
Suhyeon Nam – Korea Energy Economics Institute (KEEI), Korea
Odón de Buen and Juan Ignacio Navarrete – National Commission for the Efficient
Use of Energy (Conuee), Mexico; Heberto Barrios Castillo, Velvet Rosemberg
Fuentes, Juan Carlos Lopez Gaviño and Brizian Renata Martínez – SENER,
Ministry of Energy, Mexico
Gigih Udi Atmo, Qatro Romandhi, Robi Kurniawan, Nurcahyanto and Devi Laksmi
– Directorate General of Newand, Renewable Energy and Energy Conservation
EBTKE, Indonesia; Evi Wahyuningsih, country consultant, Indonesia
Grażyna Berent – Enterprises Department, Statistics Poland and Ryszard Wnuk
– Department of Heating, Ministry of Climate and Environment, Poland
Pilar de Arriba Segurado, Patricia Isabel Bañón – Institute for Diversification and
Saving of Energy (IDAE), Ministry for the Ecological Transition and the
Demographic Challenge, Spain
Sukanya Nanta – Strategy and Planning Division; Pongpan Vorasayan and
Nattapon Runprasaeng – Energy Regulation and Conservation Division; Sasikarn
Harnpradit and Suthanee Vechasit – Energy Efficiency Promotion Division;
Sutthasini Glawgitigul, Siriyaporn Petchumli, Wisaruth Maethasith,
Suthanee Wachasit, Siriphat Khwunpetch, Lumyai Mungpanklang and
Siriyaporn Petchumli – Department of Alternative Energy Development and
Efficiency (DEDE), Ministry of Energy Thailand
Bilal Düzgün, Hakan Kaya, Halil Oruc and Saniye Keser – Department of Energy
Efficiency and Environment, Republic of Türkiye
Niklas Notstrand – Swedish Energy Agency, Sweden
Simon Parker and Elizabeth Waters – BEIS, United Kingdom
Ian Mead – Office of Energy Demand and Integrated Statistics, US Energy
Information Administration (EIA), United States.
Demand-side data and energy efficiency indicators Tables of contents
A guide to designing a national roadmap
PAGE | 6
I EA. CC BY 4.0.
Table of contents
Executive summary .............................................................................................................. 7
1. End-use data and energy efficiency indicators ............................................................. 9
Disentangling the different drivers of final energy consumption ................................................ 9
The importance of end-use data and energy efficiency indicators .......................................... 12
2. Towards structured data collection .............................................................................. 18
Enablers for the development of energy efficiency indicators ................................................. 18
3. Towards a national roadmap ......................................................................................... 23
Country-level assessment framework ...................................................................................... 23
Developing a roadmap for energy efficiency indicators at the national level ........................... 25
Roadmap validation ................................................................................................................. 26
4. A roadmap for the development of energy efficiency indicators .............................. 28
Building the roadmap ............................................................................................................... 28
Plan .......................................................................................................................................... 31
Do ............................................................................................................................................. 39
Check ....................................................................................................................................... 44
Act-adjust ................................................................................................................................. 46
Additional remarks ............................................................................................................. 49
Conclusion ........................................................................................................................... 50
Surveys and best practices ............................................................................................... 51
Annex I: Country/economy survey on roadmap ....................................................................... 51
Annex II: Survey responses from Australia .............................................................................. 54
Annex III: Survey responses from Brazil .................................................................................. 58
Annex IV: Survey responses from Canada .............................................................................. 60
Annex V: Survey responses from Chile ................................................................................... 63
Annex VI: Survey responses from Costa Rica ......................................................................... 65
Annex VII: Survey responses from Hong Kong, China ............................................................ 67
Annex VIII: Survey responses from Indonesia ......................................................................... 69
Annex IX: Survey responses from Mexico ............................................................................... 71
Annex X: Survey responses from Thailand .............................................................................. 74
Annex XI: Survey responses from the United Kingdom ........................................................... 76
Annex XII: Survey responses from the United States .............................................................. 79
Annex XIII: Results from the Menti survey ............................................................................... 82
Annex XIV: Country assessment ............................................................................................. 86
Demand-side data and energy efficiency indicators Executive summary
A guide to designing a national roadmap
PAGE | 7
I EA. CC BY 4.0.
Executive summary
Energy efficiency is a central element of achieving carbon-neutral energy
transitions. It also brings important co-benefits such as job creation, energy
security, higher productivity, improved air quality, savings on energy bills, and
improved comfort and wellbeing.
Tracking efficiency progress is only possible with detailed data – at end-use level
– and indicators that allow the disentangling of the effects of different energy
consumption drivers (e.g. activity, structure and efficiency). Efficiency indicators
serve many different purposes, for example in policy making, monitoring targets,
making energy projections, developing scenarios and planning, and
benchmarking.
The collection of end-use data and the development of energy efficiency
indicators is not a straightforward process for any country around the globe. It
should be grounded on a robust and detailed data collection process and based
on international methodologies in order to allow for comparability and
interpretation across countries.
As a complement to the IEA’s energy efficiency technical manuals
(Fundamentals on Statistics and Essentials for Policy Making), this guide is a
strategic document looking at the whole value chain in the development of
efficiency indicators – from the initial point where the need for data and indicators
arises, to the later dissemination and data use stages. It is intended to be a
useful resource for practitioners across the world, assisting them in the process
of developing a roadmap to energy efficiency indicators at the national level.
The development of this document followed a participatory approach and was
grounded on consultation with a number of partner countries/territories for
validation and to ensure its applicability to a diversity of contexts.
This guide also reflects the national experiences gathered during the
consultation process. They are recounted here to facilitate the sharing of best
practices among countries. These experiences can be used as examples when
establishing a new process or revamping an existing process.
The guide is for professionals and decision makers in statistical offices, energy
ministries and efficiency agencies alike, describing options and good practices
for the collection of energy end-use data and the development of energy
efficiency indicators. In parallel, it can also be used as an assessment tool,
helping countries/economies to locate their starting point, to assess their
Demand-side data and energy efficiency indicators Executive summary
A guide to designing a national roadmap
PAGE | 8
I EA. CC BY 4.0.
strengths and weaknesses, and to identify appropriate targets according to their
respective national interests and priorities.
It is designed to be applicable to countries/territories regardless of whether they
are still at initial stages of indicator development, or in contrast, they have
completed previous work on the topic based on sound data collection processes.
The approach to designing a national roadmap recognises that there can be
alternative pathways towards developing efficiency indicators, and lays out
options to be considered based on successful experiences gathered from the
countries/ territories consulted.
Chapter 1 introduces the concepts of end-use data and energy efficiency
indicators with a view to creating a common understanding of the topic, and
highlights the importance of having detailed end-use data and indicators and
understanding their application. Chapter 2 identifies a number of enablers to
carrying out this process. Chapter 3 introduces the roadmap as an assessment
tool. Chapter 4 describes the roadmap in detail and presents good practices in the
steps identified. Finally, a summary of all the interviews conducted with national
experts is available in the annexes of this document, following a common
template.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 9
I EA. CC BY 4.0.
1. End-use data and energy
efficiency indicators
Disentangling the different drivers of final
energy consumption
Robust energy efficiency indicators are those that allow you to track the progress
of energy efficiency specifically, and not other factors that can have an impact on
energy use. While this may sound self-evident, energy intensity and other
aggregate indicators are still widely used as a proxy for an energy efficiency
indicator, due to the unavailability of more detailed data on a larger scale. A
well-known example is the Sustainable Development Goal (SDG) indicator
SDG 7.3 on energy efficiency, which is defined as the total energy supply divided
by national GDP.
In other words, energy efficiency progress can only be tracked if data are available
that allow you to track energy efficiency progress (e.g. in relation to national
targets) and disentangle the effect of energy efficiency on energy use, distinct from
the effects of changes in activity and structure, among other drivers.
A generic energy efficiency indicator is defined as the ratio between the energy
variable and the corresponding activity variable. For this, and in order to develop
a proper energy efficiency indicator, it is appropriate to consider either sub-sector
or end-use data for both energy and activity (with similar boundaries), across the
main final consumption sectors (e.g. residential, services, industry and transport).
The figure below illustrates the disaggregation of end-use data required to build
energy efficiency indicators and the table that follows provides examples of
indicators that can be developed in this way. For more detail on methodologies,
please refer to IEA Energy Efficiency Indicators: Fundamentals on Statistics.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 10
I EA. CC BY 4.0.
Schematic disaggregation of total final consumption into sectors and sub-sectors or
end uses
IEA. CC BY 4.0.
Sector
Example of indicator
Residential
Residential energy consumption per capita
Space heating energy consumption per m
2
Services
Services energy consumption per unit of value added
Lighting energy consumption per employee
Industry
Industry energy consumption per industry unit of value added
Iron and steel energy consumption per tonne of steel produced
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 11
I EA. CC BY 4.0.
Transport
Transport energy consumption per vkm
Transport energy consumption per pkm (for passenger) or per tkm (for freight)
Other
Other industries energy consumption per unit of value added
Agriculture consumption per agriculture unit of value added
Notes: pkm = passenger-kilometre; tkm = tonne-kilometre; vkm = vehicle-kilometre.
Source: IEA (2014), Energy Efficiency Indicators: Fundamentals on Statistics.
It is important to highlight that to obtain a trustworthy energy efficiency indicator,
the accuracy of both the numerator and denominator in the ratio is of critical
importance. While solid and settled international methodologies and practices
exist for the collection of the energy variable (numerator), the activity
(denominator) part is more exposed to possible inaccuracies. This is because,
first, the activity data usually come from other administrative sources and therefore
assumptions and boundaries need to be assessed, and second, activity data need
a careful review to remove the effects that do not influence efficiency. For instance,
considering space heating indicators, it is important to collect data for occupied
dwellings only (instead of the total) to obtain a meaningful indicator. This requires
accurate analysis and strong co-ordination among different institutions and any
necessary processing of the raw data.
Similarly, the numerator and the denominator should have the same boundaries,
with a view to avoiding biased interpretations (e.g. the definition of the activities
included in the energy numerator and value-added denominator when developing
industrial sub-sector intensities). This may require strong collaboration and
exchanges between the respective institutions in charge.
At the international level a number of initiatives have been supporting
countries/economies with methodologies for the development of energy efficiency
indicators, and they have been compiling end-use data and efficiency indicators
following harmonised methodologies, for comparability. The IEA has been closely
collaborating with its counterparts on this topic.
International initiatives on energy efficiency indicators
A standardised approach is widespread amongst international organisations and
projects or initiatives, such as IEA Energy Efficiency Indicators Data Collection, the
Odyssee-Mure Project at EU level, Eurostat Efficiency Data Collection, also at the
EU level, the BIEE Project for Latin America, and the APEC efficiency indicators
initiative for the ASEAN.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 12
I EA. CC BY 4.0.
The importance of end-use data and energy
efficiency indicators
Energy efficiency has been identified as a central driver for achieving clean energy
transitions and a carbon-neutral world by 2050 (IEA, 2021). In addition to its effect
in mitigating greenhouse gas emissions, energy efficiency has a number of
additional benefits, such as the reduction of energy bills, improved air quality and
quality of life (e.g. indoor comfort), and potentially job creation.
The availability of detailed demand-side data enables a more robust assessment
of these transitions and bottom-up modelling work. In particular, the development
of energy efficiency indicators is essential to track energy efficiency
progress.
Detailed demand-side energy data coupled with activity data allow you to perform
decomposition analysis to disentangle the actual effect of energy efficiency from
those of activity, structure and other drivers, and to estimate the energy savings
that can be attributed to efficiency improvements. For more information on
decomposition analysis, please see IEA Energy Efficiency Indicators: Essentials
for Policy Making. In parallel with the energy efficiency indicators, the subsequent
development of carbon emission indicators at the end-use level is of utmost
importance to track decarbonisation efforts across countries. Because energy
data are a prerequisite for deriving carbon emission estimates, this report focuses
on the energy dimension.
Accurate and effective efficiency tracking, through end-use data and efficiency
indicators, is important for a diversity of potential users (not only policy and
decision makers, but also those in industry, markets, research and academia, and
society at large). Users are interested in efficiency indicators for several reasons,
including those summarised below.
Evidence-based policy making
The design of tailored and effective energy efficiency policies and their monitoring
and evaluation should be grounded in a factual understanding of the behaviour of
demand-side patterns. The collection of detailed data allows you to identify the
priority sectors and end uses to target, for example. As for policy evaluation, this
normally requires specific indicators to assess policy effectiveness
(e.g. comparing data from beneficiaries and others). Furthermore, the availability
of official efficiency indicators at national level strongly supports longer-term
analysis of energy use trends and further decision making.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 13
I EA. CC BY 4.0.
The SEAD initiative and UK-IEA Product Efficiency Call to Action
The SEAD (Super-Efficient Equipment and Appliance Deployment) initiative is an
international forum for exchange on policy making on product energy efficiency.
Through the SEAD initiative, the IEA is working closely with the UK government to
encourage a higher level of ambition on product efficiency, from COP26 and
beyond. In particular, it seeks to double the efficiency of four key product types by
2030: industrial motors, air conditioners, refrigerators and lighting.
In order to monitor whether these targets are met, significant emphasis has been
put on the availability of disaggregated data on energy consumption, stocks by
appliance type, and the efficiency levels of appliances being sold in the market.
The availability of such data allows the tracking of energy consumption per
appliance and hence the estimation of efficiency progress over time.
Whereas several countries are already collecting data on air conditioners,
refrigerators and lighting, the same data for industrial motors may be more difficult
to obtain, and hence, it is important to keep data availability in mind when
assessing new data collection opportunities.
Monitoring progress against targets
Regardless of the status of energy efficiency policies, a large number of countries
have adopted targets such as for the reduction of the overall economy’s energy
intensity or even sectoral targets for the reduction of energy use. The availability
of detailed end-use data allows you to monitor, from a bottom-up perspective, the
progress made against such targets.
Indonesia’s General Plan for National Energy
Indonesia’s Presidential Regulation No. 22 Year 2017, the so-called General Plan
for National Energy, foresees among other goals a reduction in final energy
consumption of 17%, a reduction in energy intensity of 1% per year, and the
improvement of labelling for energy efficiency on electrical appliances.
Specifically regarding appliance standards and labelling schemes, it is important
to monitor energy consumed by appliance type, in order to understand how
effective such programmes have been in delivering energy efficiency savings, and
how to adjust the programme in the market to promote continued savings over
time.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 14
I EA. CC BY 4.0.
Making energy projections, developing scenarios and
planning
Many decisions taken today will affect energy systems in the coming decades. For
example, whether (and by how much) new energy production capacity should be
added or electrical grids strengthened. The existence of robust and detailed data
allows you to better understand how energy is consumed across final consumption
sectors and better supports longer-term energy planning.
In particular, up-to-date information reflecting the latest trends (e.g. the
digitalisation of society) plays an important role in allowing for robust projections
and planning.
Forecasts of electricity demand in Australia’s national electricity market
The Australian Energy Market Operator (AEMO) also provides strategic
forecasting and planning advice. Energy efficiency is the first fuel and hence a key
factor in flattening the growth of electricity consumption (along with other benefits).
Understanding the efficiency effect is of major importance to developing reliable
projections of energy savings.
This is only possible if detailed data are available. The absence or inaccuracy of
data may lead to very costly decisions such as overestimating future loads and
overinvesting in the grid.
The top figure shows how AEMO revised their forecast in 2016 to take into account
the effect of energy efficiency in future energy consumption. The overall expected
efficiency effect is in orange. This shows how reliable and disaggregated data are
key to planning investment in assets and avoiding investment in assets that will
not be used.
The figure at the bottom shows the contribution of each appliance type given their
household diffusion.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 15
I EA. CC BY 4.0.
Forecasts for Australian operational consumption to 2035
Source: Australian Energy Market Operator (2016), National Electricity Forecasting Report.
Change in demand for energy services in Australia for different appliances
Source: Australian Energy Market Operator (2016), National Electricity Forecasting Report.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 16
I EA. CC BY 4.0.
Benchmarking
Benchmarking is becoming popular in several countries. One way to assess
national performance is to compare it with other countries, highlighting the need
for comparable indicators across geographies through harmonised data and
methodologies. Benchmarking helps in the selection of critical areas that need to
be prioritised and the identification of opportunities where potential benefit-cost
ratios are greatest.
New benchmarking report on the pulp and paper sector in Brazil developed
jointly by EPE and the IEA
In the case of economically important industry sectors, countries may be interested
in deepening their analysis and seeing how they compare with other countries
worldwide. This allows for the identification and adoption of good practices towards
improved energy efficiency.
Brazil published a benchmarking report for the pulp and paper industry, which is
highly important in the Brazilian economy. The pulp and paper industry has been
increasing its relevance in Brazil, and its energy consumption has increased from
5% of final industrial consumption in 1970 to 16% in 2020.
The report is one of a series of international benchmarking analyses developed
jointly by EPE and the IEA, with key industry organisations, to evaluate progress
on energy efficiency in key sectors and identify opportunities for improvement. EPE
(Empresa de Pesquisa Energética) is Brazil’s government-funded agency to
support energy policy makers with studies and research related to energy
planning.
Naturally, there are costs inherent in data collection and countries are often faced
with budgetary constraints. Data collection in this report refers to the four main
methodologies for collecting data according to IEA Energy Efficiency Indicators:
Fundamentals on Statistics, being administrative sources, surveys, modelling and
metering. Specifically for the residential sector, Eurostat’s MESH – Manual for
Statistics on Energy Consumption in Households can also be useful.
However, as demonstrated above, the cost of having no data, or inadequate data,
may be even higher. Decisions (and investments) made on the basis of inaccurate
or defective information may be significantly costlier than accurately monitoring
efficiency progress. Furthermore, energy efficiency financing programmes are
often used as a way to achieve energy efficiency improvements. The existence of
background information is a clear asset for the stakeholders involved, especially
lenders.
Demand-side data and energy efficiency indicators 1. End-use data and energy efficiency indicators
A guide to designing a national roadmap
PAGE | 17
I EA. CC BY 4.0.
Demand-side data coupled with activity data allow you to perform decomposition
analysis in order to disentangle the actual effect of energy efficiency from those of
activity, structure and other drivers, and to estimate the energy savings that can
be attributed to efficiency improvements.
In order to support countries in energy efficiency tracking, Chapter 2 presents key
enablers for the development of energy efficiency indicators, while
Chapters 3 and 4 present a strategic roadmap to illustrate how data can be used
as an assessment tool and as a guide for developing efficiency indicators at a
national level, respectively.
Demand-side data and energy efficiency indicators 2. Towards structured data collection
A guide to designing a national roadmap
PAGE | 18
I EA. CC BY 4.0.
2. Towards structured data
collection
Enablers for the development of energy
efficiency indicators
The development of energy efficiency indicators at a national level is often a multi-
stakeholder effort, as data (especially activity data) are typically scattered and
collected by different institutions. Energy statisticians and analysts aiming to
develop such indicators acknowledge the existence of several barriers in this
process. This section identifies and presents key enablers that may be useful in
helping overcome existing barriers.
Political will and awareness
An important enabler of the development of energy efficiency indicators is the
degree of priority given to the subject matter – energy efficiency. In many
countries, energy efficiency is high on the political agenda and seen as an
important means of decarbonisation (along with its wider benefits, as described
above). The prioritisation of energy efficiency at a national level requires
continuous awareness-raising among policy and decision makers about its
importance and multiple benefits, particularly for people-centred clean energy
transitions: job creation, improved quality of life and comfort standards, poverty
alleviation (lower bills), and so on.
The basic pillar for the development of energy efficiency indicators at a national
level is the acknowledgement of energy efficiency’s importance, backed up by a
strong policy framework, an understanding of the need for data
1
to track its
progress, and evidence-based policy design and evaluation. Once this
recognition is established (both in terms of the subject matter and the related data
needs), it becomes easier to justify proper resource allocation to the collection of
end-use data and the development of efficiency indicators.
1
This presupposes that energy efficiency statistics, as with statistics in general, are acknowledged as a public good
(according to the Fundamental Principles of Official Statistics of the UN).
Demand-side data and energy efficiency indicators 2. Towards structured data collection
A guide to designing a national roadmap
PAGE | 19
I EA. CC BY 4.0.
A trusted and empowered data collection system
Statistical data collection should be grounded on a solid framework mandated
and enforced by law. This allows there to be, simultaneously, one or more
government institutions with clearly established responsibilities and tasks for data
collection, and an obligation on businesses, industry and citizens (depending on
the data collection target) to collaborate and provide the requested data in an
accurate and timely manner, making data collection efforts feasible.
Another relevant consideration is the need for responsible institutions
(e.g. statistical offices) to be seen as independent and trusted bodies, increasing
social acceptance of official statistics in general, and efficiency indicators in
particular. For energy efficiency statistics, given the high granularity or resolution
of the data at stake, trust becomes of utmost importance to ensure that
respondents continue to collaborate. Data sharing is often formalised through
non-disclosure agreements.
Proper resource allocation
All statistical programmes and data collection processes rely on an officially
allocated budget. Statistical officers and efficiency professionals often argue that
the resources allocated to this topic are insufficient. It is important that
governments allocate appropriate resources to energy data collection, and in
particular demand-side energy consumption patterns, as these require additional
detail and effort. The appropriate level of funding depends on a number of aspects
related to the context. For example, the size of the country, existing data sources,
how advanced data collection is and what the data gaps are, all represent
important variables. It is likely that the resources available will be insufficient to
cover all data needs in the first year(s). That is why creating a longer-term data
collection strategy, which identifies priority indicators to reflect the
national/regional background, may help set a coherent budget for a longer time
frame.
The necessary resources include a proper budget allocation for data collection,
having sufficient (and qualified) human capital to do the job, and even the essential
basic infrastructure, such as offices, computers and other ICT (e.g. a solid data
management infrastructure). In order to avoid unnecessary new data collection
costs, we recommend thoroughly investigating existing data collection processes
and data, building on them wherever feasible (adjusting, if necessary), and only
thereafter adding to existing processes. More specifically, this means taking
advantage of existing data (e.g. administrative data) and data collection processes
(e.g. existing surveys).
Demand-side data and energy efficiency indicators 2. Towards structured data collection
A guide to designing a national roadmap
PAGE | 20
I EA. CC BY 4.0.
While all countries operate with limited resources, raising the profile and
awareness of the importance of data and evidence-based policies is a key enabler
of the proper allocation of funds to data collection.
In cases where national resources are truly constrained, countries may consider
looking at options for external financing. Funds may be available from international
organisations to support energy data collection in developing countries
(sometimes under a different scope from energy, such as living standards
measurement surveys), or for broader collaboration programmes or projects in
which data collection can be included as an individual component. For example,
the Energy Sector Management Assistance Program (ESMAP) is a partnership
between the World Bank and other partners to help low- and middle-income
countries reduce poverty and boost growth through sustainable energy solutions,
including an energy data and analytics component.
Another source of potential financing may be regional banks (such as the African
Development Bank or the Asian Development Bank). These institutions provide
loans, technical assistance, grants and equity investment to promote social and
economic development. One option to explore would be adding a data component
to energy efficiency financing projects. Also, by linking the development of energy
efficiency indicators with climate reporting and tracking, there may be
opportunities under the Global Environmental Facility (GEF).
The IEA is keen to provide technical assistance and methodological support for
data collection and management.
Staff capacity and stability
Qualified staff who understand key efficiency concepts and the methodological
particularities of efficiency indicators (including methodological differences when
reporting more aggregated data) are an absolute requirement for the development
of energy efficiency indicators at a national level. In addition, it is important to build
capacity in different data collection methodologies (including administrative
sources, surveys, modelling and metering), and how to derive indicators from the
raw data collected.
Longer-term visibility and planning are only possible if staff are provided with the
right conditions. For instance, contract durations should be no shorter than the
time needed to undertake the tasks inherent to a data cycle (e.g. design,
collection, processing and dissemination) and should be resilient to higher-level
changes, such as those related to political changes in the government.
In addition, there is also the need to ensure backup capacity. In smaller or
developing economies, staff working on efficiency indicators or even energy
indicators may be very limited in number (sometimes it can be a single responsible
Demand-side data and energy efficiency indicators 2. Towards structured data collection
A guide to designing a national roadmap
PAGE | 21
I EA. CC BY 4.0.
person). For this reason, the existence of a backup resource and detailed
documentation is an important source of resilience in the case of staff changes.
Capacity building on efficiency indicators needs to be a continuous effort,
and in particular it should be planned so as to compensate for staff turnover, to
avoid the loss of important knowledge.
The IEA has been actively supporting countries with capacity building on energy
efficiency indicators, both with in-person training courses and making available a
range of resources (e.g. manuals and online training) including a database
featuring methodologies for collecting data on energy end uses across sectors
(transport, industry, residential, services). This helps promote the adoption of the
UN International Recommendations for Energy Statistics (IRES) and other
relevant international methodologies, to allow for comparable data and insights
across countries.
Data collection strategy
A well-developed data collection strategy means one that:
Is planned in accordance with the national context and allocated budget.
Promotes dialogue between statistics and policy making to raise awareness of
existing data needs.
Facilitates institutional arrangements for data collection.
Embeds data into the different stages of the policy cycle.
Albeit not specifically focused on end-use data and efficiency indicators, nor
energy at large, the Partnership in Statistics for Development in the 21st Century,
Paris21, helps low-income and lower middle-income countries design, implement
and monitor national strategies for the development of statistics, and to have data
for all SDG indicators. Paris21 may be a useful resource for countries looking for
support to strengthen their statistical system, which will in due course facilitate the
development of efficiency indicators.
In order to shed further light on the development of energy efficiency indicators at
a national level, this document proposes a roadmap to guide countries along the
way.
Multilateral collaboration both at national and
international level
Given the scattered nature of the end-use data and corresponding activity data
needed to develop efficiency indicators, the promotion of strong institutional
collaboration and communication is essential. In addition, organisational
Demand-side data and energy efficiency indicators 2. Towards structured data collection
A guide to designing a national roadmap
PAGE | 22
I EA. CC BY 4.0.
structures with a clear definition of responsibilities and clear communication
channels can provide strong support for the development and updating of
efficiency indicators.
These enable an easier and less costly data acquisition process, for example
through the existence of data sharing agreements. There is a strong rationale for
staff in one ministry knowing who their counterpart is for a specific topic in another
ministry (e.g. road vehicle stocks in the transport ministry).
However, even if the relevant contacts are known, where there is significant
bureaucracy to overcome for each data sharing request, continued collaboration
is likely to become quite burdensome and challenging.
To avoid this, institutional collaboration should be fostered at a high level
(regardless of whether the approach is more or less formal), enabling a higher
level of engagement and accountability among stakeholders. This is believed to
improve the consistency and efficiency of statistical systems.
At the international level, co-operation is also an important driver of improved data
collection processes. This can be done, for instance, by inviting countries to share
their experiences of data collection methodologies or the financing of data
collection. It can also be done by the development of joint work and common
methodological frameworks for the development of indicators, in line with
international methodologies, allowing for comparable data and findings. Sharing
expertise across countries and organisations is key to learning good
practices, and the IEA is keen to facilitate these exchanges.
The links between the enablers listed above and the roadmap stages are defined
in Chapter 4.
Demand-side data and energy efficiency indicators 3. Towards a national roadmap
A guide to designing a national roadmap
PAGE | 23
I EA. CC BY 4.0.
3. Towards a national roadmap
Country-level assessment framework
This document presents a roadmap for the development of energy efficiency
indicators at a national level. But before introducing and applying a roadmap to a
specific country, it is important to understand the current availability of end-use
data and the stage of development of energy efficiency indicators in the country
of analysis. To help with this, presented in the figure below is a framework for
assessing a country’s status with regard to energy efficiency indicators.
This assessment framework aims to help countries locate their starting point, and
to identify appropriate targets according to their national interests and priorities.
Simply put, it answers questions like:
What data are available in my country?
What robust and insightful indicators can I develop with them?
What indicators do I need to track the policies we have in place and monitor
progress towards my targets?
Each country can develop indicators for one or more final consumption sectors
with or without full coverage across end uses, depending on national
characteristics, objectives, priorities and resources.
Countries that have yet to start developing efficiency indicators can work on one
or a few sectors at a time, or alternatively in parallel across sectors. It is also
possible to collect energy end-use or activity data for a given sector at different
points in the process, as occasionally happens in many countries. Typically, this
does not allow efficiency indicators to be developed for that sector, but it means
that the country has taken some initial steps and has the basis for further work to
be developed in due course.
Then countries can decide whether to tackle all sectors or to stop the process
when partial indicators have been developed. Once all the sectors and the
indicators are ready, the process is complete as shown in the right-hand part of
the figure. The number of sectors and the order they are taken in differ for each
country and depend on the priorities set at a national level.
While acknowledging that at a national level the indicators to be developed will
depend on the country’s specific priorities, such as policy tracking, a number of
efficiency indicators are typically highlighted internationally (e.g. the IEA Energy
Efficiency Indicators Framework). Hence, achieving full coverage according to the
Demand-side data and energy efficiency indicators 3. Towards a national roadmap
A guide to designing a national roadmap
PAGE | 24
I EA. CC BY 4.0.
roadmap represents a position where the efficiency indicators often seen in
international frameworks or widely targeted by countries have been achieved. Of
course, there is always room for further improvement and scope to develop more
detailed indicators where there is the will, interest and resources to do so.
Framework for assessment of a country’s status in the development of energy
efficiency indicators
IEA. CC BY 4.0.
To better understand this assessment framework, the example in the following
figure shows the case for an imaginary country: “Statisland”. It assesses the
country’s current stage and indicates the pathways for improved indicator
coverage. In this case, Statisland is at the stage where the country has partial
indicators for some sectors.
Looking in closer detail, we can imagine that for the residential sector data are
available for some end uses (space heating, water heating, cooking, and lighting
and appliances are reported together), but not all. With regard to activity, data on
population and occupied dwellings are available, but not residential floor area or
appliance stocks.
In the case of the transport sector, activity data are available for rail and air
transport (pkm and tkm), but not for road or water transport. Similarly, for energy
use, no data are available by segment or vehicle type. Statisland has data
available on total consumption by mode from its national energy balances.
The services sector is the sector with least coverage. Data on energy consumption
by end use/sub-sector are not available, and for activity, services value added is
only available as a total.
Services
Industry
Transport
Energy
efficiency indicators
for some
end uses/sectors
Energy data
Activity data
All end uses
Some end uses
All end uses
Some end uses
Residential
energy
efficiency
indicators
No energy
efficiency
indicators
Energy
efficiency
indicators
for all end
uses across
sectors
Residential
Demand-side data and energy efficiency indicators 3. Towards a national roadmap
A guide to designing a national roadmap
PAGE | 25
I EA. CC BY 4.0.
Finally, for industrial energy consumption a similar breakdown to the one from the
energy balances is available, but there is no additional detail on specific industries
such as rubber and plastics, or cement. As for activity data, information is available
on value added with a similar breakdown by economic activity to that of energy,
as well as physical production data for steel and cement.
Once the starting point has been assessed for the country, in this case Statisland,
the staff responsible for the enhancement of the indicators can identify gaps and
set priorities. For instance, we can imagine that the cement sector is highly
relevant for the country, but available data are not sufficient to monitor trends and
facilitate efficiency in the industry. Therefore, Statisland officials can follow the
path described in Chapter 4 to create the indicators needed.
Example of application of the assessment framework to the country of Statisland
IEA. CC BY 4.0.
Developing a roadmap for energy efficiency
indicators at the national level
Previous sections made the case for the importance of energy efficiency indicators
for policy design and evaluation, energy projections and forecasting,
benchmarking and efficiency tracking at large. Following an initial assessment of
a country’s situation on energy efficiency indicators, and where it wants to get to
according to its needs and priorities, this section proposes a work flow to help
guide national statisticians and policy makers through this journey.
The goal is to develop a roadmap that helps countries to start collecting or
complement existing end-use data, regardless of the stage they may be at, and to
Demand-side data and energy efficiency indicators 3. Towards a national roadmap
A guide to designing a national roadmap
PAGE | 26
I EA. CC BY 4.0.
develop or improve their respective energy efficiency indicators. It seeks to be a
resource both for countries wishing to initiate data collection and for countries with
existing activity, but who wish to expand to new or more detailed data series or
indicators.
This document proposes a flowchart that is sufficiently generic to be applied in
different geographies, i.e. in countries with different political settings and priorities,
and with different profiles of energy use and institutional arrangements and
resources. The roadmap implementation steps are presented in a flowchart
(intentionally generic) in the following chapters and detailed in the paragraphs that
follow.
The roadmap identifies the necessary steps to take to develop energy efficiency
indicators and/or to collect related energy and activity end-use data at a national
level. It is intended to be comprehensive and cover the whole process, roughly
following a PDCA (plan-do-check-act) approach to project planning – detailed in
the following paragraphs (with similar colour coding to that of the roadmap
flowchart):
Plan Identify a need or opportunity
Do Carry out activities necessary for the change
Check Review the activities, analyse the results
Act Take action to improve based on learning experience (also
known as Adjust).
Plan-do-check-act cycle representation
IEA. CC BY 4.0.
Roadmap validation
In order to test and validate the roadmap’s applicability in the real world, we
consulted with a number of partner countries both to validate it and to provide
additional concrete content to illustrate its application in different contexts.
Our consultation included the preparation of a written survey (presented in
Annex I: Country/economy survey of roadmap) and a number of interviews with
stakeholders from countries/territories in different geographies and at different
PLAN
ACT
ADJUST
DO CHECK
Demand-side data and energy efficiency indicators 3. Towards a national roadmap
A guide to designing a national roadmap
PAGE | 27
I EA. CC BY 4.0.
stages along the pathway to developing energy efficiency indicators (some in the
early stages, others with work initiated but with opportunities for continued
development, and others with more consolidated experience).
Besides the invaluable insights and knowledge gathered from those working “in
the field” and dealing with these issues on a daily basis, the interviews and the
surveys also allowed us to identify good practices and tips that we have now
shared in the boxes showing case studies throughout this guide.
The countries/territories (hereafter called countries for simplicity) that kindly
agreed to collaborate on this project are: Australia, Brazil, Canada, Chile,
Costa Rica, Hong Kong, Indonesia, Mexico, Thailand, the United Kingdom and
the United States.
The feedback received from these countries allowed us to verify that the steps
identified in the roadmap could apply to all these different contexts and to infer
that they could similarly be applied in other geographies.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 28
I EA. CC BY 4.0.
4. A roadmap for the development
of energy efficiency indicators
Building the roadmap
This section presents the roadmap in a graphic way and moves on to describe in
detail each of the steps that together create it. The roadmap is presented in a
similar format to a board game and is intentionally designed in an abstract way,
so that it can be applied to countries with different backgrounds and at different
stages of developing energy efficiency indicators.
The following figure shows the roadmap’s implementation steps for the collection
of end-use data and/or the development of energy efficiency indicators. It can be
applied to one or more final consumption sectors, or even to specific missing end
uses, according to the stage that a particular country has reached at a given
moment in time.
Despite having a linear flow, it is possible at any point in the process to go back to
previous stages if need be. It is also possible to skip steps if they are not relevant
or possible depending on the national context. There may be a number of reasons
that determine the applicability of some of the roadmap steps; for example,
applicability to federal states may be slightly different given the local (data)
governance landscape and the distribution of responsibilities among the different
levels and institutions.
Nevertheless, the flow shown below is deemed to be the most efficient and
effective process for the development of energy efficiency indicators at a national
level, reflecting the results of our consultation. One challenge of energy efficiency
indicators is that the necessary energy and activity data come from different
sources, which need to be consistently brought together to make sure that the
methodology and coverage are coherent. This requires good alignment between
different entities and the allocation of clear responsibilities. Theoretically it is
possible to develop energy efficiency indicators without government or ministry
endorsement. However, the lack of high-level support is likely to make it a very
challenging task (e.g. lack of resources, low priority among institutions holding
data), one that could eventually either fail to deliver the necessary data, for
instance, or develop lower quality results that are difficult to reproduce and/or to
sustain over time.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 29
I EA. CC BY 4.0.
Roadmap implementation steps for the development of energy efficiency indicators
IEA. CC BY 4.0.
At present, most countries are able to develop energy balances (with varying
levels of detail and accuracy). Because energy end-use data are not available in
energy balances, additional efforts are needed to collect such data. The existence
of sound national energy balances is not considered an absolute prerequisite for
the development of energy efficiency indicators. Still, it is an important milestone
and the existence of more aggregated data at the sectoral level very much
facilitates the process. It is also important that the end-use data collected are
consistent with more aggregated data from balances (this is further explained in
the Check and Act sections of the roadmap implementation).
Need arises
Government
or high-level
endorsement
Legal
framework
Designation of
responsible entity
Goal definition
and
priorities
Capacity
building
Data collection
plan
Institutional
arrangements
Mapping data
sources
and gaps
Resource
allocation
Good practices
and international
experiences
Design
methodology
(data collection,
storage,
processing)
Data collection
roll-out
Data
management
Data
validation
Data use
Dissemination
Data
analysis
Needs for future
adjustments
Act on
results
PLAN
DO CHECK
ACT
ADJUST
International
support
Legend
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 30
I EA. CC BY 4.0.
The steps where international collaboration could provide support are marked with
a box edged in blue. This highlights the importance of collaboration as a key driver
for the development of energy efficiency indicators, either through international
organisations or by partnering with other countries that could provide relevant
experience.
For easier understanding, the following figure shows the roadmap’s
implementation for the imaginary country of Statisland. This allows you to rapidly
see, first, how energy efficiency indicators can be implemented in a country, even
where previous work has been completed for several final consumption sectors,
and second, how priorities can be established, leading the development of the
whole workflow as shown in the figure.
Example of roadmap implementation steps for the development of energy efficiency
indicators in Statisland
IEA. CC BY 4.0.
New policy for
energy efficiency
in buildings
highlights need for
indicators
The ministry of
energy recognises
that indicators are
needed to track the
new policy
There is an existing
regulatory
framework for
statistical data
collection
A new energy
efficiency agency is
established and is in
charge of energy
efficiency indicators
Suitable indicators
are identified for
tracking the
residential and
services sectors
Team is in place
and being trained in
surveying and
indicator
methodologies
A new household
survey is to be
designed; in the
meantime, sectoral
indicators will be
used
Data sharing
agreements are
established
Sources and
institutions are
mapped, identifying
gaps
Budget is allocated
based on initial
workplan
Good practices in
household surveys
are identified
(reach out to IEA)
Survey is designed,
following
international
guidelines
Survey is rolled out
Preprocessing of
collected data (incl.
anonymisation) and
storage
Robustness,
representativeness
and plausibility of
data/indicators are
assessed
Use of data (by
modellers, planners,
policy makers,
citizens, industry,
academia)
Dissemination (via
newsletters, web,
social media,
brochures, apps)
Data and indicators
are analysed
Identify lessons
learnt (e.g. sample
needs to be larger,
questionnaire needs
to be shorter)
Adjust the policy
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 31
I EA. CC BY 4.0.
It is important to note that the example provided does not aim to be prescriptive,
but merely illustrative, as individual countries can have various combinations of
data availability, national-level priorities for efficiency indicators and data collection
methodologies.
The paragraphs that follow provide more detail on each of the implementation
steps, including the key questions to be asked at each stage.
Plan
Need arises
(Linked enabler: Political will and awareness)
Is energy efficiency high on the political agenda?
Do data have a high profile?
Is there any planned or ongoing monitoring or evaluation work?
The development of efficiency indicators typically happens when individual
countries face the need to track their energy conservation and efficiency policies,
or energy efficiency progress in general (e.g. in line with decarbonisation efforts).
It may be that some countries have prioritised other aspects of energy policy, for
example electricity access or energy security, and have not regarded energy
efficiency as a national priority (despite being related). The acknowledgement of
the importance of energy efficiency and the drive to track its progress are an
important trigger for the development of efficiency indicators. Also, international
reporting requirements may be equally as important in initiating such work at a
national level.
Government or high-level endorsement
(Linked enabler: Political will and awareness)
Does the government or ministry see the value of energy efficiency indicators?
Does the government or ministry endorse the development of energy efficiency
indicators?
Once there is a degree of prioritisation around energy efficiency (e.g. work is
initiated to design new policies, or to minimise/optimise the investment in electricity
grids or installed capacity), it is important that the government or government
bodies (e.g. the energy ministry) recognise the importance of tracking progress in
the development of efficiency indicators and support their formation. This can be
done either formally (e.g. as part of national strategies) or informally (e.g. through
messages to public institutions). Government support is not an absolute
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 32
I EA. CC BY 4.0.
requirement for the development of energy efficiency indicators, but the existence
of high-level acknowledgement and impetus strongly facilitates the process.
Legal framework
(Linked enablers: Political will and awareness, trusted and empowered data
collection system)
Is there a regulatory framework that enables the collection of end-use data (either
stand-alone or part of a broader framework)?
If not, is it possible or relevant to create a new one?
Who or what institution is or would be in charge? What responsibilities would be
assigned?
Several countries have national data collection frameworks established under law,
which can be generic (e.g. a general law or regulation on statistics) or specific
(e.g. dedicated laws by topic, such as energy or energy efficiency). This
arrangement typically assigns the responsibility for collecting and processing data
to a designated institution; it can also designate whether the submission of data is
mandatory or voluntary and the specifics of compliance or incentives for
collaboration. It may also include aspects such as data protection (e.g. privacy
and confidentiality issues).
Where there is no existing national framework for end-use data collection or the
development of efficiency indicators, it can be sensible to either establish a new
one, or adjust an existing one (e.g. adding to the responsibilities of an existing
entity).
Integrating the development of energy efficiency indicators into national
regulation in Mexico
While many countries establish a regulatory framework for statistical data
collection in general, or energy statistics in more detail (even if partially), it is not
as common to see energy efficiency indicators explicitly mentioned in such
regulations. This may be, in part, because such regulatory frameworks came into
force several years ago, when awareness of this topic was lower than today.
In the case of Mexico, the government has acknowledged the importance of
indicators for tackling climate action and gaining a better understanding of the
country’s energy context and needs. It has done this by including energy efficiency
indicators in national legislation to evaluate and monitor the progress of Mexico’s
Transition Strategy to Promote Cleaner Technologies and Fuels.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 33
I EA. CC BY 4.0.
End-use energy efficiency indicators and their international comparison
(benchmarking) are mentioned in Article 18 of the Sustainable Energy Use Law
and in its associated regulation. In December 2015 this law was substituted by the
Energy Transition Law, in which the energy efficiency indicators are mentioned in
Article 29. This regulation establishes that energy efficiency indicators by sector
should be part of the Energy Transition Information System.
This has been enabled by high-level awareness of the importance of energy
efficiency and of the existence of indicators to track its progress. Specifying the
topic within the law is a way to ensure that this work stream becomes sustained
over time. Further information is available in Annex IX.
Designation of responsible entity
(Linked enablers: trusted and empowered data collection system and proper
resource allocation)
Is there an existing national institution that can take over energy efficiency
indicator duties?
If not, is it possible to create a new one?
In countries that do not have a legal framework for end-use data collection, it is
still possible to develop efficiency indicators if the responsibility has been
informally assigned to a national institution, or if an national institution is interested
in voluntarily undertaking such a task. The latter may be less common, although
there are cases where the development of efficiency indicators has started
organically, without a mandate. These entities typically have limited resources and
are less likely to commit unless they have been formally designated (and have
resources allocated).
Depending on the country, responsibility for the development of energy efficiency
indicators typically falls under the umbrella of one of three key types of national
institution: statistical offices, energy ministries or energy efficiency agencies. In
any case, close collaboration between all of them is an important asset for the
production of consistent and coherent data sets.
Goal definition and priorities
(Linked enablers: trusted and empowered data collection system and proper
resource allocation)
What indicators are needed to address the existing needs?
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 34
I EA. CC BY 4.0.
Can these indicators be developed based on available data?
What priority indicators need to be developed?
Once a responsible entity is identified, the focus shifts to revisiting the goals of the
indicators to be developed and the corresponding data to be collected. Different
indicators deliver different messages, and hence it is important to define what
indicators are needed based on the tracking needs identified at the start. Similarly,
an initial assessment of what information already exists and what else is needed
may be relevant to negotiating allocated funds (in subsequent steps). This is also
the time to identify priorities in instances where there are several needs to be
addressed.
The national energy efficiency plan, and identification of indicators needed
in Chile
Chile published its first ever energy efficiency law in 2021. It aims to contribute to
achieving climate neutrality by 2050. In the future, specific data needs may
emerge, arising from the law’s monitoring requirements and the measures
foreseen in the energy efficiency plan. The Ministry of Energy is developing a line
of work related to information, its co-ordination and interoperability between
different public and private institutions.
Chile estimates its energy savings by comparing actual energy use with that
expected according to a linear regression of final energy consumption against total
GDP – disaggregated data are not available on a yearly basis to perform a
decomposition analysis. However, the national energy efficiency plan mentions the
type of data and indicators to be developed to track the progress of the plan’s
targets. For example, energy use per unit of value added for productive sectors,
vehicle stocks, passengers and distances travelled by vehicle type/mode, fuel
efficiency by vehicle type, and residential and services end uses and floor areas.
In particular, Chile has an interest in the mining sector due to its prominence in the
country. The government is seeking to develop suitable indicators for this
productive sub-sector that allow for improved capture of the efficiency effect and
which can disentangle it from factors related to the deterioration of mineral sources
and greater carrying distances.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 35
I EA. CC BY 4.0.
Resource allocation
(Linked enablers: proper resource allocation and staff capacity and stability)
What resources are needed to develop the required indicators?
What budget is available initially and what activities can it cover?
The allocation of a proper budget is an essential step. This is not only to collect
the required data, which is in itself an important element of the overall budget, and
one which may largely determinate the choice of the data collection methods and
their accuracy. It is also essential for the development or improvement of the
national energy data management system, the hiring of qualified staff and staff
training, and the acquisition of the necessary physical and digital infrastructure.
In principle, surveys should be as short and low-cost as possible to address data
needs. Countries often conduct less detailed surveys at relatively high frequency
and undertake more ambitious and detailed data collection (with higher budgetary
requirements) at longer intervals.
Defining the relevant budget in the United States
The US Energy Information Administration (EIA) provides independent, impartial
information to support the development of US energy efficiency indicators. The
development of these indicators is not specifically itemised in the budget, but is
instead a component within EIA’s overall annual appropriation.
The US federal government budget formulation process is complex, involving
multiple layers of negotiation and approval, ultimately resulting in legislative action
by Congress. The EIA is assigned a budget request level by the Department of
Energy, which is submitted for review and approval by the Office of Management
and Budget. The EIA provides a justification narrative explaining how
appropriations would be spent. The Office of Management and Budget’s approved
levels are included in the President’s budget request, which is submitted to
Congress. Enacted appropriations may include specifically directed funding for EIA
initiatives.
The EIA has traditionally provided its efficiency indicators within the annual
appropriation process outlined above.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 36
I EA. CC BY 4.0.
Mapping data sources and gaps
(Linked enablers: data collection strategy and multilateral collaboration)
What data are already available?
What are the data sources and institutions to contact?
What data are still missing?
The identification of relevant indicators for policy tracking, and the corresponding
data needed to calculate them (including energy end-use and activity data), is
followed by the process of mapping existing data sources across national
institutions or databases. This allows you to understand what data are already
available (e.g. being collected for other purposes – floor areas may be collected
for taxpaying reasons) and what data need to be collected through new methods,
or by adapting existing ones. In this sense, the existence of sound energy
balances can be an important asset for a more detailed disaggregation of data by
end use, and for the subsequent development of energy efficiency indicators.
Institutional arrangements
(Linked enablers: data collection strategy and multilateral collaboration)
Are any other institutions already collecting data useful for efficiency indicators?
Is it possible to create a seamless process to simplify data sharing among these
institutions (potentially with benefits for all parties)?
Data for energy efficiency indicators are often collected by different institutions.
The existence of arrangements between institutions (or departments within the
same institution) that collect and own data useful to other institutions may simplify,
speed up and reduce the cost of data collection. Ideally, such arrangements
should be established in a formal way (e.g. through written data sharing
agreements) and at a high level, and be implemented at the operational level,
complemented by informal agreements as needed. For this, it is important that
decision makers and high-level stakeholders are aware of institutional data needs
and sources. In any case, data sharing agreements between institutions need to
account for privacy and confidentiality issues (Graef et al., 2019).
The UN International Merchandise Trade Statistics (IMTS) compilation guide
identifies a number of criteria for effective institutional arrangements:
the designation of only one responsible agency
a clear definition of the rights and responsibilities of all agencies involved
the establishment of formalised working arrangements between agencies
including agreements on holding inter-agency working meetings, as needed, and
on the access to micro-data that those agencies collect.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 37
I EA. CC BY 4.0.
Formalisation of institutional arrangements in Canada
Natural Resources Canada (NRCan) is responsible for the production of detailed
energy end-use data across regions and sectors, based on aggregated energy use
data from Statistics Canada (StatCan), and data from other sources. NRCan finds
it useful to have formal agreements with other national counterparts to facilitate
data sharing and to establish the terms for disclosure of information.
A departmental memorandum of understanding between NRCan and StatCan was
first signed in 2013 and renewed in 2019, governing the collection, sharing and
disclosure of data, the confidentiality and use of the information, and access to the
information at the departmental level. This fosters trust and collaboration among
institutions and respondents to the surveys, as it ensures data security and that
confidentiality is protected throughout the process.
Further to this memorandum, additional letters of agreement are also used to
govern the implementation of data collection and sharing practices. For example,
there is an annual trilateral letter of agreement between NRCan, Environment and
Climate Change Canada and StatCan to establish the implementation details for
the sharing of three different data products: 1) the Report on Energy Supply and
Demand, which produces national and provincial energy balances; 2) the Annual
Survey of Industrial Consumption of Energy; and 3) the Survey of Secondary
Distributors of Refined Petroleum Products. The letter of agreement includes
aspects such as a detailed schedule, deliverables and payment obligations
between parties.
It is also practice to sign letters of agreement between NRCan and StatCan to
cover the details of survey implementation, such as the Survey of Household
Energy Use and the Survey of Commercial and Institutional Energy Use.
In addition, regular meetings are held at various levels, including working groups,
committees and senior management, to address specific data needs and issues,
as well as to discuss the implementation of the signed agreements.
Data collection plan
(Linked enabler: data collection strategy)
What is the most suitable methodology to collect the data needed in this case?
Is there any existing data collection process that can be used to gather the
information needed?
What is the timeline to collect the missing data?
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 38
I EA. CC BY 4.0.
When the data needed to develop indicators are not available, it is logical to
establish a plan to collect them. It can also be useful to plan for both the short and
the long term. From the different methods available (e.g. administrative sources,
surveys, modelling or metering), it is important to define which will be used to
collect each of the missing data series and when. This is a higher-level decision
before going into the detailed design of the data collection itself (e.g. survey
sampling), but it is essential to complete a plan and a timeline for the collection of
the missing data, in order to properly estimate resources for the longer term. In
the interim, while the data needed for the indicators are not available, it may also
be useful to define next-best or proxy indicators on a provisional basis.
Where it exists, adapting an existing survey may turn out to be less costly than
embarking on a new one if the information can be collected from a few additional
questions. In some cases, it may be that the appropriate data collection method is
determined by the requirements set out in the legislation (e.g. at EU level,
regulations on statistics to promote adequate data monitoring).
At this stage it is also important to consider the role of new and digital technologies
for the collection of disaggregated energy (and non-energy) data. As the diffusion
of smart meters and smart sensors becomes increasingly widespread, these may
make an important contribution to better characterising demand-side energy
patterns. The IEA has published a report entitled Energy End-Use Data Collection
Methodologies and the Emerging Role of Digital Technologies, available on the
IEA website.
Use of administrative data to estimate energy use in the Netherlands
In order to estimate energy consumption in the services sector with a high level of
resolution (and based on a bottom-up approach), Statistics Netherlands combines
traditional methods by compiling a large amount of administrative data and
registers, and then using new technologies (geographic information systems [GIS])
to make it visible “on the ground”. The data sources considered include: 1) the so-
called “client files” – registers of the public gas and electricity distribution
companies in the country; 2) the BAG (Basisregistratie Adressen en Gebouwen) –
the register of all buildings and addresses in the Netherlands; 3) the Dataland2 –
a national register that contains information on building types; 4) the National
Business Register, which includes information on all enterprises in the
Netherlands; 5) Locatus, a national register of services companies (by service
activity); and 6) district heating registers that contain the postal codes of district
heating use.
Linking the various data sources is not a straightforward task. For example, the
client files contain registers of all connections, but do not distinguish between
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 39
I EA. CC BY 4.0.
household and business connections. Linking the client files with the BAG allows
this distinction to be made. However, house identities are often registered in
different forms, leading to some inconsistencies. Similarly, identifying building
users requires matching the National Business Register with the client files.
Despite the challenges, the client files are considered a good source for energy
statistics, allowing data from various sources to be linked, and then plotted in a
spatial way using GIS. Client files also allow plausibility checks and visual
inspections to be made. The outcome is that more than 98% of natural gas and
electricity deliveries are allocated, serving as inputs to the Dutch Energy Balance.
Capacity building
(Linked enablers: staff capacity and stability and data collection strategy)
Do the staff have the capacity to collect the data?
Do the staff have the capacity to develop energy efficiency indicators?
Having qualified staff is of the utmost importance to the implementation of this
work at a national level. They need to fully understand both the national energy
data landscape and the underlying methodological aspects of efficiency indicators.
For this, the staff should benefit from ongoing capacity building programmes to
provide updates on important methodological changes and to compensate for staff
turnover.
This step is placed under the Planning stage of roadmap implementation, but in
reality it is ideally a continuous effort that could run all the way through the whole
cycle.
Do
Good practices and international experience
(Linked enablers: data collection strategy and multilateral collaboration)
How do other countries collect end-use data and develop efficiency indicators?
Can some practices be adapted to my country?
What worked well and what did not?
Whether at the stage of designing a new data collection process or reviewing and
improving an existing one, it may be useful to refer to other countries’ experiences
and practices. Learning from others’ experiences can be a valuable and efficient
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 40
I EA. CC BY 4.0.
way to avoid replicating mistakes that have already been made. Looking beyond
the data collection stage, this learning can also be applied to the whole value
chain, and for this reason the roadmap gathers real-world examples that can be
used as a reference and hopefully be of benefit to you. Furthermore, the IEA is
keen to facilitate knowledge exchange between willing countries.
International experiences in Costa Rica
Costa Rica has proven to be in the vanguard of national energy efficiency and
sustainable energy policy. It created a national commission for energy
conservation (CONACE) in 1993, and in 2012 it announced its intention to become
carbon neutral by 2021 (Source: Informe nacional de monitoreo de la eficiencia
energética de Costa Rica).
With regard to energy data, the country has been developing energy efficiency
indicators as part of the Energy Efficiency Indicators Database (BIEE project) from
the Economic Commission for Latin America and the Caribbean (ECLAC). One of
Costa Rica’s strengths is its vast experience in surveying across economic sectors,
although its end-use data need to be better disseminated to become more useful
and to raise their visibility.
Furthermore, Costa Rica has referred to other countries’ practices and
experiences when designing its own surveys. For example, for the industry survey
that took place in 2018 and 2019, the country undertook a review both of its
previous national industry surveys and other similar studies in the region and
beyond (e.g. in Argentina, Uruguay, Chile, Spain and Canada). This was done to
identify the key points for defining the survey sample. It is generally good practice
because it increases the relevance and quality of the data collected by benefiting
from previous or other experiences in the field.
Design methodology (data collection, storage and
processing)
(Linked enabler: data collection strategy)
What will data collection look like?
What is the targeted population (the sample size, etc.)?
What is the replication frequency and how easy is it to replicate?
After the higher-level data collection plan (administration, surveying, metering,
modelling etc.) has been established for each of the missing data series, it is time
to design a detailed methodology to fill the identified gaps. Starting with priority
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 41
I EA. CC BY 4.0.
indicators and corresponding data needs, it is important to define the target
population, the sample size and design including stratification, the questionnaire
if applicable, what elements are to be collected and the collection methods (e.g. in-
person, remotely, with or without incentives), and replication frequency. Once
progress has been made in higher-priority indicators, lower-priority indicators can
be tackled.
This is an opportune stage to oversee the whole process, including not only data
collection itself, but also the required infrastructure to store it and allow easy
retrieval of the information and its processing (also ensuring that data protection
is maintained). This is important because storing and processing may be closely
linked to the selected data collection method.
It is also worth mentioning that there may be opportunities to apply alternative data
collection techniques, which can be less resource-intensive (e.g. mobile crowd-
sourcing, or use of satellite data). Their use for energy statistics is not widely
established, but interest in them has been growing in various countries.
The Energy Conservation and Promotion Act – an opportunity for energy
data collection in Thailand
Under Thailand’s Energy Conservation and Promotion Act (ENCON Act), all
occupants of designated factories and commercial buildings are required to submit
an annual energy management report covering energy consumption, processes,
targets and conservation measures.
Besides this annual energy management report, occupants are then audited on
site by a team of accredited auditors. Both of these procedures constitute relevant
sources of energy consumption data that can be used for statistical purposes.
The Department of Alternative Energy and Efficiency is the entity responsible for
implementing the ENCON Act and gathering the energy management reports
submitted. Currently, these data are only collected for large energy consumers and
hence they are not representative of the whole sector (services and industry). In
the future, it would be beneficial to apply the act’s requirements to a wider group
of users (both buildings and industries). This would take advantage of an up and
running system for the collection of important data that can be used for statistical
purposes to track efficiency progress more generally; it would also promote larger
energy savings from efficiency at the national level.
The five-digit national classification system (TSIC) – based on the International
Standard Industrial Classification of All Economic Activities (ISIC) – has also been
applied to the energy data that can therefore be compared internationally (Source:
Wongsapai, W. [2017]).
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 42
I EA. CC BY 4.0.
Data collection roll-out
How long will data be collected for?
Is it feasible to implement in practice the methodology as designed?
This is the time for the actual roll-out and implementation of the data collection
methodology designed above. It can be a single collection of data, or continuous
(e.g. in the case of smart metering).
Surveys are reliable and necessary, but they are resource-intensive. It is worth
noting that data collection here refers not only to surveying, but also to the use of
modelling techniques to produce reliable estimates of energy consumption across
end uses. This is done in numerous countries, which rely on modelling in different
situations, for example to continuously produce their energy end-use data using
secondary activity data from official statistics or more aggregated energy data, or
to estimate energy consumption between survey years (which may have varying
frequency depending on the country, sector, etc.).
Application of models to derive end-use data in Brazil
In the case of Brazil, a significant proportion of the data that are used to develop
energy efficiency indicators is modelled by EPE, the Brazilian energy research
office. EPE has models for the residential sector (by end use), the industrial,
agricultural and services sectors, the transport sector (by mode, segment and
vehicle type) and for electricity demand.
In general, the demand-side models used at EPE are developed in-house, and so
are flexible enough to adapt to the data available from different sources throughout
the country. This approach also allows EPE to build assumptions based on expert
knowledge and tailor it to its needs. The methodologies for the residential and
electricity demand models are available online.
EPE has highlighted one particular survey – the Survey of Possession and Habits
of Consumption of Electrical Equipment in the Residential Sector – as an important
example of the synergies between different data collection methods, and in
particular between the use of surveys to complement modelling work. This has had
a positive impact by allowing the improvement of the demand-side models used
by EPE. This survey was conducted under the Procel Program, and two more are
planned – one for the commercial sector and another for the residential sector.
In addition, surveys conducted by sector associations are also used for
constructing energy efficiency indicators. Often surveys conducted without an
energy focus can nonetheless be extremely helpful for energy analysis.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 43
I EA. CC BY 4.0.
Data management
What tools are to be used to process and store the collected data?
What techniques are to be applied?
Are privacy and confidentiality issues accounted for?
After collection, data need to be properly processed (e.g. by aggregating or
anonymising), validated (e.g. by removing outliers) and stored in a suitable
platform allowing for easy access for different purposes.
This step becomes increasingly complex the greater the amounts of data
collected, as for example in the case of real-time data collected through digital
means. The FAIR
2
principles for data management have emerged as a widely
accepted toolbox for data management.
The energy data management system in Indonesia
In response to Indonesia’s energy conservation targets (e.g. reducing final energy
consumption by 17% by 2025), the country has developed POME (Pelaporan
Online Manajemen Energi), an online energy reporting system for industry,
managed by the Directorate General of New, Renewable Energy and Energy
Conservation (DGNREEC), part of the Ministry of Energy and Mineral Resources
(MEMR). Under Government Regulation 70/2009 on energy conservation, large
energy users (consuming more than 6 000 toe/year) are required to report their
energy consumption through POME. Currently, only manufacturing industries
meeting the energy threshold report their energy data.
MEMR is revising this regulation, and it is expected that the energy threshold level
for the industrial sector will be lowered from 6 000 toe/year to 4 000 toe/year.
Furthermore, with the promulgation of the new regulation, the buildings sector
(500 toe/year threshold) and transport sector (4 000 toe/year threshold) will also
be mandated to report their energy consumption to the government.
The data reported include: energy consumption by fuel type, equipment and
appliance data, power plant data, implemented energy efficiency measures,
energy savings achieved, and energy efficiency investment data. POME has
undergone a redesign process to improve its user-friendliness, and it now includes
a benchmarking feature that allows companies to compare their energy
performance with others, while it also allows DGNREEC to provide feedback and
recommendations to businesses, encouraging companies to implement energy
2
Findability, Accessibility, Interoperability, and Reuse of digital data.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 44
I EA. CC BY 4.0.
efficiency measures. Some of the collected information feeds into Indonesia’s
energy efficiency information website (SINERGI), among other data and
resources.
This type of online reporting system is expected to significantly advance the
understanding of energy use in the industrial context and to improve insight into
the current status in relation to established targets. Industries covered by this
reporting system account for about 70% of total industrial consumption. The
progressive lowering of the threshold and expansion to other sectors should be an
important step in improving the national characterisation of energy use patterns.
Check
Data validation
(Linked enablers: data collection strategy and multilateral collaboration)
Is the data good quality? (i.e. robust, representative, plausible)
What data should be analysed carefully?
Is metadata available?
After the collection and preprocessing of the data (part of the management step),
it is important to check for data quality in a more comprehensive way. This
includes, for example, assessing data representativeness (e.g. whether the
different strata are properly represented), robustness (e.g. the response rate),
coverage of the different elements collected, plausibility of the data and indicators
produced (e.g. by comparing with plausible ranges). This can be done through
quality control systems, both embedded in the data collection process itself and in
place in this later data validation stage.
Data quality assurance and protection in Australia
The Australian Energy Statistics (AES) is the Australian government’s official
source of energy statistics for Australia, including end-use data. A robust quality
assurance process is in place for the verification of data when compiling AES
estimates.
Plant-level data are used to confirm and explain sudden fluctuations in production
or consumption (this may, for instance, explain sudden jumps or falls from the
opening or closure of a plant or by misreporting in the source data). Data are also
validated by cross-checking with alternative data sources. AES estimates are
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 45
I EA. CC BY 4.0.
validated by revisiting the trends in national, state and industry-level economic
activity indicators (e.g. GDP, population) and data on passenger and freight
activities.
Data are also validated for each fuel by looking at discrepancies in the supply and
demand balance tables. Major inconsistencies are usually resolved in consultation
with the data source agencies (e.g. the Clean Energy Regulator). Where possible,
the data are compiled and presented using concepts and definitions intended to
align the AES with international frameworks.
Further to data validation, maintaining data privacy and confidentiality is also of
utmost importance. Statistics for release must ensure that the identification of an
individual person or organisation, either directly or indirectly, is not possible. This
requires the use of statistical methods that preclude identification, while allowing
sufficiently detailed information to make the data useful. Most commonly, this
involves removing or altering information, or collapsing detail.
For instance, if a cell in a published AES table were to contain data from only a
small number of companies (or from many companies but where only one or two
predominate), then it could be possible for a third party to deduce information about
the companies involved.
In order to mitigate against identification and disclosure risks, data concerning
some fuel types and industries in the AES tables are aggregated or withheld from
the published tables. Where confidentiality measures extend beyond these fuel
types and industries (e.g. where information could be deduced by subtracting other
published data from an aggregate), this is noted in the tables.
Needs for future adjustment
How did the data collection process go in practice?
What lessons can be learned and what can be improved for next time?
This step refers to the ex-post assessment of the data collection process,
addressing the resources spent and whether they have deviated from the initial
estimated budget, as well as the overall performance and efficacy of the
methodology used. It also looks at whether the response rate was high enough
and what could have been done from a strategic point of view to improve it. It
considers any lessons learned from the process for future replications.
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 46
I EA. CC BY 4.0.
Act-adjust
Data analysis
What messages do the indicators tell us?
Do the developed indicators address the initial goals and needs?
After the data have been collected and duly systematised, and the indicators
aimed for have been produced, it is time to analyse the patterns and trends found
in the data and the indicators. Fundamentally, this step aims to interpret the
messages from the indicators, which should be able to track and fully address the
initial defined goals.
Dissemination
Do the data and indicators reach a large number of users and different audiences?
Are data and indicators disseminated in a clear way and in an appropriate format?
Data are collected to serve a number of purposes, not for the sake of being
collected. As such, it is important to disseminate them into practical formats for
different users, and to convey the key messages found. Good and effective data
dissemination also allows for improvements in its quality through the queries and
feedback received by the data providers from the users.
Data use
Are users using the data for different purposes?
What are the data being used for?
What conclusions can be drawn?
Using the data for a number of purposes (e.g. energy planning, modelling,
policymaking) allows us to advance knowledge (e.g. regarding progress on
efficiency, the effectiveness of specific technologies or policies) and to meet the
needs and goals initially identified when it was decided to develop energy
efficiency indicators in the first place. At this stage, important conclusions are
drawn from users, such as:
Can efficiency improvements be associated with a specific policy?
Is this investment necessary if efficiency continues to progress at the same pace?
Specifically, regarding data for policymaking, it is important that data become
embedded in all stages of the policy cycle. Only evidence-based policies can be
effective, and we have witnessed in the past policies and national targets being
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 47
I EA. CC BY 4.0.
designed without a baseline or background information, and often falling short of
delivering the expected results.
Act on results
What changes/adjustments are needed based on data insights?
What else can be done with the new information available?
Ideally, the insights and conclusions drawn from the use of the data lead to
actions, for example adjusting a policy that is being tracked, or setting new (and
stricter) targets. This is necessary to guarantee that countries continue to achieve
savings from energy efficiency, to identify new priorities for action and to check if
emission reductions are enough to deliver national commitments.
In addition, besides policy adjustments there may also be the need to adjust the
indicators used, depending on whether they have met the initial goals and needs
and whether they have been able to capture the intended information.
As a result, the end of a cycle may lead to the beginning of a new one, with new
needs and new indicators to develop.
Data collection embedded into the policy cycle in the United Kingdom
The United Kingdom has been collecting end-use data for over 20 years, data that
are acknowledged as being important for monitoring national targets across
sectors. At present, the data are used to inform a range of climate change and
energy efficiency policies. The country has committed to reaching net zero
emissions by 2050. For this reason, energy consumption is monitored across
different sectors and end uses to identify what policies are needed to meet the
country’s long-term targets.
In particular, data collection for monitoring and evaluation are included in the
budgets of these policies. Despite this, there is a challenge in turning the data
collection exercises commissioned for individual policies into long-term
frameworks. This represents a real-world example of how data are embedded into
the policy cycle.
For example, an evaluation of the Climate Change Agreements (CCA) scheme is
being conducted to assess and help deliver an improvement of at least 20% in
business energy efficiency by 2030, laid out in the Government’s Clean Growth
Strategy. The CCA scheme is a voluntary agreement scheme that aims to mitigate
the effect of the Climate Change Levy on energy- and trade-intensive industry.
Firms in eligible sectors choose to participate under sector-specific “umbrella” CCA
Demand-side data and energy efficiency indicators 4. A roadmap for the development of energy efficiency indicators
A guide to designing a national roadmap
PAGE | 48
I EA. CC BY 4.0.
agreements. It offers discounts on the Climate Change Levy to firms meeting
targets for carbon or energy efficiency improvements.
The evaluation programme combines a number of methods (e.g. analysis of
emissions data, econometric analysis of the impact on energy consumption at the
macro level [2-digit ISIC code level], and a telephone and online survey). This
demonstrates not only the importance of detailed data availability for policy
monitoring and evaluation, but also how policy work can constitute an important
source of data that can be used for other purposes.
Demand-side data and energy efficiency indicators Additional remarks
A guide to designing a national roadmap
PAGE | 49
I EA. CC BY 4.0.
Additional remarks
As useful and necessary as energy efficiency indicators are for describing key
trends and patterns in energy use across the main final consumption sectors and
understanding the role of efficiency, it is important to keep them in perspective.
Despite being very detailed, and certainly the most detailed indicators in energy
statistics, they are average indicators. As a result, they do not provide insights into
more extreme patterns and, for instance, they are not able to describe variability
in energy use due to variables such as income level, gender or age.
In order to understand the impacts on more vulnerable populations, especially in
light of calls for so-called just or fair energy transitions, additional layers of detail
are needed. The end-use data and the efficiency indicators presented above
should be collected and developed with segmentation across each of these
dimensions (income, gender, age).
It is acknowledged that many countries struggle with the collection of the
sub-sectoral and end-use data mentioned earlier, and hence options for further
development represent “second-level” indicators that may be useful for
characterising other dimensions of energy efficiency policy, and for making sure
no one is left behind. As challenging as this may be in the real world, given existing
constraints at a national level, it is important to keep it in mind, as the opportunity
may emerge.
Demand-side data and energy efficiency indicators Conclusion
A guide to designing a national roadmap
PAGE | 50
I EA. CC BY 4.0.
Conclusion
The development of energy efficiency indicators is a necessary prerequisite to
track energy efficiency progress for different purposes (e.g. policy design and
monitoring, energy planning). Energy efficiency is increasingly on sustainability
and decarbonisation agendas worldwide, and several countries have developed
or are developing energy efficiency indicators at a national level.
This document aims to increase awareness of their importance and offer a guide
to support different stakeholders in initiating or continuing their development,
regardless of the stage the country may be at. It also offers a number of good
practice examples from countries globally, with real-world application of different
steps of the roadmap to illustrate how they can work in practice. Naturally there is
no single recipe and the success of each approach is largely determined by a
given national context.
This roadmap benefited from the invaluable contribution of national counterparts
during the consultation stage, who reviewed it, provided inputs and shared their
experiences. It is our wish that these contributors and many more may benefit
from it. The IEA is also keen to support and facilitate this process at a national
level.
For any questions or remarks, please contact energyindicators@iea.org.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 51
I EA. CC BY 4.0.
Surveys and best practices
Annex I: Country/economy survey on
roadmap
This annex reproduces the set of questions asked to each of the national
counterparts consulted. This questionnaire was sent in written format by email,
and later discussed during an interview. The interview also included a more
quantitative analysis (based on a Menti survey), as shown in Annex XIII.
Survey begins:
“The questionnaire below is framed under an IEA project that aims at developing
a roadmap that countries can adopt in the development of energy end-use data
and efficiency indicators (EEI) at national level. This work is thought of and
planned in a way that can benefit countries/territories in different development
stages of such indicators and with different needs or priorities (e.g. applicable to
different/several final consumption sectors).
The IEA wishes to make this a collective experience and to gather as many
insights as possible from our counterparts, in order to make this work applicable
and representative of different geographical contexts for the benefit of all. All
countries may need to start this cycle sometime in the future.
Please answer the questions below to the best of your knowledge and providing
as much information and detail as possible, describing the case for your country.
Views gathered may be incorporated in the final report. Please mark any
confidential information as such, so that it is not included. Or please indicate upon
returning the survey whether you would like to keep it anonymised.
Please feel free to provide any additional material or links that you may find
relevant.
Part I: targeted questions
Background
1. What energy end-use data and energy efficiency indicators have been developed
in your country? By whom? When?
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 52
I EA. CC BY 4.0.
Needs
2. What drove (may drive) the development of energy end-use data and energy
efficiency indicators in your country (e.g. new policy, international commitments –
which?)? What sectors are (may be) covered?
Legal framework
3. Is there a regulatory framework, enabling the collection of end-use data?
a. If so, in your opinion what is its importance? What is its timeframe?
i. Is the legal framework sector-specific?
b. If not, in your opinion, is it needed and what difference would it
make?
Responsibility
4. Is there a dedicated national institution in charge of EEI, or is this work split
among several organisations? What institutions are involved?
a. Does this model work well?
i. Does it depend on the sector considered?
b. What could be improved?
Institutional arrangements
5. How is the communication between institutions collecting relevant EEI data?
a. Are there any data sharing agreements? Are they sector-specific?
b. If so, in your opinion what is its importance?
c. If not, in your opinion, is it needed and what difference would it
make?
Resources
6. Is the annual budget for the EEI work somehow negotiated or imposed top-down?
a. Are the funds allocated enough in relation to the annual work to be
performed and objectives to be met? What about the long-term
planning?
b. What additional funding possibilities do you foresee?
c. Are human resources enough (how many people?) and able to
access adequate training (what skills?)?
International collaboration
7. Do you ever refer to other countries practices when planning a new data
collection? Is (would) that (be) useful?
a. What international support, if any, would be useful in this work?
Data collection
8. How many data surveys/data sources are used for your EEI data collection? One
per sector?
a. Could you share the surveys in place in your country?
b. How is the modelling developed (if any)?
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 53
I EA. CC BY 4.0.
Data quality
9. What processes are in place to check for data quality and validation?
a. To what extent are international statistics guidelines considered in
the data collection design?
Dissemination
10. How visible are energy statistics in your country, and specifically EEI?
a. How are EEI disseminated among different users (e.g. citizens,
policy makers, analysts...)?
b. What could be improved?
Part II: open questions
1. In your opinion, what do you think works well in the energy end-use
and efficiency indicators work/end-use data collection in your country?
What could be improved?
2. Do you think that the generic roadmap applies in your country – i.e. the
steps taken to develop energy efficiency indicators are similar? Are
there any elements that don’t apply (please specify)”
Survey ends.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 54
I EA. CC BY 4.0.
Annex II: Survey responses from Australia
Key facts:
National institutions involved: Department of Climate Change, Energy, the
Environment and Water (DCCEEW), and the Clean Energy Regulator (CER).
Legal framework for data collection: There is a framework for corporations
exceeding a certain threshold of emissions or energy use, and for petroleum
products reporting.
Data sharing and governance: Data sharing arrangements between agencies
are well established (e.g. DCCEEW and CER).
The Australian Energy Statistics (AES) is the Australian government’s official
source of energy statistics (including end-use data). The AES provides detailed
energy consumption, production and trade statistics and balances at state and
territory level for all fuel types and industries. The AES is updated annually by the
Department of Climate Change, Energy, the Environment and Water (DCCEEW).
The main data source for the AES is the National Greenhouse and Energy
Reporting Scheme (NGERS), which covers mostly industry and transport (the
latter at an aggregated level). The NGERS is a national framework for reporting
and disseminating company information about greenhouse gas emissions, energy
production and energy consumption. The NGERS is administered by the CER.
Other AES data sources include:
Australian Petroleum Statistics (APS)
Resources and Energy Quarterly (REQ)
Bureau of Infrastructure, Transport and Regional Economics (BITRE)
Australian Energy Market Operator (AEMO)
datasets and estimates from other Australian federal government and state
government agencies
internal AES estimates made using statistical techniques
public company reporting.
Other data sources for developing energy efficiency indicators include the
following:
Residential Baseline Study: prepared by DCCEEW, outlines the actual and
forecast energy use from appliances in the Australian and New Zealand residential
sector.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 55
I EA. CC BY 4.0.
Australian Housing Data Portal dashboards: developed by CSIRO to help all
stakeholders gain a greater understanding of Australia’s progress towards energy-
efficient, low-emission dwellings and suburbs.
Commercial Buildings Baseline Study: provides an outline of the actual and
forecast energy use of buildings in the Australian commercial sector.
Population and dwelling data are collected by the Australian Bureau of Statistics
(ABS) and published in the Australian Census.
Meteorological data are collected by the Bureau of Meteorology and published
online.
Industry value added data are collected by the ABS and published in the Australian
National Accounts.
Energy efficiency information for commercial office space is collected through the
Commercial Building Disclosure (CBD) Program.
Data, research and reports from across the energy sector are available from
Australia’s National Energy Analytics Research (NEAR) Program.
Disaggregated transport data are obtained from BITRE and are published in the
BITRE Yearbook.
AES data are used for analysing and tracking progress on energy- and emissions-
related policies and programmes, such as the National Energy Productivity Plan
(NEPP), National Greenhouse Gas Inventory reports and Australia’s emissions
projections reports. The AES provides a platform for modelling and tracking both
short-term and long-term trends in Australia’s energy production and use. Energy
data are essential for designing, implementing and tracking progress on policies
and programmes for Australia’s net zero emissions target.
Several legislative instruments provide the legal basis for the collection and
administration of the NGERS dataset (e.g. the National Greenhouse and Energy
Reporting Act 2007 [NGER Act]). Corporations that exceed a specified emissions
threshold must register under the framework and provide a report each year
(failure to comply leads to penalties). The thresholds are based on emissions,
production or consumption over a certain limit:
25 kt or more of greenhouse gases or 100 TJ of energy for facilities
50 kt or more of greenhouse gases or 200 TJ of energy for corporate groups.
For smaller energy users modelling is necessary, including the use of econometric
techniques as well as basic growth factors using available data.
For the residential sector, data collection is non-mandatory. The last residential
baseline survey was in 2015, and a new one is expected soon. Survey frequency
depends on funding availability and other priorities. The survey of road vehicles
has been discontinued.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 56
I EA. CC BY 4.0.
In addition to the NGER Act, the Australian government legislated to establish a
mandatory reporting programme for petroleum sector data. From 2018 onwards
this mandatory programme replaced the voluntary survey conducted to collect
monthly Australian petroleum data. DCCEEW is responsible for administering
mandatory reporting of petroleum sector data.
The Department of Industry, Science and Resources (DISR) is in charge of
publishing the Resources and Energy Quarterly report, which covers forecast and
historical statistics on energy commodity production and trade; DCCEEW is in
charge of administering programmes and legislation related to energy use and
energy efficiency, which also collect data (e.g. on appliances, equipment,
buildings and energy use). There is no additional funding or specific resources
allocated to energy efficiency indicators.
Several other Australian government agencies collect energy data according to
legislation and make data available either through data sharing agreements or in
publications, such as CER, or via the ABS. The CER collects energy data and
makes them available to DCCEEW through a memorandum of understanding.
These data are an important input when compiling: the AES, the national GHG
inventory, projections and reporting under the United Nations Framework
Convention on Climate Change (UNFCCC), Kyoto Protocol and Paris Agreement,
etc.
DCCEEW has formal oversight of NGERS and the NGER Act, and responsibility
for fulfilling Australia’s GHG inventory reporting obligations, tracking progress in
Australia’s international emission reduction commitments, and informing policy
making. One challenge is that all enquiries regarding data limitations or
inconsistencies must be made through the CER, which administers the dataset.
This can limit the timeliness and effectiveness of data quality assurance
processes.
Data sharing agreements are in place between DCCEEW and the CER and
communication is good between the two agencies. Regular discussions about
challenges, issues and experiences are held with the Australian Bureau of
Statistics. Where possible relevant data are also shared.
Maintaining the privacy or confidentiality of individual companies’ data sometimes
restricts the ability to publish data or share data publicly. The NGER Act details
confidentiality requirements for reporting information. In order to mitigate against
identification and disclosure risks, statistical methods are applied. These preclude
identification, while allowing sufficiently detailed information to make the statistics
useful. Most commonly, this involves removing or altering information, or
collapsing detail. Departmental officers are also bound by restrictions on the
access, use and publication of NGERS data under the NGER Act.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 57
I EA. CC BY 4.0.
A robust quality assurance process is in place for verification of data quality. For
instance, plant-level data are used to explain sudden fluctuations in consumption.
Data are also validated by cross-checking with alternative data sources. In-house
AES estimates are validated by revisiting the trends in national, state and industry-
level economic activity indicators (e.g. GDP, population). Major inconsistencies
are usually resolved in consultation with the data source agencies (e.g. the CER).
Long-term series of energy efficiency indicators are included in the AES
publication at the national Australia level; however, improvements could be made
in disseminating these data more widely.
One of the challenges facing the development of energy efficiency indicators is
the level of detail available from source agencies, as well as information
suppressed due to confidentiality. A number of sectors are becoming more
challenging to estimate and would require more estimation and modelling. Some
of the data sources used for modelling are not updated regularly. Investments are
being made in new data sources and techniques to better understand end-use
sectors. Australia’s National Energy Analytics Research (NEAR) programme aims
to create and integrate data sources and research to better understand and predict
energy use in Australia.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 58
I EA. CC BY 4.0.
Annex III: Survey responses from Brazil
Key facts:
National institutions involved: Brazilian Energy Research Office (EPE) and the
Ministry of Mines and Energy (MME).
Legal framework for data collection: There are no legally binding regulatory
frameworks for end-use data collection, but there is one for energy balances.
Data sharing and governance: No formal agreements, but communication runs
smoothly on an informal basis.
Energy efficiency indicator development in Brazil is overseen by two key
institutions: EPE and MME. EPE is in charge of tracking and reporting. It produces
the Atlas of Energy Efficiency, which includes the ODEX indicator, and also the
10-year energy plans, which provide perspectives on energy conservation and
demand looking 10 years ahead. EPE has the institutional role to implement and
publish the Brazilian Energy Balance, which contains the major statistics that feed
into the energy efficiency indicators (along with other sets of data).
MME oversees energy efficiency initiatives through steering committees such as
the Steering Committee on Levels and Indicators of Energy Efficiency (CGIEE)
3
and the Steering Committee on Energy Efficiency (CGEE), which approves the
budget of the National Programme of Electricity Conservation (Procel) and
evaluates its results. MME also administers minimum energy performance
standards for 10 categories of equipment and the labelling systems for a range of
equipment and buildings under the Brazilian Labelling Programme. Further to this,
Procel (promoted by Electrobrás since 1985) provides annual results on the
projects and measures implemented under the programme, in terms of saved
energy (kWh) and CO
2
-eq emissions avoided (tCO
2
-eq).
National policies for monitoring energy use and planning its effects have potentially
driven the need for the development of efficiency indicators in the country.
Nevertheless, there are no legally binding regulatory frameworks for end-use data
collection. This poses some challenges, for example, in the case of data on
appliances (such as sales) from manufacturers. Additional regulatory support would
3
CGIEE is formed by MME, the Ministry of Economy, the Ministry of Science and Technology, the Brazilian Electricity
Regulatory Agency (ANEEL), National Petroleum Agency (ANP), academia and members of society. This is specific to
MEPS.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 59
I EA. CC BY 4.0.
be welcome for the collection of a set of data that would allow the tracking of energy
efficiency progress for this growing energy end use, and others across sectors.
On the positive side, this model demonstrates high levels of engagement among
the responsible institutions, where communication occurs on an informal basis
(without formal agreements on data sharing) and using the general co-ordination
of MME to support the exchange of information. Conversely, this poses some
challenges because there is no specific budget for management issues relating to
energy efficiency at large, and specifically for the development of indicators, and
also due to the absence of a structured and integrated system to monitor the
results of energy efficiency initiatives and policies.
An institutional framework exists for collecting supply-side data for the energy
balances, based on energy sources and sectors. For the development of energy
efficiency indicators a large amount of data is modelled (see Box on data collection
roll-out), although an important input for improving the demand models is the
Survey of Possession and Habits of Consumption of Electrical Equipment in the
Residential Sector (PPH Residential). This survey was conducted under Procel,
and another two are planned – one for the commercial sector and a second one
for the residential sector.
Looking ahead, Brazil would be interested in learning good practices and
experiences from other countries or institutions regarding the development of
energy efficiency indicators. Also, the interaction with private enterprises and
industry associations for data collection could be improved. Brazil is developing
the Environmental Performance Evaluation System (SIDAC) based on embodied
energy and CO
2
-eq in building materials, potentially leading to the development of
new efficiency indicators.
As a way of interacting with users and disseminating data releases, the Atlas of
Energy Efficiency – Indicators Report is disseminated through social media
campaigns and webinars. Also, the results of energy efficiency programmes are
publicly disseminated on institutional websites and through events and webinars.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 60
I EA. CC BY 4.0.
Annex IV: Survey responses from Canada
Key facts:
National institutions involved: Natural Resources Canada (NRCan) Office of
Energy Efficiency (OEE), with key dependencies on Statistics Canada (StatCan)
and Environment and Climate Change Canada (ECCC).
Legal framework for data collection: Regulatory frameworks are in place for
statistics in general, and end-use data in particular.
Data sharing and governance: NRCan has a memorandum of understanding
with StatCan and other letters of agreement are in place.
The OEE at NRCan developed a system of energy efficiency indicators in Canada
in the early 1990s with strong data support from StatCan. In particular, Canada
has two components of energy use data – actual data collected by StatCan, and
detailed end-use data based on modelling by NRCan.
StatCan produces an annual Report on Energy Supply and Demand in Canada
(RESD), covering aggregated final energy use data for Canada by province,
energy source and economic sector – equivalent to Canada’s energy balance. The
RESD data are based on the numerous feeder surveys administrated under the
energy statistical programme in StatCan. The OEE at NRCan estimates energy
use by province, energy source, sector and end use. An end-use model has been
developed to disaggregate RESD data by end use. The purpose of this modelling
is to build historical energy use trends and to estimate energy efficiency
improvement. The model covers five sectors: residential, commercial and
institutional, industrial, transport, and agriculture. As an example, end uses for the
residential sector consist of space heating, space cooling, water heating,
appliances (major and minor), and lighting. The model development and
establishment have been subcontracted to an expert company, and NRCan is in
charge of its maintenance and operation.
NRCan also depends on data from other sources such as the GHG emission
factors, heating degree data and cooling degree data from ECCC, social and
economic data from StatCan, and other data from industry sources. As such,
NRCan estimates Canada’s GHG emissions associated with energy end use,
energy and GHG intensities, and energy efficiency improvement, all based on
NRCan’s energy end-use models.
Several triggers prompted the development of energy efficiency indicators in
Canada, for example: the Energy Efficiency Act and Regulation and the annual
report to Parliament (under the Energy Efficiency Act); evidence-based decision
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 61
I EA. CC BY 4.0.
making and revision of the Act, new regulations, and the development, monitoring
and evaluation of policy, programme and project; the establishment of the OEE;
monitoring and analysis of energy demand markets; and international reporting
commitments (e.g. IEA).
Canada has a regulatory framework for statistics (not sector-specific). It enables
the collection of statistical data in general (Canada’s Statistics Act)
4
, and energy
end-use data in particular (Energy Efficiency Act 1992 – under review). The latter
is the main policy tool for supporting energy efficiency programmes in Canada.
Under this act, NRCan is granted the authority to collect data on energy use and
the mandate to “provide energy use data to Canadians and to report to
Parliament”. The Minister of Natural Resources is also granted authority to collect
statistics and information from energy companies through the Energy Monitoring
Act and the Energy Supplies Emergency Act. The Canadian government is
reviewing the Energy Efficiency Act. Setting more specific sectoral indicators and
targets and monitoring progress are among the proposals under consideration to
help accelerate improvement and enhance Canada’s ability to achieve its 2030
and 2050 net zero goals.
This “centralised” model seems to work well. One of its strengths is the
communication between the different parties and data sharing. There is a
departmental memorandum of understanding between NRCan and StatCan
governing the sharing of data at the departmental level. There are regular data
sharing and working level meetings between the managers and analysts of the
two organisations, to address specific data needs and issues.
In addition, there is an annual trilateral letter of agreement between NRCan, ECCC
and StatCan to establish the implementation details of the RESD. Also, a trilateral
senior management level and working level committee is in place to oversee the
implementation. It is also the practice to have letters of agreement with StatCan
to cover the details of the implementation of surveys, such as the Survey of
Household Energy Use (SHEU), the Survey of Commercial and Institutional
Energy Use (SCIEU) and the Industrial Consumption of Energy (ICE).
Data quality, consistency and timeliness are among the areas that have space to
improve. Data quality and validation is checked by StatCan, NRCan and other
intensive data users, sometimes leading to revisions. A more formal, robust data
quality control system could be developed.
4
This mandates StatCan to “collect, compile, analyze, abstract, and publish information on the economic, social and
general conditions of the country and its citizens”.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 62
I EA. CC BY 4.0.
The energy statistical programme in StatCan is financed by StatCan, NRCan,
ECCC and others. NRCan provides partial financial support for the operation of
the RESD, the ICE survey, the SCIEU, the SHEU, and various ad hoc projects to
improve and/or expand Canada’s energy statistics. Funding within StatCan and
from NRCan are mainly on an annual basis. This affects long-term projects in
StatCan, such as the establishment of the Building Register. As energy efficiency
and GHG emissions become more visible and important, more funding from
energy efficiency programmes is expected to be allocated to efficiency indicators
work in the future.
Canada has a well-developed dissemination system of energy use and efficiency
data and information, tailored to different audiences. Tailored support is provided
directly for reports to Parliament, the development, analysis and monitoring of
regulation, policy and programmes, and data requests from the various levels of
government (e.g. the Canada Energy Regulator or ECCC). For analysts within and
outside NRCan, sector-specific one-, two- and four-page briefs are published and
provided as desktop references, highlighting key facts that are used frequently
(not for the public). For citizens, consulting companies, academia, students and
other stakeholders, energy use data, analysis and reports are made available on
the NRCan website.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 63
I EA. CC BY 4.0.
Annex V: Survey responses from Chile
Key facts:
National institutions involved: Ministry of Energy.
Legal framework for data collection: There are no regulatory frameworks in
place for end-use data collection. The ministry has been seeking to advance
intersectoral collaboration instead. Thanks to the Energy Efficiency Law (21.305),
the ministry will have the right policy framework to collect information from large
consumers and the public sector.
Data sharing and governance: There are no formal data sharing agreements in
place.
The monitoring of energy efficiency is carried out by the Ministry of Energy,
specifically the Renewable Energy and Energy Efficiency Programme, using
official information from different sectors. In Chile the indicator that is mainly
reviewed is an aggregated indicator (the intensity of final consumption per unit of
GDP), due to the fact that energy policy establishes a long-term goal for the
decoupling of energy consumption growth from GDP growth. In addition, this
indicator is used to compare the country with the average of OECD and
Non-OECD countries. The indicator is prepared annually by the Ministry of Energy
based on the national energy balance.
In addition, there has been work on more specific indicators by sector (for
example, intensity of consumption in the industrial and mining sectors, energy
consumption per equivalent vehicle in the transport sector, and energy
consumption per dwelling for the residential sector). These indicators have been
developed with the support of the “Base de Indicadores de Eficiencia Energética”
(BIEE) working group of the Economic Commission for Latin America (CEPAL). In
general, the country's energy statistics have good visibility, thanks to the “Open
Energy” platform, developed five years ago.
Despite the use of aggregated indicators, the Energy Efficiency Plan 2022-2026
was recently published, in the context of Chile’s first Energy Efficiency Law
(21.305), establishing different indicators to monitor the performance of the
different measures proposed.
Policy needs are acknowledged as a key driver for the development of efficiency
indicators. As mentioned above, Chile’s law requires an overall energy efficiency
indicator to set long-term energy policy goals. However, since the new efficiency
plan has been in place, the performance of a number of selected measures also
needs to be tracked.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 64
I EA. CC BY 4.0.
In the residential sector it has been possible to obtain good information with
household surveys (although with relatively reduced frequency). In the industrial
and mining sectors, two study attempts have been made, but the information
collected has not been enough to make a complete disaggregation. This is likely
to improve through the Energy Efficiency Law and the obligation that will be placed
on industries to report their consumption. The transport sector is the most
complex. Attempts are being made to move forward with modelling consumption
in the sector, using all available information.
The Ministry of Energy has been seeking, in the context of updating long-term
energy policy, to create a line of work related to information, its co-ordination and
interoperability between different public and private institutions. The goal is to
advance using an intersectoral collaborative approach, rather than via a specific
regulation established by the Energy Ministry. There may be room for
improvement, specifically in interacting more closely with other institutions to
obtain information, and thus be able to build more specific indicators.
At present, there are no formal collaboration agreements on efficiency indicators
between the ministry and other institutions. In general, the indicators are built with
public information, and therefore it has not been necessary to formalise
agreements. However, if there is the plan to improve existing indicators, new
agreements could be useful. For example, existing indicators for the mining sector
have demonstrated some issues. This is because the intensity of consumption
increases over time, for reasons unrelated to efficiency, such as deterioration of
mineral sources. In this sense, more detailed information on mineral processing
would be needed to be able to isolate the effect of exogenous variables that affect
energy consumption.
With regard to budget allocation, the development of indicators is done with
existing human resources, without a special budget for the topic. However,
sometimes a special budget is requested for the development of studies that
gather information for sector indicators. Examples include the review of final
consumption by end users in the residential and industrial sectors, and in the
transport sector to obtain a better disaggregation of consumption by type of
vehicle.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 65
I EA. CC BY 4.0.
Annex VI: Survey responses from Costa Rica
Key facts:
National institutions involved: Ministry of Environment and Energy, Secretariat
of Energy Planning (SEPSE).
Legal framework for data collection: There is a mandatory framework for large
consumers only.
Data sharing and governance: Recently formalised agreements with other state
institutions.
Costa Rica’s development of energy efficiency indicators started under the Project
of the Economic Commission for Latin America and the Caribbean (ECLAC). The
Ministry of Environment and Energy, specifically SEPSE, updated most of the
indicators between 2015 and 2020. However, they have not been disseminated
lately because responsibility moved from ECLAC to SEPSE, and the indicators
have not been fully updated.
In 1994, Law 7447 on the Regulation of the Rational Use of Energy was
established to calculate energy indices for large energy consumers,
i.e. companies with annual energy consumption greater than any one of the
following: 240 000 kWh of electricity, or 360 000 litres of petroleum products or a
total energy consumption equivalent to of 12 TJ. Because this focuses on large
consumers only, other consumers report data on a voluntary basis, making it
challenging to develop robust and complete indicators on energy efficiency across
sectors, especially in the sectors that are highly competitive (e.g. industrial and
commercial).
Currently, a series of policies focused on efficiency and decarbonisation of the
economy has created the need to establish indicators to monitor progress in
relation to their objectives, including energy efficiency indicators. A new regulatory
framework has also been in place since 2019 for the collection of statistics in
general (Law 9694 on the System of National Statistics). Because this is very
recent and also generic, guidelines for the energy sector are still in the process of
implementation.
Various surveys are conducted in different sectors: industrial, residential,
commerce and services, and transport. Additionally, studies are completed on the
availability and potential of national biomass. Unfortunately, these sectoral studies
are done on an irregular basis when funding is available. Currently, because
participation in these sectoral studies is voluntary, there has been resistance to
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 66
I EA. CC BY 4.0.
sharing information among respondents. The design of each survey is modelled
before it is used on the field, and depends on the sector to be surveyed. In
particular, SEPSE estimates consumption and tries to match it with sales data.
SEPSE also collects data on mileage and vehicle stocks.
The information needed for the development of energy efficiency indicators is
dispersed across multiple state entities. Historically data exchange has been
informal. Given the need to share information among institutions, the process of
creating agreements has begun so as to allow the sustainable transfer of data and
to establish responsibilities in the management of information. For example, an
agreement was signed with the national regulator (in charge of setting electricity
tariffs), given their bilateral interests in data collection. It allows the Ministry of
Environment and Energy to access information on permits. The reason for the
agreement is timing: the data are not classified, but contacting the regulator
instead of going directly to companies allows significant time to be saved.
There are no dedicated resources or allocated budget for work on energy
efficiency indicators. Occasionally, funds are available from decarbonisation
policies, but they are not specific to the energy sector and often go to the
environment/climate change office. The development of efficiency indicators is
currently the responsibility of SEPSE. However, there is no specific unit, normative
assignment or specialised personnel in charge of processing and generating these
indicators. More support from specialists (e.g. in statistics or economics) would be
helpful.
Although Costa Rica has referred in the past to experiences from other countries,
it is acknowledged that more exposure and exchange would be beneficial,
especially, from countries with similar conditions. It would be useful to know how
they have managed to identify the energy efficiency indicators that best meet their
needs and to overcome the challenges of data collection.
Energy statistics and some of the country's energy efficiency indicators are freely
accessible and partially published on the SEPSE website. In addition, information
on energy efficiency monitoring in Costa Rica is available from the ECLAC
publication Informe nacional de monitoreo de la eficiencia energética de Costa
Rica.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 67
I EA. CC BY 4.0.
Annex VII: Survey responses from Hong
Kong, China
Key facts:
Institutions involved: Energy Efficiency Office (EEO), the Hong Kong Special
Administrative Region (HKSAR) Government.
Legal framework for data collection: There are no legally binding regulatory
frameworks for end-use data collection.
Data sharing and governance: No formal agreements, but communication runs
smoothly on a voluntary basis.
Hong Kong Energy End-Use Data (HKEEUD) has been published over 20 years.
It is an annual publication that mainly provides territory-wide energy consumption
data by fuel type, sector and end use (e.g. cooling, cooking, lighting). The data are
collected and compiled by EEO, which is in the Electrical and Mechanical Services
Department of the HKSAR Government.
This annual publication not only provides energy end-use data, but also the key
energy efficiency indicator for Hong Kong, China. Energy intensity is a key
territory-wide energy efficiency indicator, with a target as set in policy. Last year,
new electricity saving targets were introduced for commercial and residential
buildings in “Hong Kong’s Climate Action Plan 2050”. Work is ongoing to explore
the establishment of a new energy data framework and mechanism for the
collection of energy data for these new targets on a per-building basis.
The objective of the publication of HKEEUD is to provide the public with an
understanding of energy consumption patterns and usage in Hong Kong (for
example, the largest energy end use in the residential sector in 2019 was cooking).
The data collected also serve as a reference for the government to formulate and
evaluate energy efficiency policies.
Energy end-use data are collected on a voluntary basis by conducting surveys
and as provided by third-party entities for administrative data, such as the Census
and Statistics Department (C&SD), on a collaborative basis. Although there are
no data sharing agreements with other institutions, this makes no significant
difference as institutions are collaborative and provide the requested energy data.
This is also due to the fact that typically respondents are themselves from public
entities (e.g. utilities or transport companies). However, a regulatory framework
for data collection would facilitate comprehensive data collection and shorten the
processing time.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 68
I EA. CC BY 4.0.
The energy consumption surveys are conducted based on economic sectors and
then further down to segment levels. On average, 10 surveys are covered in one
survey cycle, which covers four to five years in general. In every year, there are
surveys for different sectors or segments (each survey is considered as a project).
As for data quality control measures, sample checks are conducted in the field
and on the returned questionnaires in each survey.
The energy end-use database is updated annually with third-party activity data
and the micro-data from survey results. Overall energy consumption is compiled
using a scale-up approach and the compilation of energy consumption data is
further validated by comparison against third-party macro and historical data.
This data collection and compilation work is funded by government expenditure;
recurrent expenditure covers the costs (e.g. staff) of maintaining the database and
updating the corresponding energy efficiency indicator. Other than staff costs,
project-based expenditure is on a negotiable basis, such as energy surveys for
the compilation and update of the micro end-use data. The energy surveys are
outsourced, including the provision of survey and statistical expertise, and trained
manpower for delivering the surveys.
The energy end-use data (and energy intensity indicator) are published online with
free access and download capability for the public via the government website.
Published data are naturally aggregated in order to maintain data privacy. The
free access evidences the encouragement on data transparency by the HKSAR
Government. Further to this, Hong Kong, China has also been promoting
publication through social media.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 69
I EA. CC BY 4.0.
Annex VIII: Survey responses from Indonesia
Key facts:
National institutions involved: Ministry of Energy and Mineral Resources
(MEMR), Directorate of Energy Conservation (EBTKE), Centre for Data and
Information (Pusdatin); BPS (Statistics Indonesia).
Legal framework for data collection: There is a mandatory framework for large
industrial consumers only.
Data sharing and governance: Recently formalised agreements with other state
institutions.
Indonesia is in the process of developing energy efficiency indicators. At present,
aggregated energy data are collected by Pusdatin under MEMR. More
disaggregated energy data are collected by EBTKE, also under MEMR, often on
a project-by-project basis (such as for the buildings sector). EBTKE runs POME –
an online energy reporting system for industry. Activity data (and potentially some
energy data) are collected by the Indonesian statistical office, BPS. Data are still
scattered across different institutions and, particularly disaggregated energy data,
are collected on an irregular basis.
Energy efficiency indicators are important for tracking achievement of the national
energy efficiency targets, including under the country’s nationally determined
contributions. Indonesia's National Energy Policy aims to reduce final energy
consumption by 17% in 2025 and energy intensity by 1% per year during the time
period 2015-2025. It covers industry, transport and buildings (commercial and
residential).
Government Regulation 70/2009 on energy conservation requires large energy
users (more than 6 000 toe/year) to report their energy consumption to the
government via the online energy reporting system POME. Currently, only
manufacturing industries meeting the energy threshold report their energy data.
MEMR is revising the regulation in this regard, and it is expected that the energy
threshold level for the industrial sector will be lowered from 6 000 toe/year to
4 000 toe/year. Furthermore, with the promulgation of the new regulation, the
buildings sector (above 500 toe/year) and transport sector (above 4 000 toe/year)
will also be mandated to report their energy consumption to the government.
As energy efficiency indicators are used to track the progress of energy efficiency
policy implementation, EBTKE is in charge of developing the indicators in
collaboration with Pusdatin. Due to data limitations, they can currently only be
developed at an aggregated level. Pusdatin collects energy supply or sales data
from different institutions to develop the energy balance. BPS collects activity data
and energy data through end-use surveys. However, data collected by Pusdatin
and BPS could be further synchronised with a view to reducing the differences
between both sources. Examples of surveys conducted include the following:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 70
I EA. CC BY 4.0.
Buildings: EBTKE conducted a buildings energy consumption survey in 2019. BPS
conducts annual buildings surveys to collect activity data and energy data.
Industry: EBTKE has POME as an online reporting system to collect data from
industrial energy users consuming more than 6 000 toe/year. BPS conducts an
annual industry survey to collect energy consumption, production and value-
added data.
Residential: EBTKE, supported by CLASP, conducted residential and appliance
surveys in 2019. BPS also conducts residential surveys, but does not necessarily
focus on energy data collection.
Collaboration between institutions (EBTKE, Pusdatin and BPS) could potentially
be improved, given that there is limited communication between them to identify
data needs for energy efficiency indicator development. Furthermore, it is
hampered by the wide range of data that should be collected through surveys.
EBTKE usually uses data published by other institutions, e.g. Pusdatin and BPS.
Such collaboration could potentially be improved by EBTKE communicating its
data needs to Pusdatin and BPS, and vice versa.
MEMR (and hence EBTKE and Pusdatin) has a memorandum of understanding
with BPS to gather the activity data, including data required to develop energy
efficiency indicators. MEMR specifies its data requirements to BPS for data
collection. It is important to maintain continuous co-operation and co-ordination to
ensure that the data collected follows data needs for energy efficiency indicators
and other purposes. For example, discussing the questions in the questionnaire
before distribution would be useful. Similarly, due to limited coverage of the
transport sector, transport data collection could be initiated by a partnership
between MEMR and the Ministry of Transport.
With regard to resources, there is no or minimal budget available for data
collection. End-use data collection mostly relies on the support of energy efficiency
programmes such as those from CLASP, UNDP and other international
organisations. There is no other funding from the government budget. This
approach allows for the adoption of international good practices. For instance,
CLASP has hired international consultants to conduct surveys, bringing good
practices into the process.
At present no staff are assigned to the development of energy efficiency indicators
at EBTKE. Furthermore, most staff do not have the skills to develop them, and
hence additional capacity building would be required.
As for dissemination, different users can access energy statistics via the MEMR
website. Energy efficiency indicators are also available in the EBTKE publications
entitled Data and Information on Energy Conservation.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 71
I EA. CC BY 4.0.
Annex IX: Survey responses from Mexico
Key facts:
National institutions involved: National Commission for the Efficient Use of Energy
(Conuee), the Secretariat of Energy (SENER), the Energy Ministry and the National
Institute of Statistics and Geography (INEGI).
Legal framework for data collection: There is a legal framework specifically
mentioning energy efficiency indicators.
Data sharing and governance: No data sharing agreements are in place.
Conuee, as designated by SENER, has participated in the Energy Efficiency
Indicators Database (BIEE) project since 2013, developed by the Economic
Commission for Latin America and the Caribbean (ECLAC) of United Nations. In 2018
ECLAC published the National Report on Energy Efficiency for Mexico using the
information gathered and analysed by Conuee during 2013-2018 from public and
private entities in different sectors: Informe nacional de monitoreo de la eficiencia
energética de México, 2018.
From 2016 to 2019 Conuee collaborated with the French Development Agency, the
French Agency for Ecological Transition (Ademe) and Enerdata to improve the
information on Mexico for the BIEE project and develop an online public database to
evaluate and monitor national energy efficiency policies. This database was launched
in 2017 and is updated annually with information from different sources, but mainly
from the Energy Ministry and INEGI: Base de indicadores de eficiencia energética
(biee-conuee.net).
End-use energy efficiency indicators were covered in Article 18 of the Sustainable
Energy Use Law (LASE) and in its Regulation. In December of 2015 the LASE was
substituted by the Energy Transition Law (LTE) in which the energy efficiency
indicators (EEI) are mentioned in Article 29. The LTE regulation establishes that EEI
by sector should be part of the Energy Transition Information System (SITE).
Mexico’s energy efficiency indicators are used to evaluate and monitor the progress
of the Transition Strategy to Promote Cleaner Technologies and Fuels, but they are
also increasingly important for local governments taking climate action and for a better
understanding of their energy context and needs.
SENER elaborates and publishes the national energy balance, with sectoral data. In
order to disaggregate this further, methodologies and institutional arrangements at
national and sub-national level are needed to collaborate and gain access to activity
and energy data across sectors. Conuee is mandated by the LTE to publish energy
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 72
I EA. CC BY 4.0.
efficiency indicators; however, other institutions produce useful information for the
creation of efficiency indicators. Among the most important are INEGI and SENER,
but also relevant are the ministries of transport, economy, tourism, urban
development and agriculture. Likewise, other institutions within the energy sector,
such as IMP, CRE, CFE and PEMEX, have valuable information. Conuee develops
and updates different indicators across sectors (e.g. industrial, residential, transport,
services, agricultural) and the main macroeconomic indicators of the country. Much
of the information comes from official websites or annual reports. Communication
between institutions depends on the sector and considerations such as the need to
disaggregate information, confidentiality and the time that institutions take to respond.
Mexico has no special processes or agreements on energy efficiency indicators.
Conuee accesses the data through public websites or official information requests,
even with the Ministry of Energy. Co-operation agreements exist on different topics,
but not specifically for energy efficiency indicators. It would be easier and quicker to
obtain the necessary data if specific agreements on sharing information were in place,
or if there were interconnected systems by which data could be available when
institutions update their databases.
The budget for Conuee is annually allocated by the Ministry of Finance and approved
annually by Congress. The budget to develop, update and improve energy efficiency
indicators is not labelled as such, but is included in that of Conuee as a whole. The
allocation of the budget depends on an internal distribution authorised by the General
Director of Conuee. In recent years, support for the area that develops energy
efficiency indicators and carries out prospective studies has seen a decrease in
human resources and other resources, mostly due to central austerity policies.
The staff in charge of energy efficiency indicator work are also committed to other
tasks on energy efficiency programmes, institutional performance evaluation and
promotional activities. As knowledge around data science is advancing and the
amount of data to process is increasing, training on data analysis tools and modelling
programs would be is useful.
Conuee seeks to comply with the International Recommendations for Energy
Statistics (IRES) and to follow the IEA manuals, complemented by the Latin America
Energy Organisation (OLADE) resources on energy statistics. Conuee appreciates
the guidance and shared experiences of different countries and their approaches to
evaluating and improving energy efficiency data collection, and also the access to
different models and programs that can facilitate data updates and analysis.
As a result of shared experiences, Mexico – represented by the Policies and
Programmes Director of Conuee – has developed and integrated a methodological
approach to estimate cooling energy use, based on the variations in temperature and
energy consumption by state in Mexico: Informe nacional de monitoreo Energy
Ministry and de la eficiencia energética de México, 2018.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 73
I EA. CC BY 4.0.
Data for energy efficiency indicators mainly come from INEGI and SENER’s national
energy balance. In the case of INEGI the information used is GDP, employment, most
industrial production, household income and spending, some services (e.g. public
lighting) and agricultural sectors (inegi.org.mx).
5
The recently conducted household
survey, collecting data on energy use, activity and time of use, is known as ENCEVI
2018, developed between INEGI, SENER and Conuee. This was quite costly and it
is uncertain when it will be repeated. In total, the data for BIEE comes from more than
30 public and private data sources. Some of the information corresponds to annual
publications, but others, especially for industry and households, comes from official
requests.
Conuee developed two key models, one with French co-operation (AFD, Ademe and
Enerdata) in MedPro and another with Fundación Bariloche and European Union
co-operation in LEAP. MedPro was used to develop the scenarios of the updated
Transition Strategy to Promote Cleaner Technologies and Fuels in 2020: Conuee –
Forecast tool. The modelling with LEAP was used to develop the proposal for
instruments to facilitate energy efficiency measures in Mexico’s industrial sector, and
includes some of the data from MedPro, but only for the industrial sector.
6
Energy efficiency indicators have been public since 2017 via the BIEE tool Base de
indicadores de eficiencia energética. The Policies and Programmes Direction team
promotes the tool at every event, specifically with students and governmental entities,
via social media, mainly on Twitter (Análisis_Prospectiva @CProspectiva) and via
Conuee’s website, as in the monthly newsletter that is sent to more than 1 000
readers (Boletín digital Análisis y Prospectiva – BIEE).
Future improvements that have been considered include further awareness of BIEE-
Mexico, specifically among local government, where the rotation of public officials
makes communication more difficult. Perhaps more campaigns and messages about
the importance of energy efficiency information could help improve this.
Furthermore, given the scattered nature of data on energy efficiency indicators, the
SENER could organise an Energy Information System (SIE) so that public entities
could more easily share their information. The strengthening and training of local
teams working on energy statistics, including energy efficiency indicators, would also
be most useful.
5
On the INEGI site you can find data on the census, surveys and registers for different sectors.
6
The main document and the technical annexes are available at: https://www.gob.mx/conuee/acciones-y-
programas/propuesta-de-instrumentos-para-facilitar-medidas-de-eficiencia-energetica-en-el-sector-industrial-de-mexico.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 74
I EA. CC BY 4.0.
Annex X: Survey responses from Thailand
Key facts:
National institutions involved: Energy Policy and Planning Office (EPPO),
Department of Alternative Energy and Efficiency (DEDE).
Legal framework for data collection: There is a mandatory framework for large
facilities (buildings and industry).
Data sharing and governance: Informal data sharing.
In Thailand energy end-use data are available by energy source. The country’s
main energy efficiency indicators have been developed by EPPO in collaboration
with DEDE and related organisations. This has been done through shared and
diffuse responsibilities and cumulative work streams (i.e. efficiency indicators
alongside other topics/tasks). Specifically, EPPO is notably in charge of oil and
gas policies, while DEDE takes care of matters such as renewables and efficiency.
DEDE drafts the energy efficiency plan, based on government policy, and includes
both qualitative and quantitative measures. The most recent plan was issued in
2018 and there will be an upcoming plan in the next few years. EPPO collects the
data for its policy work, while DEDE’s needs are longer term.
The development of energy end-use data and energy efficiency indicators in
Thailand has been driven by international commitments, such as the Paris
Agreement, which covers many sectors including industry and transport, and is
aimed mainly at policy monitoring.
Recently the government has started to set up the National Energy Information
Centre (NEIC), which is a central entity to collect energy data. An energy data
management system is mandatory for large facilities (buildings and industries),
which requires, through the Energy Conservation and Promotion (ENCON) Act,
the appointment of an energy manager, and that energy and production data and
confirmation of certain efficiency measures are submitted to DEDE on a yearly
basis. If any of the following conditions are met, the reporting becomes mandatory:
1) total installed transformer capacity equal to or above 1.175 kVA; 2) total power
equal to or higher than 1 000 kW; 3) total energy consumption higher than
20 million MJ per year. This covers approximately 6 000 designated factories and
3 000 designated buildings. Below the threshold the act is not enforceable, and
hence for smaller companies energy data are collected through secondary
sources (e.g. electricity companies).
Additionally, there is a residential survey depending on funds available (ca. every
five to ten years), which is led by a consultant. EPPO is in charge of the energy
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 75
I EA. CC BY 4.0.
model used to set the Energy Master Plan. DEDE uses information from national
statistics, which includes energy spending by households.
There are no formal agreements between the two institutions because they are
under the same ministry. With external institutions (e.g. academia or private
entities), data sharing is in place through official channels, but there is no
regulation to enforce this.
Energy data are disseminated via the DEDE website, along with an annual energy
report (printed). Three publications are published: energy balances, an alternative
energy assessment, and energy efficiency in Thailand. DEDE also uses Facebook
to release some key information.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 76
I EA. CC BY 4.0.
Annex XI: Survey responses from the
United Kingdom
Key facts:
National institutions involved: Department for Business, Energy and Industrial
Strategy (BEIS).
Legal framework for data collection: There is a mandatory framework for energy
suppliers, and to some extent, consumers.
Data sharing and governance: Mostly reliant on published data. Data sharing
agreements are used for disclosive or proprietary data.
The United Kingdom regularly produces detailed energy balances, which include
final consuming sectors reported in the Digest of UK Energy Statistics (DUKES).
From these, and through modelling, BEIS also produces energy consumption
statistics with a more detailed sector breakdown, available in the consumption
tables of Energy Consumption in the UK (ECUK). Energy consumption is split into
end uses (e.g. space heating, water heating and cooking) as reported in the
end-use table of ECUK, and electricity consumption for appliances in the
residential sector in the electrical products tables of ECUK.
Some of these detailed data are available from 1999, such as data on industrial
energy consumption. The Department for Transport has responsibility for much of
the data collection around energy consumption in the transport sector. This
includes breaking down energy consumption into different modes of transport.
The national reporting of energy efficiency indicators with a focus on economic
activity (e.g. measured through gross value added [GVA], population, number of
households and kilometres travelled by vehicles, passengers and goods) is via
the intensity tables of ECUK.
Such data are used to inform a range of climate change and energy efficiency
policies. The United Kingdom has committed to reaching net zero emissions by
2050 and this creates the need to monitor energy consumption across different
sectors and end uses to understand what policies are needed to meet the long-
term targets.
BEIS has the legal power to compel the provision of energy data under Section 98
of the Electricity Act 1989 and Section 1 of the Statistics of Trade Act 1947. The
Electricity Act covers the generation, transmission and supply of electricity, and
the use of interconnectors and smart meter communication services; it does not
cover consumers of electricity. The Statistics of Trade Act covers all business
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 77
I EA. CC BY 4.0.
surveys including the Office for National Statistics (ONS) Annual Purchases
Survey, which asks how much is spent on energy products consumption. The
English Housing Survey collects energy data on the residential sector and is
voluntary (although a small number of energy questions included in the Census
are mandatory as set out in the Census Act 1920).
The Electricity Act 1989 in relation to statistics on trade in electricity makes it
mandatory for energy suppliers to report their electricity data, although it is
uncertain whether it is also compulsory for consumers (e.g. commercial and
industrial). Data are collected on a voluntary basis, the legal framework only being
enforced when strictly needed. The act provides BEIS with the legal basis for
collecting data from energy suppliers, for example to create the national energy
balances. Collecting data on energy consumption is the responsibility of BEIS, as
the UK department for energy. Other government bodies may also be involved
(e.g. Department for Transport, the Oil and Gas Authority) depending on the sector
being covered. As these surveys are for suppliers, sector attribution is determined
afterwards. Determining the sector in which business energy consumption should
be classed as is often not trivial, and may differ depending on the objectives of the
data collection exercise.
With regard to consumers, the Annual Purchases Survey requires a sample of UK
businesses to indicate how much they spend on different fuels, but not the actual
consumption (i.e. in currency not kWh). Some regulations (e.g. emissions trading,
climate change agreements) also require organisations to report fuel
consumption, but the scope is limited. Work is ongoing to incorporate these data
into BEIS end-use and sector consumption publications. There may be other
pieces of legislation that require reporting of consumption, but there is no general
legal requirement for consumers. Consequently, relevant surveys (e.g. the BEES
survey that is used to inform end use, see below) are non-mandatory.
Macroeconomic indicators of activity and demographics (e.g. GDP, GVA,
population) are compiled by the ONS. Some indicators require data from
administrations of the nations within the United Kingdom, (e.g. Scottish
Government, Welsh Government). Responsibilities are shared differently between
the UK government and these administrations due to constitutional arrangements.
This model works because all levels of government publish data by default.
Because UK government institutions tend to publish statistics, a large amount of
data can be accessed without resorting to data sharing agreements. Collating
energy efficiency indicators involves accessing publicly accessible data. BEIS
prefers to use published data, as disclosure control has already been applied and
the data used carry the “official statistics” badge. Additionally, data sharing
agreements can take a long time and significant resources to formulate.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 78
I EA. CC BY 4.0.
However, data sharing agreements can be very useful for disclosive or proprietary
data, for example where the energy efficiency indicators are policy specific, such
as domestic energy efficiency policies targeting specific types of households.
Each data sharing agreement relates to a dataset rather than being sector-specific
and the need for a data sharing agreement is determined by the sensitivity of the
data and whether or not it has been produced by government or a commercial
organisation.
With regard to resources, much of the work underpinning energy efficiency
indicators originates from mandatory reporting, although the national balances are
given high priority when spending decisions are made. Furthermore, BEIS has
funding to target policies. Data collection for the monitoring and evaluation of
energy efficiency policies is included in the specific policy budget, and these data
become official statistics. The challenge is turning these one-off data collection
exercises commissioned for individual policies into long-term frameworks. In any
case, this is a good example of how data are embedded into the policy cycle and
how policies can also support data collection work.
Some ad hoc surveys are undertaken from time to time, one example for the
United Kingdom being BEES (reporting on end-use consumption in the services
sector) undertaken in 2016 with a reference year of 2015. BEES is not a
continuous/regular data collection exercise.
Energy statistics are published on gov.uk alongside most other statistics produced
by government. They are available to the general public, and support is available
via an email inbox as needed. Most customers (from the general public to
analysts) obtain data through the published tables. There are plans to modernise
data dissemination to include tools that are now commonplace among analytical
teams, allowing data to be used more easily.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 79
I EA. CC BY 4.0.
Annex XII: Survey responses from the
United States
Key facts:
National institutions involved: Energy Information Administration (EIA).
Legal framework for data collection: Legal frameworks for data collection exist
under detailed sectoral surveys, although no reference is made to efficiency
indicators explicitly.
Data sharing and governance: No data sharing agreements exist as most of the
information collected for energy efficiency indicators is publicly available.
EIA publishes end-use energy efficiency indicators as part of its release for many
of its large statistical programmes, including its benchmark Commercial Building
Energy Consumption Survey (CBECS), Manufacturing Energy Consumption
Survey (MECS), Residential Energy Consumption Survey (RECS) and Monthly
Energy Review (MER). EIA also publishes a number of projected indicators in its
Annual Energy Outlook (AEO) and International Energy Outlook (IEO).
The primary indicators for manufacturing rely on GDP or GVA as the denominator,
but this can also be done by industry sector. Other measures for the buildings
sector use building counts, floor space or number of workers for the denominator.
Residential sector indicators use number of households, floor space and number
of household members for the denominator. Per-capita consumption measures
and data based on vehicle miles travelled are also published.
These indicators have been developed and expanded within each of the major
survey or analytical programmes organically, out of recognition of their importance
in supporting decision making in accordance with each individual programme
area. The US statistical system is decentralised. Thus, much of the non-energy
data used to calculate the indicators come from other organisations, such as the
US Bureau of Economic Analysis, the US Census Bureau and the US Department
of Transportation.
EIA is an independent policy-neutral statistical agency that has a threefold
mission: to educate the public, to support efficient markets, and to support decision
makers. The clarity of EIA’s mission and importance of its work may have provided
much of the impetus for the continual development of energy consumption and
efficiency statistics. Further, EIA’s mandate to collect benchmark consumption
data for the commercial, manufacturing and residential sectors goes back to the
establishment of the organisation.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 80
I EA. CC BY 4.0.
The collection of end-use consumption data has been written into law since EIA’s
conception in 1979. This law has only been modified twice. The first modification
was to acknowledge that traditional funding for the benchmark surveys only
supported their execution once every four years. The Bipartisan Infrastructure Law
passed last year generically asks EIA to investigate and try to provide more
frequent and timely data.
EIA was mandated to broadly conduct its three major benchmark surveys on a
periodic basis, although efficiency indicators are not explicitly mentioned. As the
independent statistical arm of the US Department of Energy (DOE), only EIA has
the function of producing energy efficiency indicators, although this is not
specifically mandated, unlike the consumption surveys. A number of US
government programmes depend on EIA data. For example, DOE’s office
promoting energy efficiency extensively uses these data and has supported
decomposition analyses of energy efficiency indicators.
EIA has a formal well-formulated method of sharing the consumption data with
other statistical agencies, federal agencies and national laboratories that make a
formal request. In addition, much of the data collected by EIA and other statistical
agencies to develop efficiency indicators are publicly available. EIA also has data
sharing agreements with other federal agencies to use administrative data to help
lower the costs of its surveys, consistent with the Principles and Practices for a
Federal Statistical Agency.
There is also a great federal push to further implement data sharing, both between
federal organisations and researchers, through the implementation of the
Evidence-Based Policy Act that is being led by the US Office of Management and
Budget. This act also reauthorises the strong confidentiality protections in the
Confidential Information Protection and Statistical Efficiency Act (CIPSEA) for
information collected for statistical purposes by federal agencies. Restricted
datasets collected under CIPSEA protections may be shared only for statistical
purposes, and their use may not disclose any individual or establishment that
responded to the survey.
EIA collects data for its CBECS and RECS program under CIPSEA protections
and provides public use micro-data files to the general public, which do not allow
users to identify which households or buildings responded to the survey. The US
Census Bureau is the collection agent for EIA’s MECS programme and collects
manufacturing data per the confidentiality requirements of Title 13 United States
Code, Section 9. One advantage of MECS is that it is based on the Business
Masterfile maintained by the US Census Bureau. This has helped save costs and
ensure the data are consistent with other economic data.
More regular consumption statistics are provided, but they are based on a variety
of different methodologies to interpolate, extrapolate or model results. Regardless,
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 81
I EA. CC BY 4.0.
all of these data are tied to the benchmark surveys. This is a common practice in
the US statistical system – for example, the US Census Bureau conducts its
benchmark Census of Manufacturers every five years, but uses a supplemental
annual survey for a much smaller subset of businesses and firms in the intervening
years.
EIA provides independent impartial information to support development of US
energy efficiency indicators. The development of these indicators is not a
specifically budgeted item, but is instead a component within EIA’s overall annual
appropriation. The US budget formulation process is complex, involving multiple
layers of negotiation and approval across the DOE (EIA’s parent agency), the
Office of Management and Budget and the US Congress.
The statistics are distributed through the public releases of many of EIA products,
but there is no consistent report or source to find all of these data. As no single
report has to date been published on energy efficiency trends in the US, EIA is
seeking to co-ordinate work on this front, for example by starting with the
development of a guidebook on indicator interpretation.
Efficiency indicators are often provided as part of other reports without much
context, which could lead to the drawing of erroneous conclusions. For example,
economy-wide GDP in the denominator can provide misleading conclusions if an
economy is shifting towards services and away from energy-intensive
manufacturing industries. Further, the number of homes in the denominator can
provide erroneous conclusions when home sizes are becoming much larger over
time and providing greater housing services.
Similarly, many annual efficiency indicators are affected by weather. Hedonically
adjusted and indexed numbers would be a benefit. Future work could involve data
harmonisation and making information on their applicability and appropriateness
easier to find for the more general community. It is important to better explore the
conceptual basis of the measures, their individual strengths and weaknesses, and
their relative appropriateness for certain applications.
EIA is keen to explore opportunities to learn from others. It is important to know
what other countries are doing because EIA could use their data in its own
international modelling work.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 82
I EA. CC BY 4.0.
Annex XIII: Results from the Menti survey
Of the 11 countries listed in the annexes above, one has only provided written
responses (without interview) and hence no Menti responses were collected for it,
and for another country the Menti was not run due to time constraints. The Menti
results shown below refer to the remaining nine countries in total.
What drove the development of energy efficiency indicators in your country (more
than one answer is possible)?
We can see from the figure below that most countries/territories identify national
policy design and tracking efficiency progress in general as the main drivers for the
development of energy efficiency indicators. Despite international reporting also
playing an important role, none of the respondents identified international policy
monitoring a key factor.
IEA. CC BY 4.0.
Is there a regulatory framework, enabling the collection of end-use data (Yes/No)?
IEA. CC BY 4.0.
0
1
2
3
4
5
6
7
National policy
design
National policy
monitoring
International
reporting
Tracking efficiency
progress in general
Other
International policy
monitoring
78%
22%
Yes No
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 83
I EA. CC BY 4.0.
Most countries do have some type of regulatory framework for statistical data
collection; most of the existing frameworks have specific provisions for energy, but
in most cases energy efficiency indicators or end-use data are not specified.
This may relate to the fact that energy efficiency is a more recent concern in political
agendas than other energy topics, such as access or security.
How important (0-10) is the existence of a regulatory framework enabling the
collection of end-use data?
IEA. CC BY 4.0.
Despite most countries considering the existence of a regulatory framework as
important, a minority does not think it is relevant because their system works well
on an informal basis.
Who is/could be in charge of energy end-use and efficiency indicators in your
country?
IEA. CC BY 4.0.
Despite the relatively even distribution of responsibilities among different types of
national institutions, energy ministries seem to be the most common entity in charge
of developing energy efficiency indicators at a national level. Statistical offices also
0
1
2
3
4
5
1 2 3 4 5 6 7 8 9 10
0
1
2
3
4
5
6
7
Statistical office Ministry Energy efficiency agency Other
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 84
I EA. CC BY 4.0.
play an important role either directly or indirectly, and certainly energy efficiency
agencies have also been responsible for energy efficiency indicator work in many
countries.
Please indicate any advantages or strengths of your model.
A word cloud has been generated with the 15 most frequently mentioned words.
Often recognised strengths are the experience of staff involved, the institutions (and
their engagement), and the existing data management and reporting systems.
How is the communication between institutions collecting relevant energy efficiency
indicator data? Are there any formal data sharing agreements (Yes/No)?
IEA. CC BY 4.0.
Despite a relative majority of countries having data sharing agreements in place, a
fair number do not.
56%
44%
Yes
No
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 85
I EA. CC BY 4.0.
If there are there any formal data sharing agreements, in your opinion what are their
importance (0 meaning no importance and 10 meaning very high importance)?
IEA. CC BY 4.0.
A large majority of countries attribute high importance to data sharing agreements.
Among those that do not have agreements in place, most seem to acknowledge
their importance and would appreciate having them in place. Still, a few cases do
not consider data sharing agreements as a pressing need, as they have been
managing to access data without problems either because they use published data
or because they have good informal relationships with other institutions (especially
where they are state-owned).
Do you ever refer to other countries' practices when planning new data collection?
IEA. CC BY 4.0.
Most countries stated that they sometimes look at other countries’ practices when
planning new data collection, although most of them acknowledged that this would
benefit from being further promoted.
Do you think that sharing experiences with other countries on the work done in this
area can be useful to your future work (Yes/No)?
All respondents answered ‘Yes’.
0
1
2
3
4
1 2
3 4 5 6 7 8 9 10
89%
11%
Sometimes Frequently
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 86
I EA. CC BY 4.0.
Annex XIV: Country assessment
With a view to employing the guide as an assessment tool, the charts and steps
presented above are shown in a more interactive format. They are designed to
prompt questions to potential roadmap users to assess where their respective
countries stand on the collection of end-use data and on the development of
energy efficiency indicators.
As mentioned above, this roadmap is meant equally for countries in early stages
of developing efficiency indicators and those with more established structures that
may want to develop a specific area or sector. As such, the following questions
draw from the chart below and aim to promote an initial reflection on end-use
energy data availability across sectors.
What sector(s) are a priority to develop new/ additional indicators in your country?
☐ Residential; ☐ Services; ☐ Industry; ☐ Transport; ☐ All; ☐ Not known
What sector(s) have better data availability in your country?
☐ Residential; ☐ Services; ☐ Industry; ☐ Transport; ☐ All; ☐ Not known
What are the main bottlenecks?
☐ End-use energy data; ☐ Activity data; ☐ A combination of both; ☐ None; ☐ Not
known
Please tick the boxes in the roadmap that, in your opinion, are established in your
country. Leave blank those that you think require further work. This will help
identifying key bottlenecks for future work.
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 87
I EA. CC BY 4.0.
Implementation steps of the roadmap for the development of energy efficiency
indicators (EEI) – assessment template with tick boxes
Plan
Needs arise
(Linked enabler: Political will and awareness)
This step is normally spontaneous because it happens when a certain indicator is
needed for a specific reason (e.g., to track energy efficiency in industrial
processes, or to verify if efficiency of household appliances improved after a new
label is in force) but is not available. If that is the case, the need for developing
Needs arise
□
Government
or high-level
support
□
Legal framework
□
Responsible
entities
□
Goal definition
and priorities
□
Capacity
Building
□
Data collection
plan
□
Institutional
arrangements
□
Mapping sources
and gaps
□
Resource
Allocation
□
Good practices
□
Design
methodology
□
Data collection
roll-out
□
Data
management
□
Data validation
□
Data use
□
Dissemination
□
Data
Analysis
□
Needs
for
adjustment
□
Act on
results
□
PLAN
DO CHECK
ACT
ADJUST
International
support
Legend
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 88
I EA. CC BY 4.0.
energy efficiency indicators has been identified (even if only for a specific sector,
or with a confined scope).
Does your country have a dedicated energy efficiency policy or strategy?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Energy efficiency data is collected, reported or monitored regularly?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Do policy makers refer to this data?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
How would you rank the overall need for new energy efficiency indicators in your
country?
☐ Low; ☐ Low-medium; ☐ Medium; ☐ Medium-High; ☐ High
Existing energy efficiency indicators needs
How would these indicators help develop and implement energy efficiency policy measures? What
would be possible if new/ more detailed indicators were available?
Add your notes:
Government or high-level support
(Linked enabler: Political will and awareness)
This step is to assess if the need and importance of energy efficiency indicators is
recognised by high-level decision makers or only at the working level.
Does the government/ministry recognise the value of end-use data/ energy
efficiency indicators?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Does the government/ministry endorse the collection/ development of end-use
data/ energy efficiency indicators?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Are there any plans to collect new data /develop new indicators or refine existing
ones?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 89
I EA. CC BY 4.0.
Government or high-level support
Who is driving the focus on the need for indicators (in step one) and whose support will be needed to
advance key efficiency indicators?
Add your notes:
Legal framework
(Linked enablers: Political will and awareness, trusted and empowered data
collection system)
This step serves to identify whether there is a relevant legal and regulatory
framework governing collection of end-use data (as this is often an important
enabler).
Is there a regulatory framework that enables the collection of end-use data across
sectors (either stand-alone or part of a broader one)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
If not, is it possible/relevant to create a new legal framework?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Is/are there clearly mandated institution(s) which is/are in charge?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probably; ☐ Yes
Legal framework
What are the main legal and regulatory levers governing collection of end-use data across sectors?
Are there barriers?
Add your notes:
Responsible entities
(Linked enablers: trusted and empowered data collection system and proper
resource allocation)
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 90
I EA. CC BY 4.0.
This step serves to understand if there is any institution in charge of collecting
indicators, and to identify whether any changes are needed.
Is there an existing national institution for (or that could take over) energy
efficiency indicators?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Yes
If not, is it possible to create a new institution in charge of efficiency indicators?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Do you know who/what institution is/would be in charge for the four main final
consumption sectors?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Responsible entities
What institution(s) is/are responsible for collecting energy efficiency indicators? Are there any
difficulties in this framework? What can be done to strengthen or clarify institutional responsibility or
coordination in this area?
Add your notes:
Goal definition and priorities
(Linked enablers: trusted and empowered data collection system and Proper
resource allocation)
This step serves to define the types of indicators needed (and their purposes) to
meet the needs that have been identified.
Are the objectives of the indicators developed/to be developed fully clear (e.g.,
monitor an existing policy, benchmarking, national/international reporting…)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are the priority indicators to address the existing needs identified?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Yes
Can these indicators be developed based on available data?
☐ No; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Yes
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 91
I EA. CC BY 4.0.
Goal definition and priorities
Are the priority indicators clearly identified? What are they?
Add your notes:
Resource allocation
(Linked enablers: proper resource allocation and staff capacity and stability)
This step serves to identify available resources and any new resource needs.
Are there specific resources allocated for data and efficiency indicators?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are these resources quantified and well known?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are there sufficient resources to develop efficiency indicators?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Can the activities to be covered be assessed with the resources available?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are there opportunities to raise the need for additional resources (e.g., to
management)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Resource allocation
Do the existing resources suffice (both in the short and long-term)? Does the collection of efficiency
indicators have a designated budget? Are there any challenges? Are there new funding
opportunities?
Add your notes:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 92
I EA. CC BY 4.0.
Mapping data sources and gaps
(Linked enablers: data collection strategy and multilateral collaboration)
This step serves to understand the availability of data sources and gaps to help
define areas requiring additional attention.
Is there an assessment of the data already available (mapping)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is there an identification of the data sources /institutions to contact?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is there an assessment of data gaps?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Mapping data sources and gaps
What are the main existing data sources, are they mapped? Can they be used to develop indicators?
What are the main data gaps?
Add your notes:
Institutional arrangements
(Linked enablers: data collection strategy and multilateral collaboration)
This step serves to understand institutional arrangements in place (if any), and to
identify opportunities for improved cooperation.
Are there other institutions already collecting data useful for efficiency indicators?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Are there any institutional arrangements in force (e.g., for data sharing)?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Is it possible to create/strengthen a process to simplify data sharing among
institutions (potentially with benefits to all parties)?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 93
I EA. CC BY 4.0.
Institutional arrangements
What institutional arrangements are in place? Are there any data sharing agreements established or
is it an informal collaboration? Which institutions are involved?
Add your notes
Data collection plan
(Linked enabler: data collection strategy)
This step seeks to identify next steps for data collection, in particular assessing
the existence of a data collection plan and identifying other steps to develop
priority indicators.
Are the most suitable data collection methodologies (e.g., survey, administrative
data, modelling, metering, etc) identified?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is it possible to use an existing data collection process to gather the information
needed?
☐ Impossible; ☐ Unlikely; ☐ Maybe; ☐ Probable; ☐ Possible
Is the timeline to collect missing data defined?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Data collection plan
After having identified the priority indicators, what is the most appropriate way to collect the data to
develop them? Why were these methods selected, considering the specificities of your country?
Add your notes:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 94
I EA. CC BY 4.0.
Capacity building
(Linked enablers: staff capacity and stability and data collection strategy)
This step focuses on understanding the knowledge and skills available to collect
end-use data and develop energy efficiency indicators within responsible
institutions.
What is staff’s capacity (in terms of skills/ expertise) to collect the data?
☐ Low; ☐ Low-medium; ☐ Medium; ☐ Medium-High; ☐ High
What is staff’s capacity (in terms of expertise) to develop energy efficiency
indicators?
☐ Low; ☐ Low-medium; ☐ Medium; ☐ Medium-High; ☐ High
How would you define the staff turnover in your institution?
☐ Low; ☐ Low-medium; ☐ Medium; ☐ Medium-High; ☐ High
Capacity building
How skilled are staff in charge of developing energy efficiency indicators and collecting the data
needed? How is knowledge management and transfer insured within responsible institutions?
Add your notes:
Do
Good practices /international experience
(Linked enablers: data collection strategy and multilateral collaboration)
This step identifies opportunities to build on international experience.
Do you ever look for good practices from other countries on how to collect end-use
data and develop efficiency indicators?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Can some of these practices be adapted to your country?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 95
I EA. CC BY 4.0.
Good practices /international experience
Where would you benefit from examples from other places (if at all)? Is this current practice while
collecting new data /developing new indicators?
Add your notes:
Design methodology (data collection, storage, and processing
(Linked enabler: data collection strategy)
This step focuses on the definition of a methodology for new data and indicators
to ensure their consistent collection.
Are there different methodologies to choose from? In other words, are different
methodologies used in combination (survey, use of existing data collected in other
domains etc., modelling, big data)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is it frequent to perform estimations in the absence of more accurate data?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
How frequent is the data collection replication?
☐Low frequency; ☐Low-medium; ☐Medium; ☐Medium-High; ☐High frequency
Design methodology (data collection, storage, and processing)
What will the data collection methodology look like? What is the population targeted (the sample
size, etc.)? What is the replication frequency and how easy is to replicate?
Add your notes:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 96
I EA. CC BY 4.0.
Data collection roll-out
This step refers to the actual implementation of the data collection plan, and
considers potential difficulties that may emerge ‘on the ground’.
In practice, is it feasible to implement the methodology as designed?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
How often is the data collection plan reviewed?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Data collection roll-out
Does the data collection plan develop as planned? What type of difficulties were faced? What
alternatives were found?
Add your notes:
Data management
This step assesses whether there is adequate infrastructure in place to deal with
the data collected.
Do tools to process and store data collected adapt to data collection method?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Can the data be retrieved easily?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are privacy and confidentiality issues accounted for?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Data management
What is your IT data infrastructure and data governance? Would alternative software potentiate
the conclusions drawn from the data collected? How are privacy and confidentiality issues
protected?
Add your notes:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 97
I EA. CC BY 4.0.
Check
Data validation
This step checks if there are established data validation processes, and how it
translates into data quality improvements.
(Linked enablers: data collection strategy and multilateral collaboration)
Is there a data validation and quality check process?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is the data quality good (e.g., robust, representative, plausible)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is metadata available?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Data validation
What data validation procedures exist both for the data collected and for efficiency indicators?
How do they contribute to improving data quality?
Add your notes:
Needs for adjustment
This step is about reviewing the whole pathway and understanding if there are
potential improvements to be made in the future.
How did the data collection process go in practice?
☐ Very poor; ☐ Poor; ☐ Fair; ☐ Well; ☐ Excellent
Are there lessons learned (and documented) on potential improvements for next
time?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 98
I EA. CC BY 4.0.
Needs for adjustment
How was your experience with the data collection process? What would you do differently and
why?
Add your notes:
Act, adjust
Data analysis
This step refers to the analysis of the data collected in order to draw insights and
conclusions. It helps understand whether it meets the goals as originally defined.
This analysis refers to an internal analysis performed within the responsible bodies
(before dissemination).
Are there valuable insights from the indicators developed?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Do the developed indicators address the initial goals and needs?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Act, adjust
Is the data collected fit for purpose? What additional information was derived? Did it allow
drawing important conclusions?
Add your notes:
Dissemination
This step refers to the release of the data and information collected/indicators
developed to either specific target audiences and/or the wider public, through
different dissemination channels (e.g., publications, databases, online pieces,
social media, etc.)
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 99
I EA. CC BY 4.0.
Do data and indicators reach a wide number of users and different audiences?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are data and indicators disseminated in a clear way and in an appropriate format
(e.g., a public online database)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is there a report featuring the results of your data collection?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Dissemination
How are end-use data/ efficiency indicators disseminated in your country? Is it publicly available?
What types of audiences is it reaching?
Add your notes:
Data use
This step refers to the use of the data after it has been disseminated. It can refer
to data use for policy making or monitoring, to benchmarking analysis, energy
planning, national or international reporting, etc.
Are users using the data for different purposes?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Is there a possibility for users to give feedback on the data?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Were the indicators used in any policy recommendations/regulations or to
benchmark with other countries?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Data use
For what purposes are the end-use data collected/ indicators developed used for? Is there the
possibility to collect feedback on the data collected to enable improving its quality over time?
How is this done?
Add your notes:
Demand-side data and energy efficiency indicators Surveys and best practices
A guide to designing a national roadmap
PAGE | 100
I EA. CC BY 4.0.
Act on results
This last step refers to the overall reason why data has been collected /indicators
developed in the first place. The data collected is expected to drive action towards
change and inform policies.
Is the information produced by the new indicators going to be applied (e.g., policy
design, projections and scenario development, etc….)?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Are there any changes/adjustments needed based on data insights?
☐ Never; ☐ Occasionally; ☐ Often; ☐ Regularly; ☐ Always
Act on results
What actions can be taken based on the findings obtained from the data collected? Will policies
be reinforced, or adapted? Is there further investment on energy efficiency needed to meet
national targets or cope with infrastructure constraints?
Add your notes:
International Energy Agency (IEA).
This work reflects the views of the IEA Secretariat but does not
necessarily reflect those of the IEA’s individual Member countries or of
any particular funder or collaborator. The work does not constitute
professional advice on any specific issue or situation. The IEA makes no
representation or warranty, express or implied, in respect of the work’s
contents (including its completeness or accuracy) and shall not be
responsible for any use of, or reliance on, the work.
For further information, please contact: energyindicators@iea.org.
Subject to the IEA’s Notice for CC-licenced Content, this work
is licenced under a Creative Commons Attribution 4.0
International Licence.
This document and any map included herein are without prejudice to the
status of or sovereignty over any territory, to the delimitation of
international frontiers and boundaries and to the name of any territory,
city or area.
Unless otherwise indicated, all material presented in figures and tables is
derived from IEA data and analysis.
IEA Publications
International Energy Agency
Website: www.iea.org
Contact information: www.iea.org/contact
Typeset in France by IEA - February 2023
Cover design: IEA
Photo credits: © Shutterstock
打开行研社App查看所有内容
Copyright © 2020-2022 妙无网络 沪ICP备2021003606号

沪公网安备 31011202013362号
  • APP下载 Android&iOS
  • 微信公众号 扫码关注
  • 微信客服 扫码联系客服