基于不同行为决策的电力市场演化博弈及其混沌控制
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摘要
随着电力体制改革的深入,市场逐步建立了电力市场运行规则和政府监管体系。但对不完善的电力市场来说,电力市场动态演化研究显得更为紧迫和必要。本文在总结电力市场动态演化和混沌控制研究成果的基础上,考虑输电网络约束,建立了基于不同行为决策的电力市场演化博弈模型。分析了电力市场的均衡和周期以及混沌状态的演化机理;针对市场处于周期或混沌状态,提出了反馈控制方法,实现了电力市场从周期或混沌态到Nash均衡态的控制,极大地提高了发电商自身的竞争优势和系统的稳定性。从而使市场的经济效益得以提高。
为了准确模拟发电商报价的行为决策,在考虑输电网的约束情况下,本文提出了基于不同行为决策的电力市场动态模型,在数学上表征为内嵌优化问题的差分动态系统。该模型的优点:
1.发电商考虑了两种行为决策:有限理性行为决策和最优反应行为决策。每一个发电商对行为决策的选择取决于自身利润与所有发电商平均利润的比值,由该比值决定了发电商采取的行为决策在所有发电商采取行为决策中的比例。这一比例作为发电商对行为决策选取的概率。
2.建立了市场清算优化模型。通过独立系统调度员ISO的统一市场清算,以确保市场交易满足输电网络固有物理约束的要求。分析了基于不同行为决策电力市场动态演化,同时对动态模型的Nash均衡点及其稳定性进行了定性分析。从中显示出在不同的市场参数下,市场参数对市场稳定性的影响。本文通过平均利润作为经济性评价指标,分析比较了基于不同行为决策的电力市场动态演化处于均衡和周期以及混沌动态行为上的经济表现。当市场处于Nash均衡时经济表现最佳。
提出了电力市场时滞反馈控制法。选取当期与前期报价行为决策之差作为反馈控制信号,通过调整系统状态方式来实现市场的混沌控制。将动态模型本身的报价行为决策输出信号通过时间延迟后再反馈到混沌系统作为控制信号。当市场动态演化行为处于混沌时,通过调节行为决策反馈控制信号的大小实现对市场周期或混沌行为的控制,使发电商经济利润达到原有的均衡态。从而使市场的整体经济效益得到提高。
通过编制MATLAB程序,实现3节点和14节点模型的动态演化和混沌控制,其计算结果表明了所提模型和算法的有效性和可行性。
The market has gradually established the power market operation rules and government regulatory system along with the further reform of electricity system. However, the research on the dynamic evolution of the power market based on heterogeneous behavioral decision-makings is much more urgent and necessary for the imperfect power market. Based on the summarize of the research results on dynamic evolution and chaos control of the power market, this paper would establish the power market evolutionary game model, which considers the transmission network constraints and is based on the heterogeneous behavioral decision-makings of two-dimensional discrete dynamic systems. This paper has analyzed the equilibrium and cycle of the power market as well as the evolution mechanism of its chaotic state. For the market is under the state of periodic or chaotic, the paper put up the feedback control method to realize the control of the power market from a cycle or chaotic state to a Nash equilibrium state, and improving generators own competitive advantage and system stability. So the market efficiency is improved.
In order to accurately simulate the dynamic behavioral decision-making of electricity suppliers’quotation and considering the constraints of transmission network, this thesis will propose the power market model based on the heterogeneous behavioral decision-makings of two-dimensional discrete dynamic systems, which considers the transmission network constraints and is embedded in the mathematical optimization problem characterized by differential dynamic system. The model has two advantages:
The first one is that: generators considered two behavioral decision-making types: the bounded rationality behavioral decision-making and the best-reply behavioral decision-making. Each generator probability of behavioral decision-making is depending on the profits of generator themselves and average profit of all generation companies comparison, which determines the increase and decrease in proportion of the one generator behavior in all the generators decision-making behavior. The proportion is the selection probability of the behavior of power suppliers.
And the last one is that the market will establish clearing optimization model. A unified market-clearing process of independent system dispatcher by ISO could help market transactions satisfy the demand of physical inherent constraints in the transmission network.
This paper analyzes not only the dynamic evolution of power market based on heterogeneous behavioral decision-makings, but also the Nash equilibrium and its stability. This shows that the market parameters influence the stability of market, in the different parameters of the market. The paper adopts the average profit as economic evaluation indicators, and analyses dynamic evolution of the power market based on heterogeneous behavioral decision-makings in the Nash Equilibrium, and the dynamics of the economic performance of the economy in the cycle and chaos. When the market is in Nash equilibrium the economic performance is the best.
The time-delayed feedback control is proposed. The current and previous bidding behavior of the difference between decision-making is selected as a feedback control signal, and the control of the market chaos has been achieved by adjust the system state approach. The system bidding decision-making output signal of dynamic model is delayed and set back to the chaotic system as the control signal. When the behavior of dynamic evolution in the market reached chaotic, the control of the periodic and chaotic behaviors of the market is achieved by adjusting the size of the behavioral decision feedback control signal, and the economic profit, the cycle and the chaotic state and the behavior of the uncertainty of the decision-making will reach the original equilibrium state. In that case, the overall economic benefits are improved.
The dynamic evolution and chaos control of three-node and fourteen-node model are achieved by the program of MATLAB. So the validity and feasibility of this proposed model and algorithm are testified by calculated results.
为了准确模拟发电商报价的行为决策,在考虑输电网的约束情况下,本文提出了基于不同行为决策的电力市场动态模型,在数学上表征为内嵌优化问题的差分动态系统。该模型的优点:
1.发电商考虑了两种行为决策:有限理性行为决策和最优反应行为决策。每一个发电商对行为决策的选择取决于自身利润与所有发电商平均利润的比值,由该比值决定了发电商采取的行为决策在所有发电商采取行为决策中的比例。这一比例作为发电商对行为决策选取的概率。
2.建立了市场清算优化模型。通过独立系统调度员ISO的统一市场清算,以确保市场交易满足输电网络固有物理约束的要求。分析了基于不同行为决策电力市场动态演化,同时对动态模型的Nash均衡点及其稳定性进行了定性分析。从中显示出在不同的市场参数下,市场参数对市场稳定性的影响。本文通过平均利润作为经济性评价指标,分析比较了基于不同行为决策的电力市场动态演化处于均衡和周期以及混沌动态行为上的经济表现。当市场处于Nash均衡时经济表现最佳。
提出了电力市场时滞反馈控制法。选取当期与前期报价行为决策之差作为反馈控制信号,通过调整系统状态方式来实现市场的混沌控制。将动态模型本身的报价行为决策输出信号通过时间延迟后再反馈到混沌系统作为控制信号。当市场动态演化行为处于混沌时,通过调节行为决策反馈控制信号的大小实现对市场周期或混沌行为的控制,使发电商经济利润达到原有的均衡态。从而使市场的整体经济效益得到提高。
通过编制MATLAB程序,实现3节点和14节点模型的动态演化和混沌控制,其计算结果表明了所提模型和算法的有效性和可行性。
The market has gradually established the power market operation rules and government regulatory system along with the further reform of electricity system. However, the research on the dynamic evolution of the power market based on heterogeneous behavioral decision-makings is much more urgent and necessary for the imperfect power market. Based on the summarize of the research results on dynamic evolution and chaos control of the power market, this paper would establish the power market evolutionary game model, which considers the transmission network constraints and is based on the heterogeneous behavioral decision-makings of two-dimensional discrete dynamic systems. This paper has analyzed the equilibrium and cycle of the power market as well as the evolution mechanism of its chaotic state. For the market is under the state of periodic or chaotic, the paper put up the feedback control method to realize the control of the power market from a cycle or chaotic state to a Nash equilibrium state, and improving generators own competitive advantage and system stability. So the market efficiency is improved.
In order to accurately simulate the dynamic behavioral decision-making of electricity suppliers’quotation and considering the constraints of transmission network, this thesis will propose the power market model based on the heterogeneous behavioral decision-makings of two-dimensional discrete dynamic systems, which considers the transmission network constraints and is embedded in the mathematical optimization problem characterized by differential dynamic system. The model has two advantages:
The first one is that: generators considered two behavioral decision-making types: the bounded rationality behavioral decision-making and the best-reply behavioral decision-making. Each generator probability of behavioral decision-making is depending on the profits of generator themselves and average profit of all generation companies comparison, which determines the increase and decrease in proportion of the one generator behavior in all the generators decision-making behavior. The proportion is the selection probability of the behavior of power suppliers.
And the last one is that the market will establish clearing optimization model. A unified market-clearing process of independent system dispatcher by ISO could help market transactions satisfy the demand of physical inherent constraints in the transmission network.
This paper analyzes not only the dynamic evolution of power market based on heterogeneous behavioral decision-makings, but also the Nash equilibrium and its stability. This shows that the market parameters influence the stability of market, in the different parameters of the market. The paper adopts the average profit as economic evaluation indicators, and analyses dynamic evolution of the power market based on heterogeneous behavioral decision-makings in the Nash Equilibrium, and the dynamics of the economic performance of the economy in the cycle and chaos. When the market is in Nash equilibrium the economic performance is the best.
The time-delayed feedback control is proposed. The current and previous bidding behavior of the difference between decision-making is selected as a feedback control signal, and the control of the market chaos has been achieved by adjust the system state approach. The system bidding decision-making output signal of dynamic model is delayed and set back to the chaotic system as the control signal. When the behavior of dynamic evolution in the market reached chaotic, the control of the periodic and chaotic behaviors of the market is achieved by adjusting the size of the behavioral decision feedback control signal, and the economic profit, the cycle and the chaotic state and the behavior of the uncertainty of the decision-making will reach the original equilibrium state. In that case, the overall economic benefits are improved.
The dynamic evolution and chaos control of three-node and fourteen-node model are achieved by the program of MATLAB. So the validity and feasibility of this proposed model and algorithm are testified by calculated results.
引文
[1]王锡凡,王秀丽,陈皓勇.电力市场基础.西安:西安交通大学出版社,2003,116-117
[2]侯云鹤,吴复立.考虑周期特性的电力市场稳定性分析.中国电机工程学报, 2006,26(24):13-15
[3]张新华,赖明勇.基于演化博弈的电力竞价市场均衡分析.管理工程学报,2008,22(2):145-147
[4] Alvarado F L. The Stability of Power System Markets. IEEE Transactions on Power Apparatus and Systems, 1999, 14(2): 505-511
[5] Alvarado F L, Meng J, De Marco C L. Stability analysis of interconnected power systems coupled with market dynamics. IEEE Transactions on Power Systems, 2001, 16(4): 605-701
[6]杨志辉,刘有非,唐云.电力市场稳定性分析.中国电机工程学报,2005,25(2):1-5
[7]汤玉东,吴军基,邹云.电力市场的稳定性研究.电力系统自动化,2001,25(4):11-16
[8] Maiorano A, Song Y H, Trovato M. Dynamics of non-collusive oligopolistic electricity markets. IEEE Power Engineering Society Winter Meeting, Singapore, 2000, 2: 45-46
[9]张宇波,罗先觉,薛钧义.非线性市场需求下机组优化出力的自适应动态古诺模型.中国电机工程学报,2003,23(11):86-87
[10]高洁,盛昭瀚.发电侧电力市场竞价策略的演化博弈分析.管理工程学报,2004,18(3):91-95
[11]薛禹胜.电力市场稳定性与电力系统稳定性的相影响.电力系统自动化,2002,26(21):1-6
[12]尹逊和,蔡晓,赵栋.工程混沌及混沌应用的研究现状与展望.系统工程与电子技术,2001,23(12):71-76
[13]李煜,盛昭瀚,姚洪兴.离散Bala混沌价格调整过程的控制.系统工程学报,2004,19(3):223-228
[14] Yang W G, Sheble G B. Modeling generation company decisions and electric market dynamics as discrete systems. Proceedings of the IEEE Power Engineering Society Summer Meeting. Chicago, 2002, 1385-1391
[15]杨洪明,赖明勇.考虑输电网约束的电力市场有限理性古诺博弈的动态演化研究.中国电机工程学报,2005,25(23):71-79
[16]杨洪明,童小娇,赖明勇.基于光滑非线性互补函数的电力市场动态研究.电网技术,2006,22(30):42-48
[17]童小娇,王洁,杨洪明,等.计及输电线路和投标量界约束的电力市场动态投标模型及分析.系统工程理论与实践,2008,(5):105-115
[18]童小娇,王洁,杨洪明.计及输电网约束的电力市场动态集团投标分析.长沙理工大学学报(自然科学版),2007,1(5):57-63
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[21] Guo M S, Leang S, Chen G. Ordering chaos in chua’s circuit: a sampled data feedback and digital-data feedback and digital data redesign approach. International Journal of Bifurcation and Chaos, 2000, 10(9): 2221-2231
[22]姚洪兴,盛昭翰.经济混沌模型中一种改进的反馈控制方法.系统工程学报,2002,6(17):507-511
[23]陈凤祥.混沌控制与同步的鲁棒控制器研究:[博士论文].上海:上海交通大学,2008,1
[24] Chen G, Dong X. On feedback control of chaotic dynamic system. International Journal of Bifurcation and Chaos, 1992, 2(2): 407-411
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[26]卢俊国,魏荣,汪小帆,等.连续混沌系统控制与同步的自适应方法.控制与决策,2002,17(1):114-116
[27]裴文江,黄俊.自适应延迟反馈控制混沌.控制理论与应用,1999,16(2):298-300
[28]陈小山,张伟江.基于变结构的混沌控制.上海交通大学学报,1999,33(5):581-583
[29]徐红兵,吕炳朝.一类非线性动力学系统的变结构混沌控制.电子科技大学学报,1999,28(3):283-285
[30]蔡朝洪,徐振源,须文波.凹槽滤波反馈控制混沌系统.控制理论与应用,2002,19(4):549-554
[31]王忠勇,蔡远利.混沌系统的神经网络预测控制.控制与决策,2000,15(1):55-58
[32]张宇波,罗先觉,薛钧义.非线性市场需求下机组优化出力的自适应动态古诺模型.中国电机工程学报,2003,23(11):80-84
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[2]侯云鹤,吴复立.考虑周期特性的电力市场稳定性分析.中国电机工程学报, 2006,26(24):13-15
[3]张新华,赖明勇.基于演化博弈的电力竞价市场均衡分析.管理工程学报,2008,22(2):145-147
[4] Alvarado F L. The Stability of Power System Markets. IEEE Transactions on Power Apparatus and Systems, 1999, 14(2): 505-511
[5] Alvarado F L, Meng J, De Marco C L. Stability analysis of interconnected power systems coupled with market dynamics. IEEE Transactions on Power Systems, 2001, 16(4): 605-701
[6]杨志辉,刘有非,唐云.电力市场稳定性分析.中国电机工程学报,2005,25(2):1-5
[7]汤玉东,吴军基,邹云.电力市场的稳定性研究.电力系统自动化,2001,25(4):11-16
[8] Maiorano A, Song Y H, Trovato M. Dynamics of non-collusive oligopolistic electricity markets. IEEE Power Engineering Society Winter Meeting, Singapore, 2000, 2: 45-46
[9]张宇波,罗先觉,薛钧义.非线性市场需求下机组优化出力的自适应动态古诺模型.中国电机工程学报,2003,23(11):86-87
[10]高洁,盛昭瀚.发电侧电力市场竞价策略的演化博弈分析.管理工程学报,2004,18(3):91-95
[11]薛禹胜.电力市场稳定性与电力系统稳定性的相影响.电力系统自动化,2002,26(21):1-6
[12]尹逊和,蔡晓,赵栋.工程混沌及混沌应用的研究现状与展望.系统工程与电子技术,2001,23(12):71-76
[13]李煜,盛昭瀚,姚洪兴.离散Bala混沌价格调整过程的控制.系统工程学报,2004,19(3):223-228
[14] Yang W G, Sheble G B. Modeling generation company decisions and electric market dynamics as discrete systems. Proceedings of the IEEE Power Engineering Society Summer Meeting. Chicago, 2002, 1385-1391
[15]杨洪明,赖明勇.考虑输电网约束的电力市场有限理性古诺博弈的动态演化研究.中国电机工程学报,2005,25(23):71-79
[16]杨洪明,童小娇,赖明勇.基于光滑非线性互补函数的电力市场动态研究.电网技术,2006,22(30):42-48
[17]童小娇,王洁,杨洪明,等.计及输电线路和投标量界约束的电力市场动态投标模型及分析.系统工程理论与实践,2008,(5):105-115
[18]童小娇,王洁,杨洪明.计及输电网约束的电力市场动态集团投标分析.长沙理工大学学报(自然科学版),2007,1(5):57-63
[19] Sigh H, Hao S, Papalexopoulos A. Ransmission congestion management in competitive electricity markets. IEEE Transactions on Power System, 1998, 3(2): 672-680.
[20]李煜,盛昭翰,陈国华.混沌经济系统的控制优化.中国管理科学,2003,11(3):66-71
[21] Guo M S, Leang S, Chen G. Ordering chaos in chua’s circuit: a sampled data feedback and digital-data feedback and digital data redesign approach. International Journal of Bifurcation and Chaos, 2000, 10(9): 2221-2231
[22]姚洪兴,盛昭翰.经济混沌模型中一种改进的反馈控制方法.系统工程学报,2002,6(17):507-511
[23]陈凤祥.混沌控制与同步的鲁棒控制器研究:[博士论文].上海:上海交通大学,2008,1
[24] Chen G, Dong X. On feedback control of chaotic dynamic system. International Journal of Bifurcation and Chaos, 1992, 2(2): 407-411
[25] Chen G, Dong X. On feedback control of chaotic continuous-time systems. IEEE Transactions on Circuits and System, 1993, 40(9): 591-600
[26]卢俊国,魏荣,汪小帆,等.连续混沌系统控制与同步的自适应方法.控制与决策,2002,17(1):114-116
[27]裴文江,黄俊.自适应延迟反馈控制混沌.控制理论与应用,1999,16(2):298-300
[28]陈小山,张伟江.基于变结构的混沌控制.上海交通大学学报,1999,33(5):581-583
[29]徐红兵,吕炳朝.一类非线性动力学系统的变结构混沌控制.电子科技大学学报,1999,28(3):283-285
[30]蔡朝洪,徐振源,须文波.凹槽滤波反馈控制混沌系统.控制理论与应用,2002,19(4):549-554
[31]王忠勇,蔡远利.混沌系统的神经网络预测控制.控制与决策,2000,15(1):55-58
[32]张宇波,罗先觉,薛钧义.非线性市场需求下机组优化出力的自适应动态古诺模型.中国电机工程学报,2003,23(11):80-84
[33]谢识予.经济博弈论.上海:复旦大学出版社,2002,252-253
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