On Bidding Strategies for Competitive Generators Based on PSO Method under Incomplete Information
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- 英文论文题名：On Bidding Strategies for Competitive Generators Based on PSO Method under Incomplete Information
- 论文作者：Tong Le
- 英文论文作者：Tong Le ; School of Automation ; Beijing Institute of Technology
- 年：2017
- 作者机构：School of Automation,Beijing Institute of Technology;
- 英文论文关键词：Bidding strategy ; Particle swarm ; Profit optimization
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：F426.61;F726
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：643k
- 原文格式：D
- 会议级别：全国
摘要
In power market, it is rather important for Gencos to choose their bids wisely. This paper conducts a research on bidding strategies for Gencos under incomplete information and proposes a bidding strategy model with elimination mechanism. By narrowing the searching space of bids to simplify the model, it avoids the algorithm trapped into a local optimum to some extent. Meanwhile, the elimination mechanism also optimizes the bids in a way which provides a Genco with more assurance under the prerequisite of pursuing maximum profits. The experimental results verify the validity of the proposed model.
In power market, it is rather important for Gencos to choose their bids wisely. This paper conducts a research on bidding strategies for Gencos under incomplete information and proposes a bidding strategy model with elimination mechanism. By narrowing the searching space of bids to simplify the model, it avoids the algorithm trapped into a local optimum to some extent. Meanwhile, the elimination mechanism also optimizes the bids in a way which provides a Genco with more assurance under the prerequisite of pursuing maximum profits. The experimental results verify the validity of the proposed model.
In power market, it is rather important for Gencos to choose their bids wisely. This paper conducts a research on bidding strategies for Gencos under incomplete information and proposes a bidding strategy model with elimination mechanism. By narrowing the searching space of bids to simplify the model, it avoids the algorithm trapped into a local optimum to some extent. Meanwhile, the elimination mechanism also optimizes the bids in a way which provides a Genco with more assurance under the prerequisite of pursuing maximum profits. The experimental results verify the validity of the proposed model.
引文
[1]X.Fang,S.Misra,Smart Grid—The new and improved power grid:a survey.IEEE Communications Surveys&Tutorials,14(4):944-980,2012.
[2]L.Shi,Y.Luo,G.Y.Tu,Bidding strategy of microgrid with consideration of uncertainty for participating in power market,International Journal of Electrical Power&Energy Systems,59(7):1–13,2014.
[3]H.Zhang,F.Gao,Optimal bidding strategies for wind power producers in the day-ahead electricity market.Energies,5(12):4804-23,2012.
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[8]PD.Klempere,MA.Meyer,Supply function equilibria in oligopoly under uncertainty.Econometrica,57(2):1243-77,1989.
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[11]E.Rasmusen,Games and Information:An Introduction to Game Theory.Beijing:China Renmin University Press,2009.
[12]Z.Ji,H.L.Liao,Q.H.Wu,Particle Swarm Optimization and Application.Beijing:Science Press,2009.
[13]AD.Yucekaya,J.Valenzuela,G.Dozier,Strategic bidding in electricity markets using particle swarm optimization.Electric Power Systems Research,79(2):335-345,2009.
[14]S.Soleymani,Bidding strategy of generation companies using PSO combined with SA method in the pay as bid markets.Electrical Power and Energy Systems,33:1272-78,2011.
[15]JW.Pearson,M.Stoll,Regularization-robust preconditioners for time-dependent pde-constrained optimization problems.Siam Journal on Matrix Analysis&Applications,33(4):1126-1152,2012.
[2]L.Shi,Y.Luo,G.Y.Tu,Bidding strategy of microgrid with consideration of uncertainty for participating in power market,International Journal of Electrical Power&Energy Systems,59(7):1–13,2014.
[3]H.Zhang,F.Gao,Optimal bidding strategies for wind power producers in the day-ahead electricity market.Energies,5(12):4804-23,2012.
[4]S.Y.Wu,G.W.Ma,Theory and Methodology for Hydropower Market Competition.Beijing:Electric Power Press,2008.
[5]Elhawary Mohammad E,Electrical power systems.IEEE Press Power Systems Engineering Series,1995.
[6]J.Perloff,Microeconomics:Theory&Applications with Calculus.Newyork:Pearson,2008.
[7]Z.Liu,Y.L.Ren,The bidding mechanism in power market based on signal transmission.Systems Engineering,26(2):35-40,2008.
[8]PD.Klempere,MA.Meyer,Supply function equilibria in oligopoly under uncertainty.Econometrica,57(2):1243-77,1989.
[9]F.S.Wen,A.K.David,Oligopoly electricity market production under incomplete information.IEEE Power Engineering Review,21(4):58-61,2001.
[10]Y.B.Zhang,X.J.Luo,J.Y.Xue,Game solution to competitive bidding of generation companies under incomplete information,Proceedings of the EPSA,15(1):27-32,2003.
[11]E.Rasmusen,Games and Information:An Introduction to Game Theory.Beijing:China Renmin University Press,2009.
[12]Z.Ji,H.L.Liao,Q.H.Wu,Particle Swarm Optimization and Application.Beijing:Science Press,2009.
[13]AD.Yucekaya,J.Valenzuela,G.Dozier,Strategic bidding in electricity markets using particle swarm optimization.Electric Power Systems Research,79(2):335-345,2009.
[14]S.Soleymani,Bidding strategy of generation companies using PSO combined with SA method in the pay as bid markets.Electrical Power and Energy Systems,33:1272-78,2011.
[15]JW.Pearson,M.Stoll,Regularization-robust preconditioners for time-dependent pde-constrained optimization problems.Siam Journal on Matrix Analysis&Applications,33(4):1126-1152,2012.