含电动汽车和电转气的园区能源互联网能源定价与管理
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摘要
能源互联网的发展有助于实现多能系统间的互补、协调和优化,获得经济与环境效益。而电动汽车向电网反向送电(V2G)和电转气(P2G)技术的不断发展,对能源互联网中多类型能源的能量管理提出了新的要求。在此背景下,以含电动汽车和P2G设备的园区能源互联网为研究对象,首先提出包含能源供应商、园区运营商和用户代理的互动框架。接着,建立了园区运营商和用户代理理性追求自身利益最大化的主从博弈模型。其中,园区运营商(领导者)确定从能源供应商处的购能策略、所拥有设备的运行状态,并制定向/从用户代理出售/购买的多种能源价格,而用户代理(追随者)则根据动态能源价格信号调整用户用能策略。之后,应用KKT(Karush-Kuhn-Tucker)条件、对偶定理和线性松弛技术,将主从博弈模型转化为混合整数线性规划问题,并利用商业化求解器YALMIP/GUROBI求解。最后,以某工业园区为例对所提出的模型和方法进行说明,并着重分析V2G和P2G技术在提高系统运行的整体经济性、消纳风电能力等方面的效果。
Significant benefits in economics and environment could be attained from the development of Energy Internets,with the objectives of implementing complementarity,coordination and optimization among multi-energy systems.Recent developments in some key technologies,such as vehicle to grid(V2 G)and power to gas(P2 G),impose new requirements for the energy management of multiple kinds of energy in an energy internet.Given this background,apark-level Energy Internet(PEI)with integrated electric vehicles(EVs)and P2 Gdevices is addressed.First,an interactive framework of the PEI is proposed,including the energy suppliers,park operator and user agent.A Stackelberg game model is then established,in which the park operator and user agent rationally seek optimal strategies to maximize their own benefits.The park operator(the leader)determines the optimal energy procurement portfolio from the energy suppliers,the optimal operation strategy of owned devices and sets prices for various kinds of energy for the user agent while the user agent(the follower)adjusts the energy consumption profile with respect to dynamic energy price signals.Next,the Stackelberg game model is transformed into a mixed integer linear programming problem through jointly employing the KKT(Karush-Kuhn-Tucker)optimality condition,the duality theory and the relaxation technology,and then solved with the well-developed YALMIP/GUROBI commercial solver.Finally,a sample industrial park is employed to demonstrate the presented model and solution method.The performances of V2 G and P2 G in promoting the overall economic benefits,as well as enhancing the capability of accommodating wind power,are also analyzed.
Significant benefits in economics and environment could be attained from the development of Energy Internets,with the objectives of implementing complementarity,coordination and optimization among multi-energy systems.Recent developments in some key technologies,such as vehicle to grid(V2 G)and power to gas(P2 G),impose new requirements for the energy management of multiple kinds of energy in an energy internet.Given this background,apark-level Energy Internet(PEI)with integrated electric vehicles(EVs)and P2 Gdevices is addressed.First,an interactive framework of the PEI is proposed,including the energy suppliers,park operator and user agent.A Stackelberg game model is then established,in which the park operator and user agent rationally seek optimal strategies to maximize their own benefits.The park operator(the leader)determines the optimal energy procurement portfolio from the energy suppliers,the optimal operation strategy of owned devices and sets prices for various kinds of energy for the user agent while the user agent(the follower)adjusts the energy consumption profile with respect to dynamic energy price signals.Next,the Stackelberg game model is transformed into a mixed integer linear programming problem through jointly employing the KKT(Karush-Kuhn-Tucker)optimality condition,the duality theory and the relaxation technology,and then solved with the well-developed YALMIP/GUROBI commercial solver.Finally,a sample industrial park is employed to demonstrate the presented model and solution method.The performances of V2 G and P2 G in promoting the overall economic benefits,as well as enhancing the capability of accommodating wind power,are also analyzed.
引文
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[11]李杨,刘伟佳,赵俊华,等.含电转气的电-气-热系统协同调度与消纳风电效益分析[J].电网技术,2016,40(12):3680-3688.LI Yang,LIU Weijia,ZHAO Junhua,et al.Optimal dispatch of combined electricity-gas-heat energy systems with power-togas devices and benefit analysis of wind power accommodation[J].Power System Technology,2016,40(12):3680-3688.
[12]SOARES J,CANIZES B,GHAZVINI M A F,et al.Twostage stochastic model using Benders’decomposition for largescale energy resources management in smart grids[J].IEEE Transactions on Industry Applications,2017,53(6):5905-5914.
[13]LIU N,YU X H,WANG C,et al.Energy sharing management for microgrids with PV prosumers:a Stackelberg game approach[J].IEEE Transactions on Industrial Informatics,2017,13(3):1088-1098.
[14]魏韡,陈玥,刘锋,等.基于主从博弈的智能小区代理商定价策略及电动汽车充电管理[J].电网技术,2015,39(4):939-945.WEI Wei,CHEN Yue,LIU Feng,et al.Stackelberg game based retailer pricing scheme and EV charging management in smart residential area[J].Power System Technology,2015,39(4):939-945.
[15]YU M M,HONG S H.A real-time demand-response algorithm for smart grids:a Stackelberg game approach[J].IEEE Transactions on Smart Grid,2017,7(2):879-888.
[16]DAMAVANDI M Y,NEYESTANI N,CHICCO G,et al.Aggregation of distributed energy resources under the concept of multi-energy players in local energy system[J].IEEE Transactions on Sustainable Energy,2017,8(4):1679-1693.
[17]马丽,刘念,张建华,等.基于主从博弈策略的社区能源互联网分布式能量管理[J].电网技术,2016,40(12):3655-3661.MA Li,LIU Nian,ZHANG Jianhua,et al.Distributed energy management of community energy internet based on leaderfollowers game[J].Power System Technology,2016,40(12):3655-3661.
[18]WEI W,LIU F,MEI S W.Energy pricing and dispatch for smart grid retailers under demand response and market price uncertainty[J].IEEE Transactions on Smart Grid,2017,6(3):1364-1374.
[19]QADRDAN M,WU J,JENKINS N,et al.Operating strategies for a GB integrated gas and electricity network considering the uncertainty in wind power forecasts[J].IEEE Transactions on Sustainable Energy,2014,5(1):128-138.
[20]LI Z S,GUO Q L,SUN H B,et al.Sufficient conditions for exact relaxation of complementarity constraints for storageconcerned economic dispatch[J].IEEE Transactions on Power Systems,2016,31(2):1653-1654.
[21]SHAO C C,WANG X F,WANG X L,et al.Cooperative dispatch of wind generation and electric vehicles with battery storage capacity constraints in SCUC[J].IEEE Transactions on Smart Grid,2014,5(5):2219-2226.
[22]MARZBAND M,JAVADI M,DOMNGUEZ-GARCA J L,et al.Non-cooperative game theory based energy management systems for energy district in the retail market considering DER uncertainties[J].IET Generation,Transmission and Distribution,2016,10(12):2999-3009.
[23]黄国日,刘伟佳,文福拴,等.具有电转气装置的电-气混联综合能源系统的协同规划[J].电力建设,2016,37(9):1-13.HUANG Guori,LIU Weijia,WEN Fushuan,et al.Collaborative planning of integrated electricity and natural gas energy systems with power-to-gas stations[J].Electric Power Construction,2016,37(9):1-13.
[24]YAO W F,ZHAO J H,WEN F S,et al.A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles[J].IEEE Transactions on Power Systems,2013,28(3):2768-2778.
[2]贾宏杰,王丹,徐宪东,等.区域综合能源系统若干问题研究[J].电力系统自动化,2015,39(7):198-207.DOI:10.7500/AEPS20141009011.JIA Hongjie,WANG Dan,XU Xiandong,et al.Research on some key problems related to integrated energy systems[J].Automation of Electric Power Systems,2015,39(7):198-207.DOI:10.7500/AEPS20141009011.
[3]曾鸣,杨雍琦,刘敦楠,等.能源互联网“源-网-荷-储”协调优化运营模式及关键技术[J].电网技术,2016,40(1):114-124.ZENG Ming,YANG Yongqi,LIU Dunnan,et al.“GenerationGrid-Load-Storage”coordinative optimal operation mode of energy internet and key technologies[J].Power System Technology,2016,40(1):114-124.
[4]孙宏斌,郭庆来,潘昭光.能源互联网:理念、架构与前沿展望[J].电力系统自动化,2015,39(19):1-8.DOI:10.7500/AEPS20150701007.SUN Hongbin,GUO Qinglai,PAN Zhaoguang.Energy Internet:concept,architecture and frontier outlook[J].Automation of Electric Power Systems,2015,39(19):1-8.DOI:10.7500/AEPS20150701007.
[5]SU W C,WANG J H,ROH J.Stochastic energy scheduling in microgrids with intermittent renewable energy resources[J].IEEE Transactions on Smart Grid,2014,5(4):1876-1883.
[6]ZHAO J H,WEN F S,DONG Z Y,et al.Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization[J].IEEE Transactions on Industrial Informatics,2012,8(4):889-899.
[7]李建林,田立亭,来小康.能源互联网背景下的电力储能技术展望[J].电力系统自动化,2015,39(23):15-25.DOI:10.7500/AEPS20150906004.LI Jianlin,TIAN Liting,LAI Xiaokang.Outlook of electrical energy storage technologies under Energy Internet background[J].Automation of Electric Power Systems,2015,39(23):15-25.DOI:10.7500/AEPS20150906004.
[8]刘伟佳,文福拴,薛禹胜,等.电转气技术的成本特征与运营经济性分析[J].电力系统自动化,2016,40(24):1-11.DOI:10.7500/AEPS20160504013.LIU Weijia,WEN Fushuan,XUE Yusheng,et al.Cost characteristics and economic analysis of power-to-gas technology[J].Automation of Electric Power Systems,2016,40(24):1-11.DOI:10.7500/AEPS20160504013.
[9]张华一,文福拴,张璨,等.计及舒适度的家庭能源中心运行优化模型[J].电力系统自动化,2016,40(20):32-39.DOI:10.7500/AEPS20160503002.ZHANG Huayi,WEN Fushuan,ZHANG Can,et al.Operation optimization model of home energy hubs considering comfort level of customers[J].Automation of Electric Power Systems,2016,40(20):32-39.DOI:10.7500/AEPS20160503002.
[10]DIVSHELI P H,CHOI B J,LIANG H.Multi-agent transactive energy management system considering high levels of renewable energy source and electric vehicles[J].IET Generation Transmission and Distribution,2017,11(15):3713-3721.
[11]李杨,刘伟佳,赵俊华,等.含电转气的电-气-热系统协同调度与消纳风电效益分析[J].电网技术,2016,40(12):3680-3688.LI Yang,LIU Weijia,ZHAO Junhua,et al.Optimal dispatch of combined electricity-gas-heat energy systems with power-togas devices and benefit analysis of wind power accommodation[J].Power System Technology,2016,40(12):3680-3688.
[12]SOARES J,CANIZES B,GHAZVINI M A F,et al.Twostage stochastic model using Benders’decomposition for largescale energy resources management in smart grids[J].IEEE Transactions on Industry Applications,2017,53(6):5905-5914.
[13]LIU N,YU X H,WANG C,et al.Energy sharing management for microgrids with PV prosumers:a Stackelberg game approach[J].IEEE Transactions on Industrial Informatics,2017,13(3):1088-1098.
[14]魏韡,陈玥,刘锋,等.基于主从博弈的智能小区代理商定价策略及电动汽车充电管理[J].电网技术,2015,39(4):939-945.WEI Wei,CHEN Yue,LIU Feng,et al.Stackelberg game based retailer pricing scheme and EV charging management in smart residential area[J].Power System Technology,2015,39(4):939-945.
[15]YU M M,HONG S H.A real-time demand-response algorithm for smart grids:a Stackelberg game approach[J].IEEE Transactions on Smart Grid,2017,7(2):879-888.
[16]DAMAVANDI M Y,NEYESTANI N,CHICCO G,et al.Aggregation of distributed energy resources under the concept of multi-energy players in local energy system[J].IEEE Transactions on Sustainable Energy,2017,8(4):1679-1693.
[17]马丽,刘念,张建华,等.基于主从博弈策略的社区能源互联网分布式能量管理[J].电网技术,2016,40(12):3655-3661.MA Li,LIU Nian,ZHANG Jianhua,et al.Distributed energy management of community energy internet based on leaderfollowers game[J].Power System Technology,2016,40(12):3655-3661.
[18]WEI W,LIU F,MEI S W.Energy pricing and dispatch for smart grid retailers under demand response and market price uncertainty[J].IEEE Transactions on Smart Grid,2017,6(3):1364-1374.
[19]QADRDAN M,WU J,JENKINS N,et al.Operating strategies for a GB integrated gas and electricity network considering the uncertainty in wind power forecasts[J].IEEE Transactions on Sustainable Energy,2014,5(1):128-138.
[20]LI Z S,GUO Q L,SUN H B,et al.Sufficient conditions for exact relaxation of complementarity constraints for storageconcerned economic dispatch[J].IEEE Transactions on Power Systems,2016,31(2):1653-1654.
[21]SHAO C C,WANG X F,WANG X L,et al.Cooperative dispatch of wind generation and electric vehicles with battery storage capacity constraints in SCUC[J].IEEE Transactions on Smart Grid,2014,5(5):2219-2226.
[22]MARZBAND M,JAVADI M,DOMNGUEZ-GARCA J L,et al.Non-cooperative game theory based energy management systems for energy district in the retail market considering DER uncertainties[J].IET Generation,Transmission and Distribution,2016,10(12):2999-3009.
[23]黄国日,刘伟佳,文福拴,等.具有电转气装置的电-气混联综合能源系统的协同规划[J].电力建设,2016,37(9):1-13.HUANG Guori,LIU Weijia,WEN Fushuan,et al.Collaborative planning of integrated electricity and natural gas energy systems with power-to-gas stations[J].Electric Power Construction,2016,37(9):1-13.
[24]YAO W F,ZHAO J H,WEN F S,et al.A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles[J].IEEE Transactions on Power Systems,2013,28(3):2768-2778.