Abstract
Energy systems analysis is a young field, with no long history of academic scholarship. Indeed, it is not even clear that energy planning and policy analysis itself has much recognition as an academic discipline, and the body of such knowledge as might be termed energy planning remains ill defined. Moreover, the body of knowledge that is germane to the unique problems of the third world is extremely fragmented, much of it not generally available in the places where lessons learned in one country could be usefully applied in another.
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Actually the original use of the term systems analysis did not necessarily imply quantitative, mathematical treatment of the system under study: some of the classic texts contain not a single equation. Systems analysis was meant simply as a way of approaching complex problems, emphasising comprehensive rather than partial analysis. In general, however, systems analysis has come to imply the use of formal mathematical techniques, and it is in this sense that we shall use the term here.
The definitional difficulties here are typified by the National Research Council Report, “Systems Analysis and Operations Research: A Tool for Policy and Program Planning for Developing Countires,” Commission on International Relations National Academy of Sciences, Washington, D.C., which defines applied systems analysis in the following terms: “Applied Systems Analysis is not merely a technique or group of techniques such as probability theory or mathematical problems; rather it can be thought of as a broad research strategy one that involves the use of techniques, concepts, and a scientific, systematic approach to the solution of complex problems. It is a framework of thought designed to help decision makers choose a desirable (or in some cases a “best”) course of action,” (p. 65). Systems analysis, then, is not easy to define in a few words.
For some other views of the National Energy Planning process in the context of developing countries, see e.g., “An Analytical Framework for the Assessment of Energy Resource and Technology Options for Developing Countries,” BNL 50800, Brookhaven National Laboratory, New York, NY, February 1978; or M. Munasinghe, “An Integrated Framework for Energy Pricing in Developing Countries,” Energy Journal, 1, 3 (1980) p. 1–30.
Supply curves, then, also have a probabilistic manifestation, since even if, say, a seismic survey considerably narrows the bounds of uncertainty, it may take years for a potential resource to be fully prospected. Thus the planner must work with supply curves subject to certain levels of uncertainty.
For a complete discussion on data needs, see e.g., P. Palmedo and R. Chatterjee, “Information Needs for Energy Planning,”U.N. Symposium on Energy Planning in Developing Countries, Stockholm, Sweden, October 1981. With respect to rural energy use, Palmedo and Chatterjee note”…almost universally it is found that the weakest area of existing energy information is for households, and particularly for consumption of “non-commercial” fuels such as wood or agricultural waste. The uncertainty of non-commercial fuel use is often at least ± 50 percent, despite the fact that such use is of great social and often environmental significance.”
It may be argued that research and development is best left to the developed countries who are better able to afford the not considerable expense. However, many universities in developing countries have excellent research programs: the challenge to the energy planner is to focus the country’s RμD efforts into the most promising areas from the perspective of the local energy system.
This is of course not a problem confined solely to energy sector investment, For example, in Tunisia for the period of the fourth Development Plan (1973–1976), investment was the only macro-economic objective not met (or exceeded). The World Bank, in its review of the prospects for the 5th Plan, noted that the otherwise excellent economic performance was offset by investment, “…which was 10 percent short of target because Government investment remained 30 percent below target. Investment performance during the Fourth Plan showed that the Governments and public enterprises’ capacity to identify, prepare and implement projects still needs considerable strengthening. The measures taken by the Government since the beginning of the decade to shift greater responsibility to the private sector, and supporting it through a generous incentive system, were reflected in the excellent investment performance of this sector that exceeded its target.”
In actuality total consumption will not be the only important parameter — to properly size the solar units requires a breakdown between kitchen, laundry and guest use.
The illustrative example used here assumed that the choices of the parties are independent — that is, the World Oil Price is unaffected by the choice of the National Government. Such a model would not be appropriate to very large exporters (such as Saudi Arabia), very large importers (such as the U.S.) or smaller countries that may strongly influence regional markets (such as Indonesia in South East Asia).
If all three oil price cases are equally likely, then strategy A has an expected value of E(A) = 0.33 × 3 + 0.33 × 4 + 0.33 × 6 - 4.29. E(B), however, computes to 4.62.
Many of the most successful economies in South and East Asia (Japan, Singapore, among others) illustrate this point.
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© 1984 Springer-Verlag Berlin Heidelberg
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Meier, P. (1984). Introduction. In: Energy Systems Analysis for Developing Countries. Lecture Notes in Economics and Mathematical Systems, vol 222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48337-0_1
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DOI: https://doi.org/10.1007/978-3-642-48337-0_1
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