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Bidding strategy with forecast technology based on support vector machine in the electricity market
Authors:Ciwei Gao  Roberto Napoli  Jian Zhou
Affiliation:a Southeast University-School of Electrical Engineering, 210096, Nanjing, Jiangsu, PR China
b Politecnico di Torino-Dipartimento di Ingegneria Elettric 10129, Torino, Italy
c Yangzhong Power Distribution Company, 212200, Zhenjiang, Jiangsu, PR China
Abstract:The participants in the electricity market are concerned very much with the market price evolution. Various technologies have been developed for price forecasting. The SVM (Support Vector Machine) has shown its good performance in market price forecasting. Two approaches for forming the market bidding strategies based on SVM are proposed. One is based on the price forecasting accuracy, with which the rejection 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 parameter settings. The proposed approaches have been tested on a numerical example.
Keywords:Electricity market   Strategic bidding   Price forecast   Support vector machine
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