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Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem

Author

Listed:
  • Samer Takriti

    (Enron Research, Enron Building, 1400 Smith Street, Houston, Texas 77002)

  • Benedikt Krasenbrink

    (Mathematical Sciences Department, IBM Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

  • Lilian S.-Y. Wu

    (Mathematical Sciences Department, IBM Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598)

Abstract

The electric power industry is going through deregulation. As a result, the load on the generating units of a utility is becoming increasingly unpredictable. Furthermore, electric utilities may need to buy power or sell their production to a power pool that serves as a spot market for electricity. These trading activities expose utilities to volatile electricity prices. In this paper, we present a stochastic model for the unit commitment that incorporates power trading into the picture. Our model also accounts for fuel constraints and prices that may vary with electricity prices and demand. The resulting model is a mixed-integer program that is solved using Lagrangian relaxation and Bender's decomposition. Using this solution approach, we solve problems with 729 demand scenarios on a single processor to within 0.1% of the optimal solution in less than 10 minutes. Our numerical results indicate that significant savings can be achieved when the spot market is entered into the problem and when stochastic policy is adopted instead of a deterministic one.

Suggested Citation

  • Samer Takriti & Benedikt Krasenbrink & Lilian S.-Y. Wu, 2000. "Incorporating Fuel Constraints and Electricity Spot Prices into the Stochastic Unit Commitment Problem," Operations Research, INFORMS, vol. 48(2), pages 268-280, April.
    • Handle: RePEc:inm:oropre:v:48:y:2000:i:2:p:268-280
    DOI: 10.1287/opre.48.2.268.12379
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    References listed on IDEAS

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    1. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    2. John A. Muckstadt & Sherri A. Koenig, 1977. "An Application of Lagrangian Relaxation to Scheduling in Power-Generation Systems," Operations Research, INFORMS, vol. 25(3), pages 387-403, June.
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