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Restriction techniques for the unit-commitment problem with total procurement costs

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  • Kaleta, Mariusz
  • Toczylowski, Eugeniusz

Abstract

Many discrete optimization problems may be solved much easier, if the solution space can be restricted in a convenient way. For a given specific problem, the restriction techniques can be helpful if an available optimization solver, perceived as a black box, is capable of solving quickly only reduced subproblems of a limited size. For the family of hard unit-commitment problems we investigate a hierarchical search algorithm, which is based on decomposition of the problem into two subproblems. The upper-level subproblem is a relatively small decision "kernel" of the problem that can be solved approximately by a search algorithm. We define an appropriate restricted decision space for this subproblem. The lower-level subproblem is an appropriate restriction of the original problem that can be solved efficiently by a dedicated solver. Our approach was analyzed on a set of historical data from the Polish electrical balancing market and the best known solutions were improved by the average of about 2-5%.

Suggested Citation

  • Kaleta, Mariusz & Toczylowski, Eugeniusz, 2008. "Restriction techniques for the unit-commitment problem with total procurement costs," Energy Policy, Elsevier, vol. 36(7), pages 2439-2448, July.
    • Handle: RePEc:eee:enepol:v:36:y:2008:i:7:p:2439-2448
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    References listed on IDEAS

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    1. 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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    3. Emanuel Canelas & Tânia Pinto-Varela & Bartosz Sawik, 2020. "Electricity Portfolio Optimization for Large Consumers: Iberian Electricity Market Case Study," Energies, MDPI, vol. 13(9), pages 1-21, May.

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