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Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market

Author

Listed:
  • C. Gao
  • E. Bompard
  • R. Napoli
  • Q. Wan

Abstract

The participants of the electricity market concern very much the market price evolution. Various technologies have been developed for price forecast. SVM (Support Vector Machine) has shown its good performance in market price forecast. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecast accuracy, with which the being rejected risk is defined. The other takes into account the impact of the producer's own bid. The risks associated with the bidding are controlled by the parameters setting. The proposed approaches have been tested on a numerical example.

Suggested Citation

  • C. Gao & E. Bompard & R. Napoli & Q. Wan, 2007. "Bidding Strategy with Forecast Technology Based on Support Vector Machine in Electrcity Market," Papers 0709.3710, arXiv.org.
    • Handle: RePEc:arx:papers:0709.3710
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    References listed on IDEAS

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    1. Gao, Ciwei & Bompard, Ettore & Napoli, Roberto & Cheng, Haozhong, 2007. "Price forecast in the competitive electricity market by support vector machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 98-113.
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