| Energy research in developing countries |
|Volume 10: Energy planning: models, information systems, research, and development|
This paper sets out the parameters of a general approach to establishing a country-specific tool for energy policy and planning. This is a large undertaking that requires a substantial commitment of national resources. But, unlike specialized consultants who provide similar information on a "one-off" basis, the resulting policy and planning tool will contribute to the long-term effectiveness of government planning institutions and, hopefully, to the efficiency of the economy.
Policy analysts and energy planners are increasingly aware that the real problem when developing information systems for energy planning is not the modeling system. Rather, the challenge is to find the most appropriate resolution, system structure, and configuration for the problem and to choose the most appropriate objective function, given the data available on energy supply and demand.
A number of "off the shelf" evaluation models have been developed since the oil crises highlighted the need for comprehensive energy planning. Although these models have helped industrialized nations make decisions on their energy policies, repeated efforts to fit the special energy problems of developing nations to these models have been futile. Variability in energy systems, energy decision functions, and available information effectively limit the application of generalized systems to data management and core computer packages (for example, regression analysis, linear programing, and matrix inversion).
Consequently, the best approach when examining the situation in any given developing country is, in effect, to build a tool for energy information, policy, and planning from the ground up. The three key components of this tool are management, information, and modeling.
The most efficient and productive way to set up an information system is to involve future users of the tool in every stage of its construction. This includes the critically important, but admittedly tedious, task of gathering microlevel information (consumer surveys and fieldwork), organizing the data into a useable (computer compatible) form, and defining the model that will analyze the data and produce report-ready output.
The energy planning tool must be managed according to the specific circumstances of the country to ensure that it is used to its maximum advantage. First, the size of the energy delivery system(s) determines, to a large extent, the degree of risk involved in committing resources to any project. Small systems take on more risk than large systems when a single, large project is added. Integrated systems face smaller risks when any kind of new supply is added. Second, the information produced by the planning tool must be in a form that meshes with the decision-making structure. If local energy planning is established, planning and policy information in the national context may be of little use. Third, the possibility of fuel substitution and conservation must be taken into account (with a sufficiently high degree of resolution) to ensure that the information provided by planners is supplied in the appropriate context.
The Information Set
The lack of information for energy planning in developing countries is a major handicap. Energy systems rely largely on traditional fuels, and their supply and demand vary from location to location across the country. The energy market can, in any given country, be fragmented into several regions, which makes aggregation to the national level difficult and potentially meaningless for policy and planning purposes. Therefore, it is necessary to undertake regional analyses of energy balances (consumption and production) and to orient policymaking accordingly. Because great detail is involved in this approach, much effort, in terms of both person hours and financial resources, is required.
Data on energy consumption can only be acquired by ground-level surveys. This is because, depending on the nation in question, up to 95% of primary energy consumption is of fuelwood or other traditional energy sources. The "market" for these energy resources is almost always local, and it must be estimated from local indicators of supply and demand. For this survey to be representative, a large number of households and fuel suppliers must be included.
Data on energy production (including imports) are often equally difficult to obtain, but advances in technology have improved their reliability and coverage. For example, satellite maps that depict the location of biomass resources (on which so much of the developing world relies) have been available since the early 1970s. The information on these maps must be locally calibrated, which involves ground-level verification, often over vast expanses of territory. The wealth of information made available is well worth the effort.
Once the data are collected, they must be organized and used as soon as possible. If too much time passes, the risk increases that when the information is finally analyzed it will yield results that are out of date when compared with the current, constantly evolving local, regional, national, and global energy markets.
Supply -The general rule when selecting from among various supply options is that the net present value (NPV) of benefits accruing from the decision option is positive (see endnote 1). There are, in addition, two evaluation approaches that are more financial (rather than economic) in perspective. The "payback period" (PBT) assesses the relative profitability of a project, which is defined as the number of years required to recover the investment costs of a project from its cash flow. In NPV terms, this is the number of years required to achieve a net present value of zero (see endnote 2). This approach is only useful if calculated paybacks are short (2 years or less indicates a good project) or very long (20 years or more indicates a poor investment). Uncertainty over intermediate times means that a more sophisticated tool must be used.
When the service produced by the investment is a fuel or energy flow, the "levelized cost" of the energy produced (or consumption avoided) can be computed. This is the "price" that must be charged to recover the total cash flow within the lifetime of the project. The levelized cost is the product of the capital recovery factor (CRF) and the present value of total costs (PVC) (see endnote 3).
Most project evaluations are based on the "internal rate of return" (IRR), which, like payback period, is calculated using the concept of discounting. The IRR is the discount rate that, when applied to a stream of benefits and costs reflected in the cash flow of a project, produces a NPV of zero (see endnote 4). Projects are generally acceptable when the IRR is greater than the accounting rate of interest (banking rate). The greater the rate of return, the more acceptable the project because a greater NPV of benefits will accrue from the investment.
Demand-Attempts to model energy decision-making by households have generally used econometric techniques. These methods are useful, but they can oversimplify actual consumer decision-making, especially in a dynamic context. A more appropriate approach might be to treat consumer decision-making as a simple accounting problem, in which consumers base their energy decisions on the capital cost of equipment (including subsidies and other policy incentives), the relative out-of-pocket costs of fuel alternatives, and an appropriate discount rate. Aggregation of the demand functions for a given population yields a target for the purpose of planning energy supply.
These classical approaches to project evaluation may appear simple. However, in practice they require a comprehensive understanding of the environmental, technical, economic, and financial factors that can affect the outcome of a decision and its long-term consequences.
1. Calculated as follows:
where B is benefits in year t, C is costs in year t, T is the overall time horizon in number of years, and r is the selected discount rate.
2. Calculated as follows:
where B is the benefit of the project in year t, C is the cost in that year, PBT is the payback time in years, and r is the selected discount rate.
CRF= r /[ (1 - (1 + r)-I ], where I is the lifetime of the project, and
where TC is the total cost in year t, T is the overall time horizon in years, and r is the selected discount rate.
4. Calculated as follows:
where B. C, T. t, and r are as defined in endnote 1, and IRR is the internal rate of return.