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Planning Electric Power Systems Under Demand Uncertainty with Different Technology Lead Times


  • Douglas T. Gardner

    (Algorithmics Inc., 185 Spadina Avenue, Toronto, Ontario, Canada M5T 2C6)

  • J. Scott Rogers

    (Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada M5S 1A4)


Demand uncertainty is a key concern of electric utility planners. While the greater use of short lead time technologies provides one possible way to deal with this problem, it is not clear how they are best deployed. The approach taken in this paper is to examine a capacity mix model that explicitly accounts for differences in technology lead times. Key results that are obtained include the characterization of the optimal solution and the development of a new set of technology screening criteria. In practice, the "lead time order" (i.e., the set of available technologies ordered by ascending length of lead time) is typically the inverse of the so-called merit order (i.e., the set of available technologies ordered by ascending operating cost). We show that for this case, the optimal solution may be determined with relative ease. A numerical example demonstrates that some short lead time technologies screened out by standard planning methods may enter the optimal solution when differences in lead time are considered, while some long lead time technologies may leave. In addition, the optimal expected level of reliability may be greater.

Suggested Citation

  • Douglas T. Gardner & J. Scott Rogers, 1999. "Planning Electric Power Systems Under Demand Uncertainty with Different Technology Lead Times," Management Science, INFORMS, vol. 45(10), pages 1289-1306, October.
  • Handle: RePEc:inm:ormnsc:v:45:y:1999:i:10:p:1289-1306

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    References listed on IDEAS

    1. Albert Madansky, 1960. "Inequalities for Stochastic Linear Programming Problems," Management Science, INFORMS, vol. 6(2), pages 197-204, January.
    2. Gardner, Douglas T., 1996. "Flexibility in electric power planning: Coping with demand uncertainty," Energy, Elsevier, vol. 21(12), pages 1207-1218.
    3. James E. Smith & Robert F. Nau, 1995. "Valuing Risky Projects: Option Pricing Theory and Decision Analysis," Management Science, INFORMS, vol. 41(5), pages 795-816, May.
    4. Hung-po Chao, 1983. "Peak Load Pricing and Capacity Planning with Demand and Supply Uncertainty," Bell Journal of Economics, The RAND Corporation, vol. 14(1), pages 179-190, Spring.
    5. Kleindorfer, Paul R & Fernando, Chitru S, 1993. "Peak-Load Pricing and Reliability under Uncertainty," Journal of Regulatory Economics, Springer, vol. 5(1), pages 5-23, March.
    6. George Stigler, 1939. "Production and Distribution in the Short Run," Journal of Political Economy, University of Chicago Press, vol. 47, pages 305-305.
    7. Nissan Levin & Asher Tishler & Jacob Zahavi, 1985. "Capacity Expansion of Power Generation Systems with Uncertainty in the Prices of Primary Energy Resources," Management Science, INFORMS, vol. 31(2), pages 175-187, February.
    8. H. D. Sherali & A. L. Soyster & F. H. Murphy & S. Sen, 1984. "Intertemporal Allocation of Capital Costs in Electric Utility Capacity Expansion Planning Under Uncertainty," Management Science, INFORMS, vol. 30(1), pages 1-19, January.
    9. Elizabeth Olmsted Teisberg, 1994. "An Option Valuation Analysis of Investment Choices by a Regulated Firm," Management Science, INFORMS, vol. 40(4), pages 535-548, April.
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    1. Malischek, Raimund & Tr├╝by, Johannes, 2016. "The future of nuclear power in France: an analysis of the costs of phasing-out," Energy, Elsevier, vol. 116(P1), pages 908-921.


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