可再生能源配额制下跨省区电力交易主体最优决策
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摘要
可再生能源配额制(renewables portfolio standards,RPS)的实施将深刻改变电力行业的竞争格局,消费者环保意识增强也将影响绿色电力的需求,两者双重作用将导致跨省区电力交易主体的决策行为发生重要转变。基于此,综合考虑RPS和消费者偏好,探究了跨省区电力交易主体的最优决策,使其在新形势下获得最优利润。首先搭建了RPS下跨省区电力交易市场架构,厘清各交易主体间复杂的电力供需关系;随后考虑消费者偏好因素,采用效用函数刻画消费者决策行为;在此基础上,以利润最大为目标,分别建立了供应链非合作和合作状态下各交易主体最优决策模型,并采用逆向归纳法求解各交易主体最优交易策略。最后通过算例分析验证所提模型和方法的有效性,为各交易主体参与跨省区电力交易决策提供参考。
Implementation of renewable portfolio standards(RPS) will profoundly change the competition pattern of power industry, and enhancement of consumer environmental awareness will affect the demand of green electricity, leading to an important change in the decision-making behavior of the main subjects of trans-provincial and trans-regional power trading. Based on this, considering RPS and consumer preference, the optimal decision of the main subjects of power trading across provinces and regions is explored, so that they can acquire optimal profit under new situations. Firstly, a trans-provincial electricity trading market structure under RPS is established, and the complex power supply and demand relationship between the main trading subjects is clarified. Then, considering the consumer preference, utility function is adopted to describe the decision-making behavior of consumers. On this basis, taking maximum profit as the goal, optimal decision models of each transaction subject under the conditions of non-cooperation and cooperation of supply chain are established respectively, and the optimal trading strategy of each trading subject is solved with reverse inductive method. Finally, validity of the proposed model and method is verified with example analysis, providing reference for each transaction subject to participate in decision making of trans-provincial power trading.
Implementation of renewable portfolio standards(RPS) will profoundly change the competition pattern of power industry, and enhancement of consumer environmental awareness will affect the demand of green electricity, leading to an important change in the decision-making behavior of the main subjects of trans-provincial and trans-regional power trading. Based on this, considering RPS and consumer preference, the optimal decision of the main subjects of power trading across provinces and regions is explored, so that they can acquire optimal profit under new situations. Firstly, a trans-provincial electricity trading market structure under RPS is established, and the complex power supply and demand relationship between the main trading subjects is clarified. Then, considering the consumer preference, utility function is adopted to describe the decision-making behavior of consumers. On this basis, taking maximum profit as the goal, optimal decision models of each transaction subject under the conditions of non-cooperation and cooperation of supply chain are established respectively, and the optimal trading strategy of each trading subject is solved with reverse inductive method. Finally, validity of the proposed model and method is verified with example analysis, providing reference for each transaction subject to participate in decision making of trans-provincial power trading.
引文
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[14]Zhang Q,Wang G,Li Y,et al.Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff[J].Applied Energy,2018(227):426-435.
[15]Ji L,Huang G H,Xie Y L,et al.Explicit cost-risk tradeoff for renewable portfolio standard constrained regional power system expansion:a case study of Guangdong Province,China[J].Energy,2017(131):125-136.
[16]Wang G,Zhang Q,Li Y,et al.Efficient and equitable allocation of renewable portfolio standards targets among China’s provinces[J].Energy Policy,2019(125):170-180.
[17]Wang B,Wei Y M,Yuan X C.Possible design with equity and responsibility in China’s renewable portfolio standards[J].Applied Energy,2018(232):685-694.
[18]Zhao X G,Ren L Z,Zhang Y Z,et al.Evolutionary game analysis on the behavior strategies of power producers in renewable portfolio standard[J].Energy,2018(162):505-516.
[19]李亚龙,刘文颖,谢昶,等.高载能负荷消纳受阻风电的供应链博弈决策方法研究[J].电力系统自动化,2017,41(7):135-143.Li Yalong,Liu Wenying,Xie Chang,et al.Supply chains game based decision-making method of congested wind power consumption for high-energy load[J].Automation of Electric Power Systems,2017,41(7):135-143(in Chinese).
[20]代业明,高岩.具有多类资源多类消费者智能电网实时定价决策[J].系统工程理论与实践,2015,35(9):2315-2323.Dai Yeming,Gao Yan.Real-time pricing decision-making in smart grid with multi-type users and multi-type power sources[J].Systems Engineering Theory&Practice,2015,35(9):2315-2323(in Chinese).
[2]赵新刚,冯天天,杨益晟.可再生能源配额制对我国电源结构的影响机理及效果研究[J].电网技术,2014,38(4):974-979.Zhao Xingang,Feng Tiantian,Yang Yisheng.Impacting mechanism of renewable portfolio standard on China’s power source structure and its effect[J].Power System Technology,2014,38(4):974-979(in Chinese).
[3]任东明.中国可再生能源配额制和实施对策探讨[J].电力系统自动化,2011,35(22):25-28.Ren Dongming.China’s renewable portfolio standard and Implementing countermeasures[J].Automation of Electric Power Systems,2011,35(22):25-28(in Chinese).
[4]钟宇峰,黄民翔,文福拴,等.计及绿色证书交易机制的大消费者直购电市场均衡分析[J].电力自动化设备,2014,34(2):144-150.Zhong Yufeng,Huang Minxiang,Wen Fushuan,et al.Equilibrium analysis of direct electricity purchase with green certificate mechanism[J].Electric Power Automation Equipment,2014,34(2):144-150(in Chinese).
[5]安学娜,张少华,李雪.考虑绿色证书交易的寡头电力市场均衡分析[J].电力系统自动化,2017,41(9):84-89.An Xuena,Zhang Shaohua,Li Xue.Equilibrium analysis of oligopolistic electricity markets considering tradable green certificates[J].Automation of Electric Power Systems,2017,41(9):84-89(in Chinese).
[6]赵新刚,梁吉,任领志,等.能源低碳转型的顶层制度设计:可再生能源配额制[J].电网技术,2018,42(4):1164-1169.Zhao Xingang,Liang Ji,Ren Lingzhi,et al.Top-level institutional design for the energy low-carbon transition:renewable portfolio standards[J].Power System Technology,2018,42(4):1164-1169(in Chinese).
[7]冯奕,刘秋华,王帅.中国售电侧可再生能源配额制设计探索[J].电力系统自动化,2017,41(24):137-158.Feng Yi,Liu Qiuhua,Wang Shuai.Design and exploration of renewable portfolio standard in power sales side in China[J].Automation of Electric Power Systems,2017,41(24):137-158(in Chinese).
[8]马子明,钟海旺,谭振飞,等.以配额制激励可再生能源的需求与供给[J].电力系统自动化,2017,41(24):90-96.Ma Ziming,Zhong Haiwang,Tan Zhenfei,et al.Incenting demand and supply of renewable energy with renewable portfolio standard:mechanism design of national renewable energy market[J].Automation of Electric Power Systems,2017,41(24):90-96(in Chinese).
[9]Zhang Y Z,Zhao X G,Ren L Z,et al.The development of the renewable energy power industry under feed-in tariff and renewable portfolio standard:a case study of China’s wind power industry[J].Journal of Cleaner Production,2017(168):1262-1276.
[10]Zhang Y Z,Zhao X G,Ren L Z,et al.The development of China’s biomass power industry under feed-in tariff and renewable portfolio standard:a system dynamics analysis[J].Energy,2017(139):947-961.
[11]赵盛楠,王蓓蓓,李杨,等.基于系统动力学的分布式可再生能源激励机制分析[J].电力系统自动化,2017,41(24):97-104.Zhao Shengnan,Wang Beibei,Li Yang,et al.System dynamics based analysis on incentive mechanism of distributed renewable energy resource[J].Automation of Electric Power Systems,2017,41(24):97-104(in Chinese).
[12]余顺坤,毕平平,杨文茵,等.基于配额制的可再生能源动态发展系统动力学研究[J].中国电机工程学报,2018,38(9):2599-2609.Yu Shunkun,Bi Pingping,Yang Wenyin,et al.Dynamic development system dynamics of renewable energy considering renewable portfolio standard[J].Proceedings of the CSEE,2018,38(9):2599-2609(in Chinese).
[13]Sun P,Nie P Y.A comparative study of feed-in tariff and renewable portfolio standard policy in renewable energy industry[J].Renewable Energy,2015(74):255-262.
[14]Zhang Q,Wang G,Li Y,et al.Substitution effect of renewable portfolio standards and renewable energy certificate trading for feed-in tariff[J].Applied Energy,2018(227):426-435.
[15]Ji L,Huang G H,Xie Y L,et al.Explicit cost-risk tradeoff for renewable portfolio standard constrained regional power system expansion:a case study of Guangdong Province,China[J].Energy,2017(131):125-136.
[16]Wang G,Zhang Q,Li Y,et al.Efficient and equitable allocation of renewable portfolio standards targets among China’s provinces[J].Energy Policy,2019(125):170-180.
[17]Wang B,Wei Y M,Yuan X C.Possible design with equity and responsibility in China’s renewable portfolio standards[J].Applied Energy,2018(232):685-694.
[18]Zhao X G,Ren L Z,Zhang Y Z,et al.Evolutionary game analysis on the behavior strategies of power producers in renewable portfolio standard[J].Energy,2018(162):505-516.
[19]李亚龙,刘文颖,谢昶,等.高载能负荷消纳受阻风电的供应链博弈决策方法研究[J].电力系统自动化,2017,41(7):135-143.Li Yalong,Liu Wenying,Xie Chang,et al.Supply chains game based decision-making method of congested wind power consumption for high-energy load[J].Automation of Electric Power Systems,2017,41(7):135-143(in Chinese).
[20]代业明,高岩.具有多类资源多类消费者智能电网实时定价决策[J].系统工程理论与实践,2015,35(9):2315-2323.Dai Yeming,Gao Yan.Real-time pricing decision-making in smart grid with multi-type users and multi-type power sources[J].Systems Engineering Theory&Practice,2015,35(9):2315-2323(in Chinese).