Energy Demand Analysis

Energy demand analysis is the first step towards determining whether it is feasible to put-together an energy supply mixes compatible with the achievement of a sustainable world at the projected energy demand levels³. It considers the activities in individual energy­ consuming sectors of the economy. It relates macro­economic developments to the energy needed to sup­port those developments in each sector. Demand analysis enables a disaggregated, end use approach to analyze the energy requirements. It uses economic, demographic and energy use information to compute and report on total and disaggregated consumption of various end use fuels⁴. It plays a sequential, intermediate, and iterative role in energy planning. First, it follows the phase of database establishment. Secondly, its output serves as input to energy policy analysis. Finally, demand analysis occurs iteratively. Two major approaches of energy demand analysis are macro and sectoral demand analysis. Macro demand analysis considers demand as a function of popula­tion, income, and prices. Sectoral demand analysis examines the structure of sectors and sub-sectors and their energy consuming activities, including the equipment². The issues associated with energy demand analysis are:

• Most energy planning exercises are carried out with aggregate data at national level. At regional level, there have been fewer efforts for energy planning. Energy resources and demand are spatially distributed⁵.

• Studies of traditional fuel sources are needed to focus on issues such as, changes in supply and demand of biomass fuels, determinants of use of biomass sources as fuel, fodder and fertilizer, changes in efficiencies of conversion and utiliza­tion, processes of generation and use of traditional sources of energy in the context of socio-political characteristics of a location.

• Meeting the basic energy needs of population at a reasonable cost would be an important policy ob­jective, it is therefore necessary to identify regions and households that currently face deficit or likely to develop a deficit in biomass resources and to analyze how their current needs are being met.

• There is a need to review the method and collate the results of available studies on energy demand analysis and management. Such a review should collate empirical information on the role of energy prices, possibilities of interfuel and interfactor substitution, and economics of conservation.

• Analysis of various methods of estimating energy shortages or unfulfilled demand for different sec­tors and categories of consumers.

• Estimates should be made of energy shortages and the processes through which the shortages have been managed. The impact of shortages on agricultural output, industrial output, employment, regional development, income distributions, con­sumer welfare, consumer health, etc., should be quantified.

• In the context of energy demand, there is a need to evaluate the social profitability of the allocation of various scarce resources to conserve rather than augment ⁶.

Energy Consuming Sectors

Sectors for energy analysis can be categorized as: i) Domestic sector (lighting, cooking, heating and other uses); ii) Municipal sector (street lighting, public water works); iii) Industrial sector (process heating, electric drive ore reduction, and industrial lighting); and iv) Transport sector; and, Agriculture sector (irrigation, harvesting, thrashing and land preparation). These sectors represent a mixture of different types of rural and urban households, industries, agriculture, and other establishments, which are often difficult to disaggregate with any reasonable degree of confidence. The largest single component of demand in this group stems from households.

The consumption of energy for lighting, cooking, heating, and other appliances by households and the service industry has shown significant changes in the recent past. Growth in household incomes and in urbanization has been accompanied by a change in the fuel mix to more efficient fuels; partly as a result, energy consumption per household appears to have stagnated in some countries. While an urban home largely depends on cooking gas and electricity for its energy requirements, 85 - 90 per cent of the energy demand of a rural home is dependent on firewood or fuel wood⁵. The domestic energy expenditure, with the increasing cost of energy, is gradually assuming a sizable share of the total domestic expenditure.

Energy consumption patterns in the Indian residen­tial sector vary widely not only among the rural and urban areas but also across various income classes in urban areas. In India, approx 86.1 per cent rural households use fuel wood and dung cakes for cooking, while 3.5 per cent use LPG for cooking. For lighting, 50.6 per cent of rural households use kero­sene and 49.4 per cent uses electricity. Out of annual average consumption of fuel wood (270 - 300 mt ) and kerosene (10.5 mt), 60 per cent was in rural areas⁷.

The levels and forms of fuel consumed by the house­hold sector depend on income levels, size of settle­ments, households and city, price of fuels, the avail­ability and accessibility of modern commercial fuels, and the efficiency of the end-use equipment used. Differences in energy-use lie both in terms of per capita energy consumption and in choice of fuel to meet the energy demands. It has been observed that with higher levels of development in the economy and rising per capita income, households tend to move towards fuels that are cleaner, more efficient, convenient, and more expensive.

Energy Supply Analysis

Energy supply analysis normally incorporates the information on the present energy supply system and the potential for the future. This includes the assess­ment of energy sources and the evaluation of the fuel distribution and supply technologies. Technology evaluation provides information on technologies used for the processing of raw energy into energy forms that are useful to end users, while resource assessment provides the quality and cost of energy sources. The work has been done in this regard, to assess bioenergy potential for a region (Kolar district) using Bioenergy Potential Assessment (BEPA), a spatial decision support system. The main hypothesis is that, this tool can be used to form a core of practical methodology that will result in more resilient in less time and can be used by decision-making bodies to assess the impacts of various scenarios and to review cost and benefits of decisions to be made. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision-making.

The bioresource assessment requires estimation of the available bioresources and demand spatially for evolving better management strategies to ensure sustainability of resources. In this regard, Geographical Information System (GIS) plays an important role in providing geographically referenced spatial distri­bution of potential and demand on temporal scale. It offer tools for handling and analyzing socio-economic problems in addition to spatial analyses, particularly those related to decentralization and distribution of service and facilities, which helps in formulating policies. The ability of GIS is to integrate spatial data from disparate sources with different formats, structures, projections, or levels of resolutions⁸.

The DSS is built in a GIS environment with the objective to exploit its powerful features in handling all the parameters with geographic variability that influence biomass availability, site selection of the energy conversion facility and estimation of the performance and cost of the energy produced. The spatial distribution of renewable energy sources potential, the inherent renewable energy sources dependence in site specific characteristics and the overall cost dependence on spatial attributes make GIS an indispensable tool for energy management. The DSS, which incor­porates the advantages, offered by GIS technology in order to fully exploit renewable energy sources databases and handle efficiently the geographic characteristics that affect renewable energy sources potential and energy cost.

DSS has already been used to analyze village level domestic energy consumption patterns⁵, in a power plant simulation tool⁹, for energy planning in Bankura district¹⁰ and energy demand model for transport, in­dustrial and residential sectors in Thailand based on LEAP (Long-Range Energy Alternative Planning)¹¹.