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A hybrid method of GA and BP for short-term economic dispatch of hydrothermal power systems

Author

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  • Xiangping, Meng
  • Huaguang, Zhang
  • Wanyu, Tan

Abstract

This paper proposed a fast synthetic genetic algorithm (FSGA). The algorithm has faster convergence speed and higher computation precision, and the number of individuals and populations decreased, respectively. To overcome long training time of back propagation (BP) algorithm, this paper combined FSGA with BP, and applied the hybrid method to short-term economic dispatch of hydrothermal power system. The simulation results demonstrate that the hybrid method is effective and training time is short.

Suggested Citation

  • Xiangping, Meng & Huaguang, Zhang & Wanyu, Tan, 2000. "A hybrid method of GA and BP for short-term economic dispatch of hydrothermal power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 51(3), pages 341-348.
    • Handle: RePEc:eee:matcom:v:51:y:2000:i:3:p:341-348
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    Cited by:

    1. Coelho, Leandro dos Santos & Souza, Rodrigo Clemente Thom & Mariani, Viviana Cocco, 2009. "Improved differential evolution approach based on cultural algorithm and diversity measure applied to solve economic load dispatch problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3136-3147.

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