基于典型场景集的虚拟电厂与配电网协同定价策略
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摘要
虚拟电厂(virtual power plant,VPP)技术能够有效地提升配电网运行灵活性和可再生能源消纳水平,为描述电力市场环境下配电系统中多种资源的不确定性,采用拉丁超立方抽样和多尺度NJW谱聚类算法获取了包含电价、负荷、可再生能源出力等多种随机因素的典型场景集;根据典型场景集,考虑配电网与虚拟电厂的网络结构、潮流安全、机组出力等约束条件,建立了基于虚拟电厂与配电网各自利益最大化的优化模型,并提出一种基于虚拟电厂与配电网交替优化的协同定价策略。算例仿真结果表明,所提方法充分地考虑了多种随机因素,能够合理地制定虚拟电厂与配电网的交易电价,维持系统功率平衡。
Virtual power plant (VPP) technology can effectively improve the flexibility of distribution network and promote the penetration of renewable energy sources. To represent the uncertainties of multiple resources in distribution system under the power market environment,typical scenes including multiple random factors are proposed,such as electricity prices,loads and renewable energy generations,which are obtained by using Latin hypercube sampling and multiscale spectral clustering algorithm. According to the typical scenario set,considering the constraints of network structure,power flowsecurity and unit output of distribution network and VPP,optimization models for maximizing the respective benefits of VPP and distribution network are established,and a cooperative pricing strategy based on alternating optimization of VPP and distribution network is proposed. Simulation analyses indicate that the proposed strategy can formulate the transaction price between the VPP and the distribution network reasonably and maintain the system power balance.
Virtual power plant (VPP) technology can effectively improve the flexibility of distribution network and promote the penetration of renewable energy sources. To represent the uncertainties of multiple resources in distribution system under the power market environment,typical scenes including multiple random factors are proposed,such as electricity prices,loads and renewable energy generations,which are obtained by using Latin hypercube sampling and multiscale spectral clustering algorithm. According to the typical scenario set,considering the constraints of network structure,power flowsecurity and unit output of distribution network and VPP,optimization models for maximizing the respective benefits of VPP and distribution network are established,and a cooperative pricing strategy based on alternating optimization of VPP and distribution network is proposed. Simulation analyses indicate that the proposed strategy can formulate the transaction price between the VPP and the distribution network reasonably and maintain the system power balance.
引文
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[13]张杭,丁晓群,陈光宇,等.基于场景时域概率的主动配电网全协调无功优化[J].电力建设,2018,39(8):53-58.ZHANG Hang,DING Xiaoqun,CHEN Guangyu,et al.General coordinated reactive pow er optimization of active distribution netw ork on the basis of scenario time domain probability[J].Electric Pow er Construction,2018,39(8):53-58.
[14]刘梦依,邱晓燕,张楷,等.计及源-荷不确定性的高比例可再生能源系统协同优化运行[J].电力建设,2018,39(12):55-62.LIU M engyi,QIU Xiaoyan,ZHANG Kai,et al.Collaborative optimization operation of pow er systems w ith high proportion of renew able energy considering uncertainty of generation and load[J].Electric Power Construction,2018,39(12):55-62.
[15]黄河,任佳依,高松,等.基于场景分析的有源配电系统有功无功协调鲁棒优化策略[J].电力建设,2018,39(8):32-41.HUANG He,REN Jiayi,GAO Song,et al.Coordinated robust optimization strategy for active and reactive pow er in active distribution system based on scenario analysis[J].Electric Pow er Construction,2018,39(8):32-41.
[16]XU Y L,LI Z C,ZHAO J H,et al.Distributed robust control strategy of grid-connected inverters for energy storage system's stateof-charge balancing[J].IEEE Transactions on Smart Grid,2018,9(6):5907-5917.
[17]陈璨,吴文传,张伯明,等.基于多场景技术的有源配电网可靠性评估[J].中国电机工程学报,2012,32(34):67-73.CHEN Can,WU Wenchuan,ZHANG Boming,et al.An active distribution system reliability evaluation method based on multiple scenarios technique[J].Proceedings of the CSEE,2012,32(34):67-73.
[18]LIN S F,LI F X,TIAN E W,et al.Clustering load profiles for demand response applications[J].IEEE Transactions on Smart Grid.2019,10(2):1599-1607.
[19]ZHU Y,YI Z,LU Q,et al.Typical scene acquisition strategy for VPP based on multi-scale spectral clustering algorithm[C]//20182nd IEEE Conference on Energy Internet and Energy System Integration(EI2).Beijing:IEEE,2018:1-5.
[20]林顺富,田二伟,符杨,等.基于信息熵分段聚合近似和谱聚类的负荷分类方法[J].中国电机工程学报,2017,37(8):2242-2252.LIN Shunfu,TIAN Erw ei,FU Yang,et al.Pow er load classification method based on information entropy piecew iseaggregate approximation and spectral clustering[J].Proceedings of the CSEE,2017,37(8):2242-2252.
[21]ZHANG H G,LI Y S,GAO D W,et al.Distributed optimal energy management for energy internet[J].IEEE Transactions on Industrial Informatics,2017,13(6):3081-3097.
[22]AHAMD J,TAHIR M,MAZUMDER S.Improved dynamic performance and hierarchical energy management of microgrids w ith energy routing[J].IEEE Transactions on Industrial Informatics,2018,DOI:10.1109/TII.2018.2877739.
[23]ZHANG W,XU Y L.Distributed optimal control for multiple microgrids in a distribution netw ork[J/OL].IEEE Transactions on Smart Grid,2018,http://ieeexplore.ieee.org/document/8357503.DOI:10.1109/TSG.2018.2834921.
[24]刘一兵,吴文传,张伯明,等.基于混合整数二阶锥规划的主动配电网有功-无功协调多时段优化运行[J].中国电机工程学报,2014,34(16):2575-2583.LIU Yibing,WU Wenchuan,ZHANG Boming,et al.A mixed integer second-order cone programming based active and reactive pow er coordinated multi-period optimization for active distribution netw ork[J].Proceedings of the CSEE,2014,34(16):2575-2583.
[25]刘健辰,刘山林.基于二阶锥松弛和Big-M法的配电网分布式电源优化配置[J].电网技术,2018,42(8):2604-2611.LIU Jianchen,LIU Shanlin.Optimal distributed generation allocation in distribution netw ork based on second order conicrelaxation and Big-M method[J].Pow er System Technology,2018,42(8):2604-2611.
[26]ZHENG W Y,WU W C,ZHANG B M,et al.A fully distributed reactive pow er optimization and control method for active distribution netw orks[J].IEEE Transactions on Smart Grid,2016,7(2):1021-1033.
[27]LOBO M S,VANDENBERGHE L,BOYD S,et al.Applications of second-order cone programming[J].Linear Algebra&Its Applications,1998,284(1/2/3):193-228.
[2]ZHAO Q C,SHEN Y,LI M Y.Control and bidding strategy for virtual pow er plants w ith renew able generation and inelastic demand in electricity markets[J].IEEE Transactions on Sustainable Energy,2016,7(2):562-575.
[3]周任军,孙洪,唐夏菲,等.双碳量约束下风电-碳捕集虚拟电厂低碳经济调度[J].中国电机工程学报,2018,38(6):1675-1683.ZHOU Renjun,SUN Hong,TANG Xiafei,et al.Low-carbon economic dispatch based on virtual pow er plant made up of carbon capture unit and w ind pow er under double carbon constraint[J].Proceedings of the CSEE,2018,38(6):1675-1683.
[4]MULLER F L,WOERNER S,LYGEROS J.Unlocking the potential of flexible energy resources to help balance the pow er grid[J/OL].IEEE Transactions on Smart Grid,2018,https://ieeexplore.ieee.org/document/8516334.DOI:10.1109/TSG.2018.2878998.
[5]方燕琼,甘霖,艾芊,等.基于主从博弈的虚拟电厂双层竞标策略[J].电力系统自动化,2017,41(14):61-69.FANG Yanqiong,GAN Lin,AI Qian,et al.Stackelberg game based bi-level bidding strategy for virtual pow er plant[J].Automation of Electric Pow er Systems,2017,41(14):61-69.
[6]TOUBEAU J F,DE GREVE Z,VALLEE F.Medium-term multimarket optimization for virtual pow er plants:A stochastic-based decision environment[J].IEEE Transactions on Pow er Systems,2018,33(2):1399-1410.
[7]黄铃燃,边晓燕,李东东,等.含储能虚拟电厂接入配电网的联合优化调度[J].电力建设,2017,38(9):38-44.HUANG Lingran,BIAN Xiaoyan,LI Dongdong,et al.Joint optimal dispatch for pow er distribution netw ork w ith energy storage virtual pow er plant[J].Electric Pow er Construction,2017,38(9):38-44.
[8]董文略,王群,杨莉.含风光水的虚拟电厂与配电公司协调调度模型[J].电力系统自动化,2015,39(9):75-81,207.DONG Wenlue,WANG Qun,YANG Li.A coordinated dispatching model for a distribution utility and virtual pow er plants w ith w ind/photovoltaic/hydro generators[J].Automation of Electric Pow er Systems,2015,39(9):75-81,207.
[9]边晓燕,杨帅帅,黄铃燃,等.虚拟电厂接入配电网的电力系统调度灵活性研究[J/OL].电测与仪表,2018,http://kns.cnki.net/kcms/detail/23.1202.th.20181208.1419.042.html.BIAN Xiaoyan,YANG Shuaishuai,HUANG Lingran,et al.Research on pow er system scheduling flexibility of virtual pow er plant accessing to distribution netw ork[J/OL].Electrical M easurement&Instrumentation,http://kns.cnki.net/kcms/detail/23.1202.th.20181208.1419.042.html.
[10]陈妤,卫志农,胥峥,等.电力体制改革下的多虚拟电厂联合优化调度策略[J].电力系统自动化,2019,43(7):42-49.CHEN Yu,WEI Zhinong,XU Zheng,et al.Optimal scheduling strategy of multiple virtual pow er plants under electricity market reform[J].Automation of Electric Pow er Systems,2019,43(7):42-49.
[11]KORAKI D,STRUNZ K.Wind and solar power integration in electricity markets and distribution netw orks through service-centric virtual pow er plants[J].IEEE Transactions on Pow er Systems,2018,33(1):473-485.
[12]仪忠凯,李志民.计及热网储热和供热区域热惯性的热电联合调度策略[J].电网技术,2018,42(5):1378-1384.YI Zhongkai,LI Zhimin.Combined heat and pow er dispatching strategy considering heat storage characteristics of heating netw ork and thermal inertia in heating area[J].Pow er System Technology,2018,42(5):1378-1384.
[13]张杭,丁晓群,陈光宇,等.基于场景时域概率的主动配电网全协调无功优化[J].电力建设,2018,39(8):53-58.ZHANG Hang,DING Xiaoqun,CHEN Guangyu,et al.General coordinated reactive pow er optimization of active distribution netw ork on the basis of scenario time domain probability[J].Electric Pow er Construction,2018,39(8):53-58.
[14]刘梦依,邱晓燕,张楷,等.计及源-荷不确定性的高比例可再生能源系统协同优化运行[J].电力建设,2018,39(12):55-62.LIU M engyi,QIU Xiaoyan,ZHANG Kai,et al.Collaborative optimization operation of pow er systems w ith high proportion of renew able energy considering uncertainty of generation and load[J].Electric Power Construction,2018,39(12):55-62.
[15]黄河,任佳依,高松,等.基于场景分析的有源配电系统有功无功协调鲁棒优化策略[J].电力建设,2018,39(8):32-41.HUANG He,REN Jiayi,GAO Song,et al.Coordinated robust optimization strategy for active and reactive pow er in active distribution system based on scenario analysis[J].Electric Pow er Construction,2018,39(8):32-41.
[16]XU Y L,LI Z C,ZHAO J H,et al.Distributed robust control strategy of grid-connected inverters for energy storage system's stateof-charge balancing[J].IEEE Transactions on Smart Grid,2018,9(6):5907-5917.
[17]陈璨,吴文传,张伯明,等.基于多场景技术的有源配电网可靠性评估[J].中国电机工程学报,2012,32(34):67-73.CHEN Can,WU Wenchuan,ZHANG Boming,et al.An active distribution system reliability evaluation method based on multiple scenarios technique[J].Proceedings of the CSEE,2012,32(34):67-73.
[18]LIN S F,LI F X,TIAN E W,et al.Clustering load profiles for demand response applications[J].IEEE Transactions on Smart Grid.2019,10(2):1599-1607.
[19]ZHU Y,YI Z,LU Q,et al.Typical scene acquisition strategy for VPP based on multi-scale spectral clustering algorithm[C]//20182nd IEEE Conference on Energy Internet and Energy System Integration(EI2).Beijing:IEEE,2018:1-5.
[20]林顺富,田二伟,符杨,等.基于信息熵分段聚合近似和谱聚类的负荷分类方法[J].中国电机工程学报,2017,37(8):2242-2252.LIN Shunfu,TIAN Erw ei,FU Yang,et al.Pow er load classification method based on information entropy piecew iseaggregate approximation and spectral clustering[J].Proceedings of the CSEE,2017,37(8):2242-2252.
[21]ZHANG H G,LI Y S,GAO D W,et al.Distributed optimal energy management for energy internet[J].IEEE Transactions on Industrial Informatics,2017,13(6):3081-3097.
[22]AHAMD J,TAHIR M,MAZUMDER S.Improved dynamic performance and hierarchical energy management of microgrids w ith energy routing[J].IEEE Transactions on Industrial Informatics,2018,DOI:10.1109/TII.2018.2877739.
[23]ZHANG W,XU Y L.Distributed optimal control for multiple microgrids in a distribution netw ork[J/OL].IEEE Transactions on Smart Grid,2018,http://ieeexplore.ieee.org/document/8357503.DOI:10.1109/TSG.2018.2834921.
[24]刘一兵,吴文传,张伯明,等.基于混合整数二阶锥规划的主动配电网有功-无功协调多时段优化运行[J].中国电机工程学报,2014,34(16):2575-2583.LIU Yibing,WU Wenchuan,ZHANG Boming,et al.A mixed integer second-order cone programming based active and reactive pow er coordinated multi-period optimization for active distribution netw ork[J].Proceedings of the CSEE,2014,34(16):2575-2583.
[25]刘健辰,刘山林.基于二阶锥松弛和Big-M法的配电网分布式电源优化配置[J].电网技术,2018,42(8):2604-2611.LIU Jianchen,LIU Shanlin.Optimal distributed generation allocation in distribution netw ork based on second order conicrelaxation and Big-M method[J].Pow er System Technology,2018,42(8):2604-2611.
[26]ZHENG W Y,WU W C,ZHANG B M,et al.A fully distributed reactive pow er optimization and control method for active distribution netw orks[J].IEEE Transactions on Smart Grid,2016,7(2):1021-1033.
[27]LOBO M S,VANDENBERGHE L,BOYD S,et al.Applications of second-order cone programming[J].Linear Algebra&Its Applications,1998,284(1/2/3):193-228.