基于协同进化的两种电力市场出清机制分析
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摘要
基于协同进化算法,对电力市场统一出清机制与一种新的双侧等效PAB(pay as bid)出清机制进行了对比分析。作为一种人工智能算法,近几年来协同进化算法逐渐成为理论分析与工程实践的热点。由于其符合进化博弈理念,并能够充分反映市场动态情况,该算法在电力市场研究中已得到广泛应用。在借鉴PAB出清方式与2016年广东市场出清方式的基础上,提出一种阶梯型报价方式下的双侧等效PAB出清机制,并运用协同进化算法对统一出清机制与双侧等效PAB出清机制进行对比验证。仿真实验结果表明相较于采用统一出清机制,采用双侧等效PAB出清机制的市场更为稳定,且市场出清结果更加贴合市场实际供需曲线交点,能够更好地反映市场的真实情况。
A new bilateral equivalent pay as bid(PAB) clearing mechanism and a unified clearing mechanism in the electricity market are compared and analyzed based on the co-evolutionary algorithm. As a kind of artificial intelligence algorithm, the co-evolutionary algorithm has gradually become the focus of theoretical analysis and engineering practice in recent years. Because it meets the concept of evolutionary game and can fully reflect the market dynamics, this algorithm has been widely used in the research of electricity market. Based on the PAB clearing method and the clearing method used in Guangdong electricity market in 2016, a bilateral equivalent PAB clearing mechanism under the step-wise bidding is proposed. The co-evolutionary algorithm is used to compare and verify the unified clearing mechanism and the bilateral equivalent PAB clearing mechanism. The simulation results show that compared with the unified clearing mechanism, the market using bilateral equivalent PAB clearing mechanism is more stable, and the market clearing results are closer to the intersection of market actual supply and demand curve, thus can reflect the real situation of electricity market better.
A new bilateral equivalent pay as bid(PAB) clearing mechanism and a unified clearing mechanism in the electricity market are compared and analyzed based on the co-evolutionary algorithm. As a kind of artificial intelligence algorithm, the co-evolutionary algorithm has gradually become the focus of theoretical analysis and engineering practice in recent years. Because it meets the concept of evolutionary game and can fully reflect the market dynamics, this algorithm has been widely used in the research of electricity market. Based on the PAB clearing method and the clearing method used in Guangdong electricity market in 2016, a bilateral equivalent PAB clearing mechanism under the step-wise bidding is proposed. The co-evolutionary algorithm is used to compare and verify the unified clearing mechanism and the bilateral equivalent PAB clearing mechanism. The simulation results show that compared with the unified clearing mechanism, the market using bilateral equivalent PAB clearing mechanism is more stable, and the market clearing results are closer to the intersection of market actual supply and demand curve, thus can reflect the real situation of electricity market better.
引文
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[18] 李晓刚,言茂松,谢贤亚.3种定价方法对发电厂商报价策略的诱导机理[J].电力系统自动化,2003,27(5):20-25.LI Xiaogang,YAN Maosong,XIE Xianya.Inducement mechanism of strategic bidding under three typical pricing methods[J].Automation of Electric Power Systems,2003,27(5):20-25.
[19] 杨彦,陈皓勇,张尧,等.基于协同进化算法求解寡头电力市场均衡[J].电力系统自动化,2009,33(18):42-46.YANG Yan,CHEN Haoyong,ZHANG Yao,et al.A coevolutionary approach to calculate equilibrium for oligopolistic electricity market[J].Automation of Electric Power Systems,2009,33(18):42-46.
[20] WANG X,LI Y Z,ZHANG S H.Oligopolistic equilibrium analysis for electricity markets:a nonlinear complementarity approach[J].IEEE Transactions on Power Systems,2004,19(3):1348-1355.
[2] WANG L,SHEN J N,WANG S Y,et al.Advances in co-evolutionary algorithms[J].Control & Decision,2014,30(2):193-202.
[3] DREZEWSKI R,DOROZ K.An agent-based co-evolutionary multi-objective algorithm for portfolio optimization[J].Symmetry,2017,9(9):10.
[4] CHONG S Y,TI,et al.A new framework for analysis of coevolutionary systems-directed graph representation and random walks[J/OL].Evolutionary Computation:1-34[2017-11-20].DOI:10.1162/evco_a_00218.
[5] LU Xiaofen,MENZEL S,TANG Ke,et al.Cooperative co-evolution-based design optimization:a concurrent engineering perspective[J].IEEE Transactions on Evolutionary Computation,2018,22(2):173-188.
[6] 陈皓勇,王锡凡,别朝红,等.协同进化算法及其在电力系统中的应用前景[J].电力系统自动化,2003,27(23):94-100.CHEN Haoyong,WANG Xifan,BIE Zhaohong,et al.Cooperative coevolutionary approaches and their potential applications in power systems[J].Automation of Electric Power Systems,2003,27(23):94-100.
[7] CHEN H Y,WONG K P,NGUYEN D M,et al.Analyzing oligopolistic electricity market using coevolutionary computation[J].IEEE Transactions on Power Systems,2005,21(1):143-152.
[8] CHEN H,WONG K P,CHUNG C Y,et al.A coevolutionary approach to analyzing supply function equilibrium model[J].IEEE Transactions on Power Systems,2006,21(3):1019-1028.
[9] 黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6):13-18.LI Canbing,KANG Chongqing,XIA Qing,et al.Generation rights trade and its mechanism[J].Automation of Electric Power Systems,2003,27(6):13-18.
[10] DOTY K W,MCENTIRE P L.An analysis of electric power brokerage systems[J].IEEE Transactions on Power Apparatus and Systems,1982,101(2):389-395.
[11] 杨强,蔡华祥,严明辉,等.基于激励相容与深度博弈的云南电力市场机制设计及应用[J].电力系统自动化,2017,41(24):27-34.DOI:10.7500/AEPS20170605022.YANG Qiang,CAI Huaxiang,YAN Minghui,et al.Design and application of electricity market mechanism for Yunnan based on theory of incentive compatibility and game in depth[J].Automation of Electric Power Systems,2017,41(24):27-34.DOI:10.7500/AEPS20170605022.
[12] 陈皓勇,付超.统一价格和PAB竞价的实验分析[J].电力系统自动化,2007,31(4):12-17.CHEN Haoyong,FU Chao.Experimental analysis of uniform price and PAB auctions in electricity markets[J].Automation of Electric Power Systems,2007,31(4):12-17.
[13] 李竹,庞博,李国栋,等.欧洲统一电力市场建设及对中国电力市场模式的启示[J].电力系统自动化,2017,41(24):2-9.DOI:10.7500/AEPS20170614004.LI Zhu,PANG Bo,LI Guodong,et al.Development of unified European electricity market and its implications for China[J].Automation of Electric Power Systems,2017,41(24):2-9.DOI:10.7500/AEPS20170614004.
[14] 荆朝霞,朱继松.月度电量集中竞价市场规则的仿真实验分析[J].电力系统自动化,2017,41(24):42-48.DOI:10.7500/AEPS20170615022.JING Zhaoxia,ZHU Jisong.Simulation experiment analysis on market rules for monthly centralized bidding[J].Automation of Electric Power Systems,2017,41(24):42-48.DOI:10.7500/AEPS20170615022.
[15] 李俊,刘俊勇,张力,等.基于电力市场PAB竞价的最优概率随机匹配机制[J].四川大学学报(工程科学版),2011,43(3):150-154.LI Jun,LIU Junyong,ZHANG Li,et al.Random matching mechanism of optimal probability based on PAB auction in electricity market[J].Journal of Sichuan University (Engineering Science Edition),2011,43(3):150-154.
[16] 谢畅,王蓓蓓,赵盛楠,等.基于双层粒子群算法求解电力市场均衡[J].电网技术,2018,42(4):3355-3360.XIE Chang,WANG Beibei,ZHAO Shengnan,et al.Equilibrium solution for electricity market based on bi-level particle swarm optimization algorithm[J].Power System Technology,2018,42(4):3355-3360.
[17] 张文强,魏广民.基于遗传算法的区域电力市场日交易计划研究[J].沈阳工程学院学报(自然科学版),2006,2(4):336-338.ZHANG Wenqiang,WEI Guangmin.Study on daily transaction schedule of regional power market based on genetic algorithm[J].Journal of Shenyang Institute of Engineering (Natural Science),2006,2(4):336-338.
[18] 李晓刚,言茂松,谢贤亚.3种定价方法对发电厂商报价策略的诱导机理[J].电力系统自动化,2003,27(5):20-25.LI Xiaogang,YAN Maosong,XIE Xianya.Inducement mechanism of strategic bidding under three typical pricing methods[J].Automation of Electric Power Systems,2003,27(5):20-25.
[19] 杨彦,陈皓勇,张尧,等.基于协同进化算法求解寡头电力市场均衡[J].电力系统自动化,2009,33(18):42-46.YANG Yan,CHEN Haoyong,ZHANG Yao,et al.A coevolutionary approach to calculate equilibrium for oligopolistic electricity market[J].Automation of Electric Power Systems,2009,33(18):42-46.
[20] WANG X,LI Y Z,ZHANG S H.Oligopolistic equilibrium analysis for electricity markets:a nonlinear complementarity approach[J].IEEE Transactions on Power Systems,2004,19(3):1348-1355.