DocumentCode :
3154870
Title :
A preliminary study on strategic bidding in electricity markets with step-wise bidding protocol
Author :
Ma, Li ; Fushuan, Wen ; David, A.K.
Author_Institution :
Zhejiang Univ., Hangzhou, China
Volume :
3
fYear :
2002
fDate :
6-10 Oct. 2002
Firstpage :
1960
Abstract :
The power industry of China is now being restructured and generation markets are expected to be established nationwide in 10-15 years. Zhejiang provincial electricity market, as a pilot one, has been successfully operated for more than two years. Under electricity market environment, the profits of generation companies depend, to a large extent, on their bidding strategies. As a result, how to develop the optimal bidding strategy has become a major concern of generation companies. Given this background, a model of bidding strategies based on Zhejiang provincial electricity market in which step-wise bidding rules are utilized is developed in this paper. Rival bidding behaviors are described by a normal distribution function, and the problem of building the optimal bidding strategy for a generation company is then formulated as a stochastic optimization problem, and solved by a Monte Carlo approach. A simple numerical example with five suppliers is served for illustrating the essential features of the presented method.
Keywords :
Monte Carlo methods; power markets; power system economics; stochastic processes; China; Monte Carlo approach; Zhejiang provincial electricity market; electricity markets; generation markets; normal distribution function; optimal bidding strategy; power industry restructuring; step-wise bidding protocol; step-wise bidding rules; stochastic optimization; strategic bidding; Artificial neural networks; Electricity supply industry; Monte Carlo methods; Power generation; Power industry; Power markets; Power supplies; Power system modeling; Protocols; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES
Print_ISBN :
0-7803-7525-4
Type :
conf
DOI :
10.1109/TDC.2002.1177759
Filename :
1177759
Link To Document :
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