Global Energy Demand Collaborative
The past decade has seen the development of many scenarios describing long-term patterns of future Greenhouse Gas (GHG) emissions. Each new approach adds additional insights to our understanding of overall future energy trends. In most of these models, however, a description of sectoral activity variables is missing. End-use sector-level results for buildings, industry, or transportation or analysis of adoption of particular technologies and policies are not provided in global energy modeling efforts.
All major analyses of long-term impacts of greenhouse gas emissions to date rely on scenarios of energy supply and demand. The underlying drivers of all such major scenarios are macro socioeconomic variables (GDP, population,) combined with storylines describing the context of economic and social development. Unfortunately, these scenarios do not provide more detail than the sector level (i.e., buildings, industry, transportation). This is to say that the scenarios are developed without reference to the saturation, efficiency, or usage of air conditioners, for example. For energy analysts and policymakers, this is a serious omission, calling into question the very meaning of the scenarios. Energy consumption is driven by the diffusion of various types of equipment; the performance, saturation, and utilization of the equipment has a profound effect on energy demand. Policy analysts wishing to assess the impacts of efficiency or other mitigation policies require more detailed description of drivers and end use breakdown.
As a result of this methodological shortcoming, published scenario results to 2050 exhibit a very wide range in CO2 emissions by a factor of 20. For 2100, the variation is far greater.
Based on these considerations and LBNL's extensive expertise in energy demand, the goal of this project is to build a new generation global energy and CO2 emissions model that will be based on the level of diffusion of end use technologies . The model will address end-use energy demand characteristics including sectoral patterns of energy consumption, trends in saturation and usage of energy-using equipment, technological change including efficiency improvements, and links between urbanization and energy demand. To this end, LBNL's Environmental Energy Technologies Division (EETD) has initiated the Global Energy Demand Collaborative to establish cooperation with energy analysts across the world that develop energy end use indicators. The ultimate goal of the GEDC is to build from a better awareness of the drivers of end use energy consumption and construct complete modeling system that covers the entire world (by region or country), and covers all economic sectors at the end use level. In the short and medium term, the core GEDC team has produced a series of publications and reports including: country studies, sector studies, or methodology reports.
Staff
Approach
The GEDC is developing a global energy demand model mirroring the 10 regions of the SRES scenarios. However, because detailed data are not available for all countries in all regions, the approach used is to further disaggregate each region into one or more marker countries (where better data are available) and a remaining rest of region sub-region to represent all other countries in a given region. Marker countries have a more detailed analysis of technologies and are used to inform trends in the rest of each region. In particular, indicator data is readily available for most sectors in industrialized countries, but it is rare in even the largest developing countries. For this reason, LBNL is collaborating on a major initiative to collect developing country energy indicators.
The GEDC is developing a global energy demand model mirroring the 10 regions of the SRES scenarios. However, because detailed data are not available for all countries in all regions, the approach used is to further disaggregate each region into one or more marker countries (where better data are available) and a remaining rest of region sub-region to represent all other countries in a given region. Marker countries have a more detailed analysis of technologies and are used to inform trends in the rest of each region. In particular, indicator data is readily available for most sectors in industrialized countries, but it is rare in even the largest developing countries. For this reason, LBNL is collaborating on a major initiative to collect developing country energy indicators.
To facilitate this approach, different levels of analysis are used in different regions and countries depending on the availability of data. These characteristic levels of analysis are keys to the GEDC strategy, which aims to produce a global model while focusing in on those countries and sectors where data is most available. Level 1 analysis are used where data are poor and for the regional remainders, while level 2 analysis will be used where better data are available. In some countries, the GEDC uses a level 3 analysis which will include detailed treatment of devices within a stock turnover model This level has been achieved for China, for example.
GEDC Levels of Analysis
Although the analysis of consumption differs by country and sector according to level of detail, all data are kept together in a single accounting framework. In order to assure sufficient flexibility and detail for the global model, GEDC chose to use the LEAP modeling system.
Emissions Scenarios
Energy consumption forecasting follows a parallel set of levels of detail, with detail distinguished both by countries but by sectors. The GEDC team has constructed a forecast for residential electricity consumption covering all regions at the end use level and seeks to expand this model to the transport and commercial buildings sector, as well as modeling other fuels in the residential sector. End-use level forecasting models equipment (appliance) uptake and unit energy consumption as a function of macroeconomic variables (per capita GDP, electrification and urbanization). The dependence of energy consumption to macroeconomic input variables has been determined according to regression analysis of historical data from a range of countries, both industrialized and developing. In the other sectors, forecasting has so far been done at a macro level by relating sector production quantities and intensities to value added GDP. A forecast of energy consumption at the end use or even equipment type level allows for construction of alternative emissions scenarios at a level of detail not achieved by top-down models. The GEDC forecasts allow for studies of sensitivity of consumption to macroeconomic patterns at the country, sector or enduse level. More importantly, they allow for construction of mitigation scenarios which are informed by a deep understanding of emerging technologies, changing use patterns, and policy options designed to address energy consumption.
Energy consumption forecasting follows a parallel set of levels of detail, with detail distinguished both by countries but by sectors. The GEDC team has constructed a forecast for residential electricity consumption covering all regions at the end use level and seeks to expand this model to the transport and commercial buildings sector, as well as modeling other fuels in the residential sector. End-use level forecasting models equipment (appliance) uptake and unit energy consumption as a function of macroeconomic variables (per capita GDP, electrification and urbanization). The dependence of energy consumption to macroeconomic input variables has been determined according to regression analysis of historical data from a range of countries, both industrialized and developing. In the other sectors, forecasting has so far been done at a macro level by relating sector production quantities and intensities to value added GDP. A forecast of energy consumption at the end use or even equipment type level allows for construction of alternative emissions scenarios at a level of detail not achieved by top-down models. The GEDC forecasts allow for studies of sensitivity of consumption to macroeconomic patterns at the country, sector or enduse level. More importantly, they allow for construction of mitigation scenarios which are informed by a deep understanding of emerging technologies, changing use patterns, and policy options designed to address energy consumption.
Long Range Energy Alternatives Planning Model (LEAP)
The accounting framework chosen for the analysis is the Long-range Energy Alternatives Planning (LEAP) software developed by the Stockholm Environment Institute (SEI). LEAP was chosen because of its multi-regional capabilities, end-use based modeling approach, flexible data structures & choice of modeling methodologies. However, to better support the GEDC approach SEI has been asked by LBNL to further adapt LEAP to support the analysis of alternative data structures and different levels of disaggregation in different regions of the analysis.
Developing Country Energy Indicators - Collaboration between LBNL/IEA/World Bank
LBNL will assist the IEA and the World Bank to develop energy efficiency indicators (EIIs) for the G+5 countries – Brazil, China, India, Mexico and South Africa. In the past, the lab and the IEA have collaborated to develop sets of energy efficiency indicators for OECD countries. One of the major outputs of this work is the publication Oil Crises & Climate Challenges- 30 Years of Energy Use in IEA Countries.
The construction of a comprehensive data set on energy use and activity is a necessary step to increase the knowledge about evolution of energy use. To separate the effect of various components over time, a sectoral decomposition is necessary where changes in sectoral energy use are analyzed in terms of sectoral / sub-sectoral activity, sectoral structure, and energy intensity of each sub-sector. The methodology combines data on energy use with data describing activities that drive energy demand to form selected energy indicators for the different sectors of the economy. The project will also involve local in-country stakeholders to examine the status and system of energy efficiency data collection and analysis. It is expected that the collection of valid data at a disaggregated level, in important end-use sectors such as transport, industry and buildings, will facilitate the development of a generation of energy indicators that will allow policy makers in the G+5 countries and other developing countries to implement and monitor more effective energy efficiency and technology policies.
The project began in June 2007.
Publications and Reports
Sectoral Trends in Global Energy Use and Greenhouse Gas Emissions
This report describes the results of a disaggregation of the SRES projected energy use and energy-related CO2 emissions for the industrial, transport, and buildings sectors for 10 world regions to 2030. An example of further disaggregation of the two SRES scenarios for the residential buildings sector in China is provided, illustrating how such aggregate scenarios can be interpreted at the end use level. The report also show the difference between results from the SRES scenarios and scenarios based on bottom up assumptions.
Energy Use in China: Sector Trends and Future Outlook (forthcoming)
Energy Use in India: Sector Trends and Future Outlook (forthcoming)
Residential Electricity in India and What can be done about it
This paper explores the dynamics of demand growth of residential electricity and the realistic potential for coping with it through efficiency. The paper forecasts ownership growth of each product using econometric modeling. Using this method, we determine the trend and dynamics of demand growth and its dependence on economic scenarios at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level.
What do India's transport energy data tell us?
Transportation mobility in India has increased significantly in the past decades. Unfortunately, existing energy data do not provide information on driving forces behind energy use and sometime show large inconsistencies. This paper fills a considerable gap by developing a database for all transport modes including passenger air and water, and freight in order to facilitate the development of energy scenarios and assess significance of technology potential in a global climate change model.
Forecasting Air Conditioning Consumption in Developing Countries
This paper combines econometric modeling of ownership rates with geographically specific efficiency scenarios in order to assess future residential air conditioner ˜business as usual" electricity consumption by country/region and to consider specific alternative high efficiency scenarios. The result is a detailed set of consumption and emissions scenarios for residential air conditioning.
Global Potential of Energy Efficiency Standard and Labeling Programs
This report estimates the global potential reductions in greenhouse gas emissions by 2030 for energy efficiency improvements associated with equipment (appliances, lighting, and HVAC) in buildings by means of energy efficiency standards and labels (EES&L). We believe the analysis reported here to be the first systematic attempt to evaluate the potential of savings from EES&L for all countries and for such a large set of products. The goal of the analysis is to provide an assessment that is sufficiently well-quantified and accurate to allow comparison and integration with other strategies under consideration.
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