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Short-Term Generation Asset Valuation: A Real Options Approach
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Short-Term Generation Asset Valuation: A Real Options Approach

Author

Listed:
  • Chung-Li Tseng

    (Department of Civil & Environmental Engineering, University of Maryland, College Park, Maryland 20742)

  • Graydon Barz

    (Electricity & Natural Gas Practice, McKinsey & Co., Two Houston Center, 909 Fannin, Suite 3500, Houston, Texas 77010)

Abstract

This paper discusses using real options to value power plants with unit commitment constraints over a short-term period. We formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward-moving Monte Carlo simulation with backward-moving dynamic programming. We assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit, that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit, and that these commitment decisions, once made, are subject to physical constraints such as minimum uptime and downtime. We also account for the costs associated with starting up and shutting down a unit. Last, we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow Ito processes. Using numerical simulation, we show that failure to consider physical constraints may significantly overvalue a power plant.

Suggested Citation

  • Chung-Li Tseng & Graydon Barz, 2002. "Short-Term Generation Asset Valuation: A Real Options Approach," Operations Research, INFORMS, vol. 50(2), pages 297-310, April.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:2:p:297-310
    DOI: 10.1287/opre.50.2.297.429
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    References listed on IDEAS

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    1. David C. Shimko, 1994. "Options on futures spreads: Hedging, speculation, and valuation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(2), pages 183-213, April.
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    3. Dwight Grant & Gautam Vora & David Weeks, 1997. "Path-Dependent Options: Extending the Monte Carlo Simulation Approach," Management Science, INFORMS, vol. 43(11), pages 1589-1602, November.
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