考虑电力参数和量测误差的网络拓扑误差辨识方法
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摘要
电力系统的参数误差和量测误差在状态估计时经常同时发生。为此提出了一种同时辨识不正常状态支路和参数误差的方法。首先建立了含断路器的支路模型,确定了利用断路器状态估计的误差方程。然后,提出了一种基于扩展状态估计方程的能够同时辨识网络拓扑误差、参数误差和坏数据量测的多源误差的方法。所提拓扑结构误差辨识方法能够在含有坏数据和网络参数误差下辨识不正常状态支路。该方法将约束条件中的归一化拉格朗日乘子加入到断路器模型和参数误差中,通过估计含有拓扑和参数误差的可疑支路的参数来辨识不正常支路的状态,且仅利用传统状态估计的结果来辨识误差。最后利用IEEE118节点系统进行算例验证,对比分析了多种场景下所提方法与传统辨识方法的结果,说明了所提方法的有效性。
The parameter error and measurement errors in the power system state estimation can appear simultaneously. In this paper, a new approach for detecting and identifying incorrect branches and measurement errors at the same time is presented. First, the model of branch including Circuit Breaker(CB) is built, thus the error estimation equation by the CB state estimation is settled. Then the proposed topology error identification approach has the ability of identifying the incorrect branch status in terms of bad data and erroneous network parameters, which can identify the incorrect status of branches through estimating the parameters of suspicious branches pertaining to topology or parameters' errors. It uses the Normalized Lagrange Multipliers(NLM) of the constraints added for modeling CBs and parameter errors to the process of identification. In addition, a new approach for simultaneous identification of incorrect branch status and erroneous parameters is proposed, which is done by the estimation of the parameters including topology error and suspicious branches to detect the state of the incorrect branches. It only requires the results of a conventional state estimator to identify the errors. In the end, the simulation results in IEEE 118 bus indicate that the proposed three-stage method is effective compared with traditional identification method under multi scenarios.
The parameter error and measurement errors in the power system state estimation can appear simultaneously. In this paper, a new approach for detecting and identifying incorrect branches and measurement errors at the same time is presented. First, the model of branch including Circuit Breaker(CB) is built, thus the error estimation equation by the CB state estimation is settled. Then the proposed topology error identification approach has the ability of identifying the incorrect branch status in terms of bad data and erroneous network parameters, which can identify the incorrect status of branches through estimating the parameters of suspicious branches pertaining to topology or parameters' errors. It uses the Normalized Lagrange Multipliers(NLM) of the constraints added for modeling CBs and parameter errors to the process of identification. In addition, a new approach for simultaneous identification of incorrect branch status and erroneous parameters is proposed, which is done by the estimation of the parameters including topology error and suspicious branches to detect the state of the incorrect branches. It only requires the results of a conventional state estimator to identify the errors. In the end, the simulation results in IEEE 118 bus indicate that the proposed three-stage method is effective compared with traditional identification method under multi scenarios.
引文
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[15]ZHAO J,NETTO M,MILI L.A robust iterated extended Kalman filter for power system dynamic state estimation[J].IEEE Transactions on Power Systems,2017,32(4):3205-3216.
[16]HUANG M,WEI Z,SUN G,et al.A multi-objective robust state estimator for systems measured by phasor measurement units[J].IEEE Access,2018,6:14620-14628.
[17]LOUREN?O E M,COELHO E P R,PAL B C.Topology error and bad data processing in generalized state estimation[J].IEEE Transactions on Power Systems,2015,30(6):3190-3200.
[18]JAEN A D L V,EXPOSITO A G.Implicitly constrained substation model for state estimation[J].IEEE Power Engineering Review,2007,22(6):57-57.
[19]ZHU J,ABUR A.Identification of network parameter errors[J].IEEE Transactions on Power Systems,2006,21(2):586-592.
[20]LIN Y,ABUR A.Enhancing network parameter error detection and correction via multiple measurement scans[J].IEEE Transactions on Power Systems,2017,32(3):2417-2425.
[21]BI T S,QIN X H,YANG Q X.A novel hybrid state estimator for including synchronized phasor measurements[J].Electric Power Systems Research,2008,78(8):1343-1352.
[22]NEJATI M,AMJADY N,ZAREIPOUR H.A new stochastic search technique combined with scenario approach for dynamic state estimation of power systems[J].IEEE Transactions on Power Systems,2012,27(4):2093-2105.
[23]CLEMENTS K A,COSTA A S.Topology error identification using normalized Lagrange multipliers[J].IEEE Transactions on Power Systems,2002,13(2):347-353.
[2]WU F F,LIU W H E.Detection of topology errors by state estimation power systems[J].IEEE Power Engineering Review,1989,9(2):50-51.
[3]SINGH H,ALVARADO F L.Network topology determination using least absolute value state estimation[J].IEEE Transactions on Power Systems,1995,10(3):1159-1165.
[4]CONTI S,RIZZO S A,SALERNO N,et al.Distribution network topology identification based on synchrophasor[J].AIMS Energy,2018,6(2).
[5]MILANO F.On the modelling of zero impedance branches for power flow analysis[J].IEEE Transactions on Power Systems,2016,31(4):3334-3335.
[6]胡春潮,何杰,马凯.基于信息冗余的电力系统分布式状态估计[J].电力系统保护与控制,2017,45(16):111-115.HU Chunchao,HE Jie,MA Kai.Power system distributed state estimation based on information redundancy of secondary system[J].Power System Protection and Control,2017,45(16):111-115.
[7]刘科研,盛万兴,何开元,等.基于拉格朗日松弛技术的复杂有源配电网分布式状态估计[J].电力系统保护与控制,2017,45(15):125-132.LIU Keyan,SHENG Wanxing,HE Kaiyuan,et al.Distributed state estimation of complex active distribution network based on Lagrange relaxation technique[J].Power System Protection and Control,2017,45(15):125-132.
[8]孙江山,刘敏,邓磊,等.电力系统分区和解耦状态估计研究综述[J].电力系统保护与控制,2018,46(10):162-169.SUN Jiangshan,LIU Min,DENG Lei,et al.Review of the research on the partition and decoupled state estimation of power system[J].Power System Protection and Control,2018,46(10):162-169.
[9]KORRES G N,KATSIKAS P J.Reduced model for numerical observability analysis in generalised state estimation[J].IEE Proceedings-Generation,Transmission and Distribution,2005,152(1):99-108.
[10]KORRES G N,KATSIKAS P J.A hybrid method for observability analysis using a reduced network graph theory[J].IEEE Power Engineering Review,2007,22(11):57-58.
[11]徐晗,陆子强.考虑误差非独立性的电力系统参数辨识估计[J].电网与清洁能源,2015,31(5):47-53.XU Han,LU Ziqiang.Power system parameter identification and estimation considering measurement error dependencies[J].Power System and Clean Energy,2015,31(5):47-53.
[12]金学成,邹根华,张浩,等.考虑抗差状态估计大误差点的电网可疑参数辨识及其应用[J].中国电力,2016,49(2):114-117.JIN Xuecheng,ZOU Genhua,ZHANG Hao,et al.Anetwork parameter errors identification method considering large error point based on robust state estimation and its real application[J].Electric Power,2016,49(2):114-117.
[13]颜伟,赵雪骞,陈俊,等.电网设备错误参数的支路量测标幺值残差代数和均值辨识法[J].电力自动化设备,2013,33(2):99-103.YAN Wei,ZHAO Xueqian,CHEN Jun,et al.Grid equipment parameter error identification based on mean algebraic sum of branch measurement normalized residuals[J].Electric Power Automation Equipment,2013,33(2):99-103.
[14]侯方迪,朱涛,赵川,等.考虑总体误差下降指标的电网参数辨识方法[J].电力系统自动化,2016,40(12):184-188.HOU Fangdi,ZHU Tao,ZHAO Chuan,et al.Network parameter identification method considering gross error reduction index[J].Automation of Electric Power Systems,2016,40(12):184-188.
[15]ZHAO J,NETTO M,MILI L.A robust iterated extended Kalman filter for power system dynamic state estimation[J].IEEE Transactions on Power Systems,2017,32(4):3205-3216.
[16]HUANG M,WEI Z,SUN G,et al.A multi-objective robust state estimator for systems measured by phasor measurement units[J].IEEE Access,2018,6:14620-14628.
[17]LOUREN?O E M,COELHO E P R,PAL B C.Topology error and bad data processing in generalized state estimation[J].IEEE Transactions on Power Systems,2015,30(6):3190-3200.
[18]JAEN A D L V,EXPOSITO A G.Implicitly constrained substation model for state estimation[J].IEEE Power Engineering Review,2007,22(6):57-57.
[19]ZHU J,ABUR A.Identification of network parameter errors[J].IEEE Transactions on Power Systems,2006,21(2):586-592.
[20]LIN Y,ABUR A.Enhancing network parameter error detection and correction via multiple measurement scans[J].IEEE Transactions on Power Systems,2017,32(3):2417-2425.
[21]BI T S,QIN X H,YANG Q X.A novel hybrid state estimator for including synchronized phasor measurements[J].Electric Power Systems Research,2008,78(8):1343-1352.
[22]NEJATI M,AMJADY N,ZAREIPOUR H.A new stochastic search technique combined with scenario approach for dynamic state estimation of power systems[J].IEEE Transactions on Power Systems,2012,27(4):2093-2105.
[23]CLEMENTS K A,COSTA A S.Topology error identification using normalized Lagrange multipliers[J].IEEE Transactions on Power Systems,2002,13(2):347-353.