Bidding strategy with forecast technology based on support vector machine in the electricity market

被引:12
作者
Gao, Ciwei [2 ]
Bompard, Ettore [1 ]
Napoli, Roberto [1 ]
Wan, Qiulan [2 ]
Zhou, Jian [3 ]
机构
[1] Politecn Torino, Dipartimento Ingn Elettr, I-10129 Turin, Italy
[2] SE Univ, Sch Elect Engn, Nanjing 210096, Jiangsu, Peoples R China
[3] Yangzhong Power Distribut Co, Zhenjiang 212200, Jiangsu, Peoples R China
关键词
electricity market; strategic bidding; price forecast; support vector machine;
D O I
10.1016/j.physa.2008.02.080
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:3874 / 3881
页数:8
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