Ramesh Bhatia

Overview

Energy demand analysis (EDA) is an important component of integrated energy plans and policy in developing countries. Planners and policymakers must understand the factors that affect the growth and pattern of energy demand to forecast energy demand and design policies for energy conservation. In turn, the analysis of demand requires the assembly of a consistent set of data (broken down by energy type and end-use sector) on the consumption of, and demand for, various forms of commercial and noncommercial (traditional) energy.

This paper reviews methods used to estimate consumption and demand. It includes estimates for commercial and traditional energy forms, methods of aggregation, data presentation, assessment of unfulfilled demand, and analysis of the shift from noncommercial to commercial sectors. Methods to analyze changes in energy consumption and demand are addressed (including methods of EDA at the macro and sectoral levels). Finally, a number of research issues pertaining to improved EDA are identified.

Analysis

Methods for Estimating Consumption and Demand

Estimates for Commercial Sources-Al though data on commercial forms of energy (for example, coal, natural gas, and electricity) are generally available, substantial effort may be required to assess the quality of information and to develop a consistent database for energy production, trade, and final consumption. Some of the difficulties encountered in developing a consistent set of energy tables include

• An inability to distinguish between transformation uses or losses and final consumption,

• Problems in separating consumption figures into relevant end-use sectors (for example, retail diesel sales do not identify the quantities consumed by trucks, buses, tractors, and irrigation pumps),

• Difficulties in distinguishing between energy consumed as fuel and energy consumed as a feedstock, and

• A lack of data on indirect fuel exports (for example, sales of oil products to international airlines and energy exchanges between neighbouring countries).

Estimates for Traditional Sources-The data on noncommercial forms of energy are generally weak. Surveys are necessary to collect information on the consumption of biomass and of animal-derived fuels. Data are also required on the energy content of these fuels, variations in moisture content over seasons, and energy conversion and appliance efficiencies (for example, the efficiency of wood-to-charcoal conversion and of cooking with woodstoves). The estimates of energy use must also be cross-checked with the estimates of animal stocks and biomass resources. The consumption data should be presented in terms of end uses such as household cooking and heating, industrial heating and steam-raising, brick-making, and animal work in agricultural operations.

Methods of Aggregation and Presentation-The use of standard energy conversion factors (for example, tonnes of oil equivalent) to aggregate fuel-specific energy use may distort the relative contribution of each energy source. These accounting measures do not recognize differences in fuel quality (for example, oil is a more convenient fuel and has higher efficiency than coal in many end uses). Therefore, data in original (natural) units should be used, and aggregation should indicate only rough orders of magnitude. Animate energy can be measured by estimating the number of work animals and converting this to energy output based on output (for example, 1.3 MJ/h) per animal, using the energy equivalent of the fodder consumed by the animals, or estimating the diesel oil that would be required to replace the animals with tractors.

Two methods of presenting data on energy transactions are the energy balance table (EBT) and the reference energy system (RES). The EBT presents data on energy production, imports, transformation losses, exports, and final consumption in a consistent matrix format. The RES focuses on estimates of the efficiencies with which fuels are converted, transported, and consumed by various end-use devices. The RES provides this information in a flow diagram that traces various stages from production to consumption. A time series of EBTs can be used to study the determinants of energy demand, whereas the RET can be incorporated into planning models by using mathematical programing techniques.

Assessment of Shift from Noncommercial to Commercial Sources-Estimates of consumption can be used to assess trends in fuel switching between noncommercial and commercial forms of energy. This analysis is helped by the results of special surveys on fuel usage and by studies of the impact of relative energy prices on the demand for these energy forms. A particularly important sector is agriculture, where mechanization increases both the sector's reliance on commercial energy forms and its energy intensity.

Assessment of Unfulfilled Demand-Frequently, the consumption of energy does not reflect demand because of supply constraints, transmission and distribution problems, and adverse conditions of income distribution and purchasing power. Two approaches to estimating unfulfilled demand are special surveys of energy consumers and the collection of indirect evidence (for example, greater deforestation, illegal sales, and increases in the prices of uncontrolled fuels).

Understanding Changes in Consumption and Demand

EDA at the Macro Level-Some of the many ways in which energy demand may be analyzed include

• Comparing the growth rate of energy use with the growth of GDP over a given time and estimating the elasticity of energy consumption with respect to GDP,

• Computing energy consumption per unit of real GDP over time and interpreting the results with respect to trends in the energy-GDP ratio,

• Estimating the demand elasticity with respect to GDP based on regression analysis over historical data (observations) on GDP and energy consumption, and

• Using general equilibrium models that take into account the interactions among economic output, sectoral patterns of growth, energy prices, and energy consumption.

The analyses should be done separately for commercial and total energy and for different sources of commercial energy. This will ensure that the generally weak database for consumption of traditional energy forms does not affect the analysis of commercial sources of energy.

EDA at the Sectoral Level-Macro analysis does not identify sector-specific factors affecting energy use. To identify these factors, sectoral models of energy demand must be developed and adapted to the availability of data and the causal factors involved in each sector (for example, agriculture, industry, transportation, and households). To ensure consistency across the sectoral studies, it is advisable to use the database embodied in EBTs as the starting point for the analysis. The sectoral studies should then attempt to quantify the relationship between sectoral energy use and economic variables (for example, sectoral output, energy prices, and demographics).

Suggestions for Further Research

Research is needed to

• Identify end uses in which traditional fuels are most important, and identify data gaps,

• Study issues such as changes in supply and demand for biomass fuels, including the impacts of conversion and utilization efficiencies and different processes of production,

• Identify the groups facing a shortage in biomass supply, and assess the welfare effects of the commercialization of biomass fuels and the switch to commercial fuels,

• Review and collate the results of studies of energy demand, including the role of energy prices, fuel switching, and energy conservation,

• Assess methods of estimating unfulfilled energy demand and the effects of shortages, and

• Evaluate the social profitability of energy conservation compared with supply augmentation.