新能源并网环境下发电侧微分演化博弈竞价策略
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摘要
智能电网中新能源的大量接入及其固有的不确定性,导致电力市场对常规电能需求裕度降低并存在大幅波动性,从而对发电侧竞价策略的可靠性提出了更高的要求。将演化博弈理论引入到发电商的竞价策略中,以便在不确定性环境中可通过动态演化获得稳定的最优竞价策略;鉴于可再生能源出力的不确定性导致演化博弈复制动态方程难以求解,提出通过将演化博弈思想与复合微分进化算法有机融合,构造复合微分演化博弈算法实现发电商竞价发电的动态演化博弈过程;最后通过与常规竞价策略进行对比分析,验证了所提出的微分演化博弈竞价策略的优越性。
Large number of renewable energy resources integrated in smart grid and its inherent uncertainty lead to decrease and high volatility of the demand margin of conventional energy resources in electricity market, raising higher requirements of reliability for the bidding strategy for generation side. In this paper, evolutionary game theory is applied to the bidding strategy of generators, so that a stable optimal bidding strategy can be obtained through dynamic evolution in uncertain environment. Because the uncertainty of renewable energy output can lead to the replicating dynamic equation of evolutionary game difficult to solve, a compound differential evolution game algorithm combining evolutionary game theory with composite differential evolution is proposed to achieve dynamic evolution game based generating and bidding of generators. Finally, by comparing with conventional bidding strategies, superiority of the proposed differential evolution game strategy is verified.
Large number of renewable energy resources integrated in smart grid and its inherent uncertainty lead to decrease and high volatility of the demand margin of conventional energy resources in electricity market, raising higher requirements of reliability for the bidding strategy for generation side. In this paper, evolutionary game theory is applied to the bidding strategy of generators, so that a stable optimal bidding strategy can be obtained through dynamic evolution in uncertain environment. Because the uncertainty of renewable energy output can lead to the replicating dynamic equation of evolutionary game difficult to solve, a compound differential evolution game algorithm combining evolutionary game theory with composite differential evolution is proposed to achieve dynamic evolution game based generating and bidding of generators. Finally, by comparing with conventional bidding strategies, superiority of the proposed differential evolution game strategy is verified.
引文
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[15]刘连光,刘鸿熹,刘自发,等.新能源接入下风火网三方非对称进化博弈分析[J].中国科学:技术科学,2015,45(12):1297.Liu Lianguang,Liu Hongxi,Liu Zifa,et al.Analysis of tripartite asymmetric evolutionary game among wind power enterprises,thermal power enterprises and power grid enterprises under new energy resources integrated[J].Scientia Sinica,2015,45(12):1297(in Chinese).
[16]孙惠娟,彭春华,余廷芳.配电网三相平衡优化重构策略[J].电网技术,2014,38(3):789-794.Sun Huijuan,Peng Chunhua,Yu Tingfang.A three-phase equilibrium reconfiguration strategy for distribution network[J].Power System Technology,2014,38(3):789-794(in Chinese).
[2]宋巍,王佳伟,赵海波,等.考虑需求响应交易市场的虚拟电厂多阶段竞价策略研究[J].电力系统保护与控制,2017,45(19):35-45.Song Wei,Wang Jiawei,Zhao Haibo,et al.Research on multi-stage bidding strategy of virtual power plant considering demand response market[J].Power System Protection and Control,2017,45(19):35-45(in Chinese).
[3]刘连光,潘明明,田世明,等.考虑源网荷多元主体的售电竞争非合作博弈方法[J].中国电机工程学报,2017,37(6):1618-1625.Liu Lianguang,Pan Mingming,Tian Shiming,et al.A noncooperative game analysis of an competitive electricity retail considering multiple subjects of source-grid-load[J].Proceedings of the Chinese Society of Electrical Engineering,2017,37(6):1618-1625(in Chinese).
[4]Gil H A,Lin J.Wind power and electricity prices at the PJM market[J].IEEE Transactions on Power Systems,2013,28(4):3945-3953.
[5]Soares T,Santos G,Pinto T,et al.Analysis of strategic wind power participation in energy market using MASCEM simulator[C]//International Conference on Intelligent System Application To Power Systems.IEEE,2015:1-6.
[6]Vilim M,Botterud A.Wind power bidding in electricity markets with high wind penetration[J].Applied Energy,2014,118(118):141-155.
[7]钱锟.智能电网中发电侧演化博弈竞价策略研究[D].南昌:华东交通大学,2018.
[8]孙云涛,宋依群,姚良忠,等.售电市场环境下电力用户选择售电公司行为研究[J].电网技术,2018,42(4):1124-1131.Sun Yuntao,Song Yiqun,Yao Liangzhong,et al.Study on power consumers’choices of electricity retailers in the electric selling market[J].Power System Technology,2018,42(4):1124-1131(in Chinese).
[9]王晓天,薛惠锋,张强.可再生能源发电并网利益协调演化博弈分析[J].系统工程,2012(4):94-99.Wang Xiaotian,Xue Huifeng,Zhang Qiang.Evolutionary game analysis on the interest coordination of grid-connected renewable energy power generation[J].Systems Engineering,2012(4):94-99(in Chinese).
[10]武英利,张彬,闫龙,等.基于演化博弈的海上风电投资策略选择及模型研究[J].电网技术,2014,38(11):2978-2985.Wu Yingli,Zhang Bin,Yan Long,et al.Research and modeling of evolutionary game based selection of investment strategies for offshore wind farm[J].Power System Technology,2014,38(11):2978-2985(in Chinese).
[11]Peng C,Sun H,Guo J,et al.Multi-objective optimal strategy for generating and bidding in the power market[J].Energy Conversion and Management,2012,57(1):13-22.
[12]孙国强,周亦洲,卫志农,等.基于混合随机规划/信息间隙决策理论的虚拟电厂调度优化模型[J].电力自动化设备,2017,37(10):112-118.Sun Guoqiang,Zhou Yizhou,Wei Zhilong,et al.Optimization model of virtual power plant based on hybrid stochastic programming and information gap decision theory[J].Electric Power Automation Equipment,2017,37(10):112-118(in Chinese).
[13]孙惠娟,刘君,彭春华.基于分类概率综合多场景分析的分布式电源多目标规划[J].电力自动化设备,2018,38(12):39-45.Sun Huijuan,Liu Jun,Peng Chunhua.Multi-objective DG planning based on classified probability integration multi-scenario analysis[J].Electric Power Automation Equipment,2018,38(12):39-45(in Chinese).
[14]达庆利,张骥骧.有限理性条件下进化博弈均衡的稳定性分析[J].系统工程理论方法应用,2006,15(3):279-284.Da Qingli,Zhang Jixiang.Stability of evolutionary equilibrium under bounded rationality[J].Journal of Systems&Management,2006,15(3):279-284(in Chinese).
[15]刘连光,刘鸿熹,刘自发,等.新能源接入下风火网三方非对称进化博弈分析[J].中国科学:技术科学,2015,45(12):1297.Liu Lianguang,Liu Hongxi,Liu Zifa,et al.Analysis of tripartite asymmetric evolutionary game among wind power enterprises,thermal power enterprises and power grid enterprises under new energy resources integrated[J].Scientia Sinica,2015,45(12):1297(in Chinese).
[16]孙惠娟,彭春华,余廷芳.配电网三相平衡优化重构策略[J].电网技术,2014,38(3):789-794.Sun Huijuan,Peng Chunhua,Yu Tingfang.A three-phase equilibrium reconfiguration strategy for distribution network[J].Power System Technology,2014,38(3):789-794(in Chinese).