Optimal bidding strategy for GENCOs based on parametric linear programming considering incomplete information

被引:13
|
作者
Gao, Feng [1 ]
Sheble, Gerald B. [2 ]
Hedman, Kory W. [3 ]
Yu, Chien-Ning [4 ]
机构
[1] SGRI North Amer, Santa Clara, CA 95054 USA
[2] Iowa State Univ, Ames, IA 50011 USA
[3] Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ USA
[4] Ventyx, Santa Clara, CA 95050 USA
关键词
Bidding strategy; Decision analysis; Incomplete information; Parametric linear programming; Non-convex optimization; ELECTRICITY MARKET; COMPANIES;
D O I
10.1016/j.ijepes.2014.10.053
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Electric energy market participants face risks and uncertainties associated with the ever-changing market environment. A profit-driven bidding decision tool is thus crucial for generation companies (GENCOs) to maintain a competitive position. Although optimal bidding strategies have been extensively studied in the literature, most previous research assumes continuous and differentiable generation offer curves, whereas actual offer curves are piecewise staircase curves. Based on the foregoing, this paper presents an optimal bidding strategy for GENCOs, derived by using parametric linear programming, and extends the proposed method to consider incomplete information. We show that the proposed algorithm is able to utilize the characteristics of piecewise staircase energy offer curves in contrast to the findings of previous researchers. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:272 / 279
页数:8
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