含光伏电站和蓄电池储能系统的主动配电系统状态估计
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摘要
间歇性和随机波动性的分布式新能源大规模接入,储能系统与电动汽车的随机充放电以及智能量测装置的量测误差等使得主动配电系统的态势感知面临诸多挑战。考虑到光照强度、温度及电池荷电状态等影响因素,文中搭建了含光伏发电电源、配电网和蓄电池储能负荷的主动配电系统状态估计模型。首先,基于光伏五参数模型和电池内阻模型,推导出光伏系统和蓄电池储能系统的量测函数及雅可比矩阵。然后,结合配电网的状态估计模型,将电气量和非电气量统一标幺化后,对主动配电系统进行状态估计及不良数据处理。最后,在IEEE 33节点系统下进行了仿真验证。仿真结果表明,与光伏系统和蓄电池储能系统作为PQ节点的模型相比,所提方法扩展了与光伏系统和蓄电池储能系统相关的状态估计和不良数据处理能力,且提高了配电网的状态估计精度。
The large-scale integration of distributed energy resources with intermittent and stochastic volatility, the random charging and discharging of energy storage system and electric vehicles, and measurement errors of the intelligent measuring devices make the situational awareness of active distribution systems face some challenges. Considering the influencing factors such as the solar irradiance, the temperature, and the state of charge(SOC) of batteries, a state estimation model for the active distribution systems is developed including integrated photovoltaic power generation systems, the distribution network, and battery energy storage systems. Firstly, based on the photovoltaic five-parameter model and the battery internal resistance model, the measurement functions and the Jacobian matrix of the photovoltaic systems and battery energy storage systems are derived. Then, combined with the state estimation model of the distribution network, the electrical quantity and non-electrical quantity are uniformly standardized, and the state estimation and bad data processing of the active distribution systems are performed. Finally, the simulation is carried out in IEEE 33-node system. The simulation results show that, compared with the conventional model which only takes the photovoltaic system and the battery energy storage system as PQ nodes, the proposed method significantly expands the scopes and capabilities of state estimation and bad data processing in the photovoltaic system and battery energy storage system, and improves the accuracy of the state estimation of the distribution network.
The large-scale integration of distributed energy resources with intermittent and stochastic volatility, the random charging and discharging of energy storage system and electric vehicles, and measurement errors of the intelligent measuring devices make the situational awareness of active distribution systems face some challenges. Considering the influencing factors such as the solar irradiance, the temperature, and the state of charge(SOC) of batteries, a state estimation model for the active distribution systems is developed including integrated photovoltaic power generation systems, the distribution network, and battery energy storage systems. Firstly, based on the photovoltaic five-parameter model and the battery internal resistance model, the measurement functions and the Jacobian matrix of the photovoltaic systems and battery energy storage systems are derived. Then, combined with the state estimation model of the distribution network, the electrical quantity and non-electrical quantity are uniformly standardized, and the state estimation and bad data processing of the active distribution systems are performed. Finally, the simulation is carried out in IEEE 33-node system. The simulation results show that, compared with the conventional model which only takes the photovoltaic system and the battery energy storage system as PQ nodes, the proposed method significantly expands the scopes and capabilities of state estimation and bad data processing in the photovoltaic system and battery energy storage system, and improves the accuracy of the state estimation of the distribution network.
引文
[1]徐航,鞠力,董树锋,等.提高配电网状态估计精度的智能配电单元优化布点方法[J].电网技术,2018,42(4):1210-1216.XU Hang,JU Li,DONG Shufeng,et al.Optimization of intelligent distribution unit placement to improve accuracy of distribution network state estimation[J].Power System Technology,2018,42(4):1210-1216.
[2]徐俊俊,吴在军,胡秦然,等.考虑多类型分布式电源和负荷不确定性的主动配电网区间状态估计[J].中国电机工程学报,2018,38(11):3255-3265.XU Junjun,WU Zaijun,HU Haoran,et al.Interval state estimation for active distribution networks considering uncertainties of multiple types of DGs and loads[J].Proceedings of the CSEE,2018,38(11):3255-3265.
[3]吴在军,徐俊俊,余星火,等.主动配电网状态估计技术评述[J].电力系统自动化,2017,41(13):182-191.DOI:10.7500/AEPS20161123001.WU Zaijun,XU Junjun,YU Xinghuo,et al.Review on state estimation technique of active distribution network[J].Automation of Electric Power Systems,2017,41(13):182-191.DOI:10.7500/AEPS20161123001.
[4]RANKOVIC'A,MAKSIMOVIC'B M,SARIC'A T,et al.ANN-based correlation of measurements in micro-grid state estimation[J].International Transactions on Electrical Energy Systems,2015,25(10):2181-2202.
[5]RANKOVIC'A,MAKSIMOVIC'B M,SARIC'A T.A threephase state estimation in active distribution networks[J].International Journal of Electrical Power&Energy Systems,2014,54(1):154-162.
[6]ABBAS I,REZA A,SEIF I,et al.A new coordinated approach to state estimation in integrated power systems[J].International Journal of Electrical Power&Energy Systems,2013,45(1):152-158.
[7]LIU J,TANG J,PONCI F,et al.Trade-offs in PMUdeployment for state estimation in active distribution grids[J].IEEE Transactions on Smart Grid,2012,3(2):915-924.
[8]VALVERDE G,SARIC A T,TERZIJA V,et al.Stochastic monitoring of distribution networks including correlated input variables[J].IEEE Transactions on Power Systems,2013,28(1):246-255.
[9]AL-OTHMAN A K.A fuzzy state estimator based on uncertain measurements[J].Measurement,2009,42(4):628-637.
[10]黄蔓云,孙国强,卫志农,等.基于脉冲神经网络伪量测建模的配电网三相状态估计[J].电力系统自动化,2016,40(16):38-43.HUANG Manyun,SUN Guoqiang,WEI Zhinong,et al.Three-phase state estimation in distribution systems based on pseudo measurement modelling using spiking neural network[J].Automation of Electric Power Systems,2016,40(16):38-43.
[11]HAUGHTON D A,HEYDT G T.A linear state estimation formulation for smart distribution systems[J].IEEETransactions on Power Systems,2013,28(2):1187-1195.
[12]CHEN Sheng,WEI Zhinong,SUN Guoqiang,et al.Multi-area distributed three-phase state estimation for unbalanced active distribution networks[J].Journal of Modern Power Systems and Clean Energy,2017,5(5):767-776.
[13]FILHO M B D C,SOUZA J C S D,GUIMARAENS M A R,et al.Enhanced bad data processing by phasor-aided state estimation[J].IEEE Transactions on Power Systems,2014,29(5):2200-2209.
[14]CARO E,CONEJO A J,MINGUEZ R,et al.Multiple bad data identification considering measurement dependencies[J].IEEE Transactions on Power Systems,2011,26(4):1953-1961.
[15]POON K K Y,EMAMI R,BOSE A,et al.External data exchange issues for state estimation in power systems[J].IEEE Transactions on Power Systems,2012,27(2):849-856.
[16]ZHANG Liuxi,ABUR A.Impact of tuning on bad data detection of PMU measurements[C]//IEEE PES Innovative Smart Grid Technologies,May 21-24,2012,Tianjin,China.
[17]LIN Yuzhang,ABUR A.A highly efficient bad data identification approach for very large scale power systems[J].IEEE Transactions on Power Systems,2018,33(6):5979-5989.
[18]ABUR A,ANTONIO G E.Power system state estimation:theory and implementation[M].New York:Marcel Dekker,2004.
[19]孔祥雨,徐永海,曾雅文,等.一种求解光伏电池5参数模型的方法[J].电力系统保护与控制,2013,41(22):46-50.KONG Xiangyu,XU Yonghai,ZENG Yawen,et al.Aparameter extraction method for five-parameter model of photovoltaic cells[J].Power System Protection and Control,2013,41(22):46-50.
[20]李秋硕.电动汽车接入电网的电能有序利用模型与控制策略研究[D].北京:华北电力大学,2014.LI Qiushuo.Research on models and strategies of electric energy coordinated consumption with electric vehicles integrated in power system[D].Beijing:North China Electric Power University,2014.
[21]HE Guangyu,DONG Shufeng,QI Junjian,et al.Robust state estimator based on maximum normal measurement rate[J].IEEE Transactions on Power Systems,2011,26(4):2058-2065.
[22]XU Weiyu,WANG Meng,TANG Ao.Sparse error correction from nonlinear measurements with applications in bad data detection for power networks[J].IEEE Transactions on Signal Processing,2013,61(24):6175-6187.
[23]LIN Yuzhang,ABUR A.Robust state estimation against measurement and network parameter errors[J].IEEETransactions on Power Systems,2018,33(5):4751-4759.
[24]GOL Murat,ABUR A.A robust PMU based three-phase state estimator using modal decoupling[J].IEEE Transactions on Power Systems,2014,29(5):2292-2299.
[25]NANCHIAN S,MAJUMDAR A,PAL B C.Ordinal optimization technique for three-phase distribution network state estimation including discrete variables[J].IEEETransactions on Sustainable Energy,2017,8(4):1528-1535.
[2]徐俊俊,吴在军,胡秦然,等.考虑多类型分布式电源和负荷不确定性的主动配电网区间状态估计[J].中国电机工程学报,2018,38(11):3255-3265.XU Junjun,WU Zaijun,HU Haoran,et al.Interval state estimation for active distribution networks considering uncertainties of multiple types of DGs and loads[J].Proceedings of the CSEE,2018,38(11):3255-3265.
[3]吴在军,徐俊俊,余星火,等.主动配电网状态估计技术评述[J].电力系统自动化,2017,41(13):182-191.DOI:10.7500/AEPS20161123001.WU Zaijun,XU Junjun,YU Xinghuo,et al.Review on state estimation technique of active distribution network[J].Automation of Electric Power Systems,2017,41(13):182-191.DOI:10.7500/AEPS20161123001.
[4]RANKOVIC'A,MAKSIMOVIC'B M,SARIC'A T,et al.ANN-based correlation of measurements in micro-grid state estimation[J].International Transactions on Electrical Energy Systems,2015,25(10):2181-2202.
[5]RANKOVIC'A,MAKSIMOVIC'B M,SARIC'A T.A threephase state estimation in active distribution networks[J].International Journal of Electrical Power&Energy Systems,2014,54(1):154-162.
[6]ABBAS I,REZA A,SEIF I,et al.A new coordinated approach to state estimation in integrated power systems[J].International Journal of Electrical Power&Energy Systems,2013,45(1):152-158.
[7]LIU J,TANG J,PONCI F,et al.Trade-offs in PMUdeployment for state estimation in active distribution grids[J].IEEE Transactions on Smart Grid,2012,3(2):915-924.
[8]VALVERDE G,SARIC A T,TERZIJA V,et al.Stochastic monitoring of distribution networks including correlated input variables[J].IEEE Transactions on Power Systems,2013,28(1):246-255.
[9]AL-OTHMAN A K.A fuzzy state estimator based on uncertain measurements[J].Measurement,2009,42(4):628-637.
[10]黄蔓云,孙国强,卫志农,等.基于脉冲神经网络伪量测建模的配电网三相状态估计[J].电力系统自动化,2016,40(16):38-43.HUANG Manyun,SUN Guoqiang,WEI Zhinong,et al.Three-phase state estimation in distribution systems based on pseudo measurement modelling using spiking neural network[J].Automation of Electric Power Systems,2016,40(16):38-43.
[11]HAUGHTON D A,HEYDT G T.A linear state estimation formulation for smart distribution systems[J].IEEETransactions on Power Systems,2013,28(2):1187-1195.
[12]CHEN Sheng,WEI Zhinong,SUN Guoqiang,et al.Multi-area distributed three-phase state estimation for unbalanced active distribution networks[J].Journal of Modern Power Systems and Clean Energy,2017,5(5):767-776.
[13]FILHO M B D C,SOUZA J C S D,GUIMARAENS M A R,et al.Enhanced bad data processing by phasor-aided state estimation[J].IEEE Transactions on Power Systems,2014,29(5):2200-2209.
[14]CARO E,CONEJO A J,MINGUEZ R,et al.Multiple bad data identification considering measurement dependencies[J].IEEE Transactions on Power Systems,2011,26(4):1953-1961.
[15]POON K K Y,EMAMI R,BOSE A,et al.External data exchange issues for state estimation in power systems[J].IEEE Transactions on Power Systems,2012,27(2):849-856.
[16]ZHANG Liuxi,ABUR A.Impact of tuning on bad data detection of PMU measurements[C]//IEEE PES Innovative Smart Grid Technologies,May 21-24,2012,Tianjin,China.
[17]LIN Yuzhang,ABUR A.A highly efficient bad data identification approach for very large scale power systems[J].IEEE Transactions on Power Systems,2018,33(6):5979-5989.
[18]ABUR A,ANTONIO G E.Power system state estimation:theory and implementation[M].New York:Marcel Dekker,2004.
[19]孔祥雨,徐永海,曾雅文,等.一种求解光伏电池5参数模型的方法[J].电力系统保护与控制,2013,41(22):46-50.KONG Xiangyu,XU Yonghai,ZENG Yawen,et al.Aparameter extraction method for five-parameter model of photovoltaic cells[J].Power System Protection and Control,2013,41(22):46-50.
[20]李秋硕.电动汽车接入电网的电能有序利用模型与控制策略研究[D].北京:华北电力大学,2014.LI Qiushuo.Research on models and strategies of electric energy coordinated consumption with electric vehicles integrated in power system[D].Beijing:North China Electric Power University,2014.
[21]HE Guangyu,DONG Shufeng,QI Junjian,et al.Robust state estimator based on maximum normal measurement rate[J].IEEE Transactions on Power Systems,2011,26(4):2058-2065.
[22]XU Weiyu,WANG Meng,TANG Ao.Sparse error correction from nonlinear measurements with applications in bad data detection for power networks[J].IEEE Transactions on Signal Processing,2013,61(24):6175-6187.
[23]LIN Yuzhang,ABUR A.Robust state estimation against measurement and network parameter errors[J].IEEETransactions on Power Systems,2018,33(5):4751-4759.
[24]GOL Murat,ABUR A.A robust PMU based three-phase state estimator using modal decoupling[J].IEEE Transactions on Power Systems,2014,29(5):2292-2299.
[25]NANCHIAN S,MAJUMDAR A,PAL B C.Ordinal optimization technique for three-phase distribution network state estimation including discrete variables[J].IEEETransactions on Sustainable Energy,2017,8(4):1528-1535.
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