Energy Statistics Compilers Manual - Unstats.un
ST/ESA/STAT/SER.F/118 Department of Economic and Social Affairs Statistics Division Statistical Papers Series F No. 118 Energy Statistics Compilers Manual [Final draft subject to official editing] Ver170323 United Nations. New York, 2016
Department of Economic and Social Affairs The Department of Economic and Social Affairs of the United Nations Secretariat is a vital interface between global policies in the economic, social and environmental spheres and national action. The Department works in three main interlinked areas: (i) it compiles, generates and analyses a wide range of economic, social and environmental data and information on which States Members of the United Nations draw to review common problems and to take stock of policy options; (ii) it facilitates the negotiations of Member States in many intergovernmental bodies on joint courses of action to address ongoing or emerging global challenges; and (iii) it advises interested Governments on the ways and means of translating policy frameworks developed in United Nations conferences and summits into programmes at the country level and, through technical assistance, helps build national capacities. Note The designations used and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area, or of its authorities, or concerning the delimitation of its frontiers or boundaries. The term “country” as used in this publication also refers, as appropriate, to territories or areas. Symbols of United Nations documents are composed of capital letters combined with figures. Mention of such a symbol indicates a reference to a United Nations document. ST/ESA/STAT/SER.F/119 UNITED NATIONS PUBLICATION Sales No. E.17.XVII.10 ISBN: 978-92-1-161621-7 eISBN: 978-92-1-060140-5 Copyright United Nations, 2016 All rights reserved
Preface The Energy Statistics Compilers Manual (ESCM) is a publication that complements in a practical manner the International Recommendations for Energy Statistics (IRES), which provides a comprehensive methodological framework for the collection, compilation and dissemination of energy statistics in all countries irrespective of the level of development of their statistical system. In particular, IRES provides a set of internationally agreed recommendations covering all aspects of the statistical production process, from the institutional and legal framework, basic concepts, definitions and classifications to data sources, data compilation strategies, energy balances, data quality issues and statistical dissemination. IRES and the ESCM were prepared in response to the request of the United Nations Statistical Commission, at its thirty-seventh session (7-10 March 2006), to review the United Nations manuals on energy statistics, develop energy statistics as part of official statistics, harmonize energy definitions and compilation methodologies and develop international standards in energy statistics. The preparation of IRES and ESCM was carried out by the United Nations Statistics Division (UNSD) in close cooperation with the Oslo Group on Energy Statistics and the Intersecretariat Working Group on Energy Statistics (InterEnerStat). The ESCM is written primarily for practitioners that are tasked with building up or improving the energy statistics programme of a country or institution in a way that is consistent with the latest international standards and which produces reliable and internationally comparable data. The ESCM aims to assist countries in the collection, analysis and dissemination of energy statistics according to international standards. It provides explanations that make it easier to apply the principles defined in IRES in practical applications, to understand specific relationships that facilitate or complicate the adaptation of such principles to national situations and therefore provide practical ways to implement an energy statistics programme that is consistent with the established international recommendations. The ESCM builds heavily on examples of country practices to illustrate various ways to implement the recommendations set out in IRES, and thus to provide users with a variety of suggestions for tackling issues arising during the implementation of IRES. Additional country examples (including some that were too big to be included in this publication) are made available on the UNSD Energy Statistics website at http://unstats.un.org/unsd/energy/escm/country examples.htm. iii
Acknowledgements This manual has been prepared by the United Nations Statistics Division (UNSD) in close collaboration with the Oslo Group on Energy Statistics. In particular, as chair of the Group from 2009 until 2015, Statistics Canada was instrumental in developing a work plan and following through on improving earlier drafts. UNSD took the lead in the final phase of editing of the manual. Chapter 2 was drafted by INEGI, Mexico. Chapter 3 was drafted by UNSD. Chapters 4 and 5 were initially drafted by Statistics Austria and then elaborated upon by UNSD (earlier versions had combined the chapters). Chapter 6 was drafted by Statistics Norway, and elaborated upon by the IEA and UNSD. Chapter 7 was drafted by Statistics Canada. Chapter 8 was drafted by Statistics South Africa. As many chapters were drafted by individuals in countries and/or international organisations, it is somewhat inevitable that even after editing, each chapter will retain its own distinctiveness and style. In addition, countries which provided examples of their own practices, both to this print version and to the online collection of country practices, are thanked in particular. iv
Table of Contents Preface . iii Acknowledgements. iv List of Abbreviations and Acronyms . xi Chapter 1: Introduction . 1 A. Background. 1 B. The International Recommendations for Energy Statistics . 1 C. Organisation of the ESCM . 2 Chapter 2: Legal Framework and Institutional Arrangements . 6 A. Introduction. 6 B. Legal Framework . 6 C. Institutional Arrangements . 11 D. Fundamental Principles of Official Statistics . 14 E. Conclusion . 15 Chapter 3: Classifications . 16 A. Introduction. 16 B. Classifications of statistical units in energy statistics . 16 1. Energy industries . 18 2. Other energy producers . 20 3. Electricity and Heat . 22 4. Energy consumers . 23 C. Classification of energy products . 29 D. Classification of mineral and energy resources. 35 Annex 3A: Standard International Energy Product Classification (SIEC) . 39 Chapter 4: The Generic Statistical Business Process Model. 45 A. Introduction. 45 B. The Generic Statistical Business Process Model . 45 1. Specify Needs Phase . 46 2. Design Phase . 47 3. Build Phase . 49 4. Collect phase . 51 v
5. Process phase . 52 6. Analyse phase . 53 7. Disseminate phase . 53 8. Evaluate phase . 54 Chapter 5: Data Sources and Data Collection . 59 A. Introduction. 59 B. Data sources and data collection . 59 1. Administrative data sources . 63 2. Surveys . 69 3. Modelling. 78 4. In situ measurement . 84 5. Country cases - multi purpose approaches . 85 Chapter 6: Commodity and Energy Balances . 88 A. Introduction and purpose . 88 1. Introduction. 88 2. Importance of energy balances . 89 B. General information pertinent to both commodity balances and energy balances. 90 1. Scope of commodity balances and energy balances. 90 2. Level of detail . 91 3. Frequency of balances. 92 C. How to compile commodity balances . 92 1. Introduction. 92 2. Energy supply . 94 3. Transfers, transformation, energy industries own use and losses . 96 4. Final consumption . 99 5. Statistical difference . 100 6. Possible elements for reconciliation . 101 7. Country examples. 102 D. Compilation of energy balances . 105 1. Level of Detail . 106 2. Calculating an energy balance . 107 3. Calorific values. 108 4. Choice of the primary energy form . 109 vi
5. Calculation of the primary energy equivalent . 110 6. Physical energy content method and the partial substitution method . 111 7. Hydro pumped storage plants, Backflows to refineries, and Oil used as feedstock and blendstock in refineries . 112 8. How to calculate the renewables column . 114 9. Examples of an energy balance . 117 10. Checking the energy balance . 122 11. Presentational issues in commodity balances and energy balances . 124 12. New technologies . 125 E. Country-specific examples . 127 Chapter 7: Quality Assurance Frameworks and Metadata . 132 A. Introduction. 132 B. Data quality, quality assurance and quality assurance frameworks . 132 1. Data quality . 132 2. Quality assurance . 133 3. Quality assurance frameworks . 133 C. Dimensions of quality . 139 D. Measuring and reporting on the quality of statistical outputs . 143 1. Quality measures and indicators . 143 2. Quality reporting . 146 E. Quality reviews . 150 F. Data quality and validation checks for international energy statistics at the IEA. 151 G. Country Practices – Quality in Energy Statistics Programmes . 153 1. Country feedback about experience assuring output quality . 153 2. Country experience in a decentralized statistical system . 154 H. Metadata on energy statistics . 156 Chapter 8: Data Dissemination . 161 A. Introduction. 161 B. Reference period . 161 C. Dissemination schedule. 162 D. Confidentiality . 162 E. Revision Policy . 166 F. Dissemination format and access. 167 vii
G. Meeting User Needs . 170 H. Energy Indicators as a Dissemination Tool . 173 Boxes Box 3.1: Energy, Water and Environment Survey in Australia. 17 Box 3.2: Energy use in manufacturing survey in Finland . 25 Box 3.3: Industrial Consumption of Energy Survey in Canada . 26 Box 3.4: Choice of the statistical unit in the survey for energy consumption by industry in Denmark . 27 Box 3.5: Statistical unit used for end use survey in Ghana . 27 Box 3.6: Philippine Standard Commodity Classification (PSCC 2015). 32 Box 3.7: Energy product classification in Azerbaijan . 34 Box 4.1: Implementation of GSBPM for energy statistics in Azerbaijan . 55 Box 5.1: 15 /18 approach used by Eurostat . 81 Box 5.2: IEA/ESTIF methodology for estimating solar heat production . 82 Box 6.1: Examples of monthly/quarterly commodity balances . 92 Box 6.2: Norway’s check on statistical differences . 100 Box 6.3: Adapting to IRES . 111 Box 6.4: Transformation gains in Norway . 122 Box 7.1: Country Example - Quality Report on Annual Energy Statistics in Slovenia . 147 Box 7.2: Selected suggested content to be covered in ESS Quality Reports . 149 Box 7.3: Examples of Data Quality/Validation Checks from the IEA. 151 Box 7.4: Examples of Country Practices for Assuring Quality in Energy Statistics: Quality Dimensions . 153 Box 7.5: Example of Data Quality in a Decentralized System . 155 Box 7.6: Metadata Items for Statistical Releases (from the Single Integrated Metadata Structure) 157 Box 7.7: Country Examples of Metadata on Energy Statistics . 159 Box 7.8: Metadata Resources and Guidelines . 160 Box 8.1: Privacy practices at Statistics Canada . 165 Box 8.2: General EIA Weekly Natural Gas Storage Report Revisions Policy . 167 Box 8.3: Energy statistics online databases in France . 168 Box 8.4: Energy statistics metadata on Bulgaria’s NSO website. 169 Box 8.5: Preliminary energy statistics: the case of Norway . 170 viii
Box 8.6: Statistics South Africa’s experience with Social Media. 171 Box 8.7: Statistics South Africa’s Dissemination Programme . 171 Box 8.8: United Kingdom’s Department of Energy and Climate Change User Survey . 172 Figures Figure 4.1: The Generic Statistical Business Process Model . 46 Figure 5.1: Sources of energy used for cooking in rural and urban areas in India, 2009-2010 . 72 Figure 6.1: Flows in the commodity balance . 93 Figure 6.2: Flows in the energy balance . 106 Figure 6.3: Illustration of calculating an energy balance from a commodity balance. 108 Figure 6.4: Adjusting for electricity generation from pump-storage plants in an energy balance . 113 Tables Table 3.1: Energy industries . 19 Table 3.2: Energy consumers . 23 Table 3.3: Types of energy resources . 36 Table 5.1: Summary of advantages and disadvantages related to statistical techniques . 61 Table 5.2: Suitable instruments and respondents depending on identified information needs. 62 Table 6.1: Commodity balances for fuelwood, motor gasoline and crude oil for Azerbaijan . 102 Table 6.2: Aggregated energy commodity balance for Norway 2011 (Preliminary figures) . 104 Table 6.3: Primary and secondary energy, natural units – Canada, 2011 . 105 Table 6.4: Percent of electricity and heat production that is from renewable sources for Austria . 115 Table 6.5: Calculation of the column “Of which: renewables” for Austria . 116 Table 6.6: Aggregated energy balance for Azerbaijan, 2011 (Thousand toe) . 118 Table 6.7: Aggregated energy balance for Austria, 2010. 119 Table 6.8: Production of primary and secondary products . 121 Table 6.9: Calculation of primary energy using the physical energy content method . 122 Table 6.10: Efficiency in different transformation processes (except electricity and heat generation) . 123 Table 6.11: Efficiency in transformation in thermal power plants and heat generation . 124 Table 6.12: Aggregated energy balance for the United Kingdom (3rd quarter 2012). 130 Table 7.1: Template for a Generic National Quality Assurance Framework . 134 Table 7.2: European Statistics Code of Practice – 15 Principles . 135 ix
Table 7.3: IMF’s Data Quality Assessment Framework (DQAF), Dimensions and Elements . 136 Table 7.4: Statistics Canada, Quality Assurance Framework . 137 Table 7.5: Examples of Data Quality Frameworks . 138 Table 7.6: Selected Indicators for Measuring the Quality of Energy Statistics . 144 Table 8.1: Confidentiality practices in selected countries . 163 x
List of Abbreviations and Acronyms API American Petroleum Institute BPM6 Balance of Payments and International Investment Position Manual Btu British thermal unit CHP Combined Heat and Power CPC Central Product Classification DQAF Data Quality Assessment Framework EEA European Environmental Agency ESCM Energy Statistics Compilers Manual Eurostat Statistical Office of the European Communities GCV Gross Calorific Value GDP Gross Domestic Product GHG Greenhouse Gas GTL Gas-to-Liquids GWh Gigawatt hour HS Harmonized Commodity Description and Coding System IEA International Energy Agency InterEnerStat Intersecretariat Working Group on Energy Statistics IPCC Intergovernmental Panel on Climate Change IRES International Recommendations for Energy Statistics ISIC International Standard Industrial Classification of All Economic Activities LNG Liquefied Natural Gas LPG Liquefied Petroleum Gas kWh Kilowatt hour NQAF National Quality Assurance Framework NCV Net Calorific Value NGL Natural Gas Liquid OECD Organisation for Economic Co-operation and Development SBP Special Boiling Point xi
SDMX Statistical Data and Metadata Exchange SEEA System of Environmental-Economic Accounts SEEA-Energy System of Environmental-Economic Accounting for Energy SI Systèmes International d’Unités SIEC Standard International Energy Product Classification SIMS Single Integrated Metadata Structure SNA System of National Accounts TES Total Energy Supply Tce Ton of coal equivalent Toe Ton of oil equivalent UN United Nations UNFC United Nations Framework Classification for Fossil Energy and Mineral Reserves and Resources UNFCCC United Nations Framework Convention on Climate Change UNSD United Nations Statistics Division VAT Value added tax xii
Chapter 1: Introduction A. Background 1.1. Energy plays an essential role in almost all forms of human activity. A successful economy is typically characterised by a reliable and efficient supply of energy that meets the full range of its social and economic needs. Ideally, all households should have access to clean, affordable and reliable energy while businesses should have access to energy that enables them to produce goods and services in a competitive marketplace. Businesses that supply energy should also be viable and ongoing. However, growing worldwide demand for energy gives rise to concerns about the sustainability of supply and the impacts on the environment. 1.2. In this modern context, it is essential for countries to monitor and manage their energy resources and various aspects of energy production and use. In order to do this well, it is important to ensure that policy decisions are informed by reliable and appropriate data. The development of systems to produce quality and consistent energy information should be based on internationally agreed-upon standards, classifications and other frameworks as these will enable cross-country comparability and consistency over time. 1.3. There is a broad range of contemporary energy issues that must be addressed. These include: ensuring a sustainable supply of energy resources for the future; developing and maintaining the infrastructure for the transport of energy products to market; managing energy price volatility; encouraging investment, innovation and efficiency in the energy sector; ensuring emergency preparedness; and managing environmental impacts of energy production and use. 1.4. Relevant and timely energy data are necessary to support evidence-based energy policy and decision-making, to monitor and assess programs, to enable research and analysis, and to inform the public on energy-related matters. As such, energy statistics are vital for a well-functioning economy and a well-maintained environment. With this context and no internationally agreed standards for energy statistics collection, it was natural for the United Nations Statistical Commission to call for the revision and further development of relevant international statistical guidelines at its thirty-sixth and thirtyseventh session. B. The International Recommendations for Energy Statistics 1.5. The United Nations Statistical Commission, at its forty-second session held in New York, 22 to 25 February 2011, adopted the International Recommendations for Energy Statistics (IRES). The Energy Statistics Compilers’ Manua
iii Preface The Energy Statistics Compilers Manual (ESCM) is a publication that complements in a practical manner the International Recommendations for Energy Statistics (IRES), which provides a comprehensive methodological framework for the collection, compilation and dissemination of energy statistics in all countries irrespective of the level of development of their statistical system.
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2. Energy and the environment 3. Energy Production 4. Energy Consumption 5. Energy and Sustainable Development 6. Energy, development and the need for statistics 7. Energy-environment statistics are key 8. Applying the FDES to energy statistics 9. Energy-environment common indicators 1. Cross-cutting issues applications of the FDES Water and .
Chapter 2 was drafted by INEGI, Mexico. Chapter 3 was drafted by UNSD. Chapters 4 and 5 were initially drafted by Statistics Austria and then elaborated upon by UNSD (earlier versions had combined the chapters). Chapter 6 was drafted by Statistics Norway, and elaborated upon by the IEA and UNSD. Chapter 7 was drafted by Statistics Canada.
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