Abstract：In multi-area interconnected power systems,the centralized estimation is difficult to implement because of the high state variable dimension and the large measurement data processing.This paper proposes a new algorithm of multi-area power system state estimation based on partial information fusion and estimate projection.In the proposed algorithm,each subarea individually obtains local estimates by implementing weighted least square iteration,and sends the local estimates of the boundary bus states to the coordination center.The coordination center applies least square fusion algorithm to calculate the coordinated estimates of total boundary bus states.According to the coordinated estimates of the boundary bus states,each subarea can further correct the local estimates of the internal states.The proposed algorithm can be implemented in the power system with PMU or without PMU.Moreover,the proposed algorithm only needs very few communication data,which also can be easy to implement.The test simulation results have proved that the proposed algorithm has good estimation accuracy and real-time property.
蔡永智, 陈皓勇, 万楚林. 基于局部信息融合和估计投影法的多区域电力系统状态估计[J]. 电工技术学报, 2017, 32(1): 69-77.
Cai Yongzhi,Chen Haoyong,Wan Chulin. Multi-Area Power System State Estimation Based on Partial Information Fusion and Estimate Projection. Transactions of China Electrotechnical Society, 2017, 32(1): 69-77.
[1] 马平川,沈沉,陈颖,等.基于伪量测型协调变量的分布式状态估计算法[J].中国电机工程学报,2014,34(19):3170-3177. Ma Pingchuan,Shen Chen,Chen Ying,et al.Distributed state estimation based on the pseudo-measurement coordination variables[J].Proceedings of the CSEE,2014,34(19):3170-3177. [2] 卫志农,周奕,李阳林,等.基于信息融合理论的动态状态估计探讨[J].电力系统自动化,2008,32(4):103-107. Wei Zhinong,Zhou Yi,Li Yanglin,et al.Discussion on dynamic state estimation based on information fusion theory[J].Automation of Electric Power Systems,2008,32(4):103-107. [3] Antonio Gomez Exposito,Antonio de la Villa Jaen,Catalina Gomez Quiles.A taxonomy of multi-area state estimation methods[J].Electric Power Systems Research,2011,81(4):1060-1069. [4] Korres G N,Contaxis C C.Application of a reduced model to a distributed state estimator[C]//IEEE Power Engineering Society Winter Meeting,2000:999-1004. [5] Yang X,Zhang X P.Fast decoupled multi area state estimation with PMUs measurements[C]//Innovative Smart Grid Technologies-Asia (ISGT Asia),Tianjin,China,2012:1-7. [6] Jiang Weiqiang,Vittal V,Heydt G T.A distributed state estimator utilizing synchronized phasor measurements[J].IEEE Transactions on Power Systems,2007,22(2):563-571. [7] Yang X,Zhang X P,Zhou S.Coordinated algorithms for distributed state estimation with synchronized phasor measurements[J].Applied Energy,2012,96:253-260. [8] Kurzyn M S.Real time estimation for large-scale power systems[J].IEEE Transactions on Power Apparatus and Systems,1983,102(7):2055-2063. [9] 王永,郭志忠,彭茂君,等.基于分区协调算法的互联电力系统状态估计[J].电网技术,2008,32(10):79-83. Wang Yong,Guo Zhizhong,Peng Maojun,et al.A new decomposition and coordination algorithm for state estimation in interconnected power system[J].Power System Technology,2008,32(10):79-83. [10]卢志刚,张静,程慧琳,等.基于分解协调及外网等值的多代理状态估计[J].电力系统自动化,2012,36(14):23-29. Lu Zhigang,Zhang Jing,Cheng Huilin,et al.Multi-agent state estimation based on decomposition and coordination and external network concentration equivalence[J].Automation of Electric Power Systems,2012,36(14):23-29. [11]王永,郭志忠,彭茂君,等.基于灵敏度分析的多区域互联电力系统状态估计[J].电力系统自动化,2007,31(19):27-31. Wang Yong,Guo Zhizhong,Peng Maojun,et al.State estimation of a multi-area interconnected power system based on sensitivity analysis[J].Automation of Electric Power Systems,2007,31(19):27-31. [12]张海波,易文飞.基于异步迭代模式的电力系统分布式状态估计方法[J].电力系统自动化,2014,38(9):125-131. Zhang Haibo,Yi Wenfei.Distributed state estimation method for power systems based on asynchronous iteration mode[J].Automation of Electric Power Systems,2014,38(9):125-131. [13]王建,陈颖,黄少伟,等.基于KKT条件分解的互联电网分布式状态估计算法[J].电力系统自动化,2010,34(19):31-36. Wang Jian,Chen Ying,Huang Shaowei,et al.A distributed state estimation method for interconnected power grid based on decomposition of KKT condition[J].Automation of Electric Power Systems,2010,34(19):31-36. [14]Gonzalez X,Ramirez J M,Marmolejo J A,et al.Methodology for multiarea state estimation solved by a decomposition method[J].Electric Power Systems Research,2015(123):92-99. [15]Kekatos V,Giannakis G B.Distributed robust power system state estimation[J].IEEE Transactions on Power Systems,2013,28(2):1617-1626. [16]Xie Le,Choi D H,Kar S,et al.Fully distributed state estimation for wide-area monitoring systems[J].IEEE Transactions on Smart Grid,2012,3(3):1154-1169. [17]Jiang W,Vittal V,Heydt G T.A distributed state estimator utilizing synchronized phasor measurements[J].IEEE Transactions on Power Systems,2007,22(2):563-571. [18]Ebrahimian R,Baldick R.State estimation distributed processing[J].IEEE Transactions on Power Systems,2000,15(4):1240-1246. [19]Zhao Liang,Abur A.Multi-area state estimation using synchronized phasor measurements[J].IEEE Transactions on Power Systems,2005,20(2):611-617. [20]Korres G H.A distributed multi-area state estimation[J].IEEE Transactions on Power Systems,2011,26(1):73-84. [21]邱家驹.分布式状态估计[J].电力系统自动化,1988,12(6):35-42. Qiu Jiaju.The distributed state estimation[J].Automation of Electric Power Systems,1988,12(6):35-42. [22]Noack B,Sijs J,Hanebeck U D.Fusion strategies for unequal state vectors in distributed kalman filtering[C]//The International Federation of Automatic Control,Cape Town,South Africa,2014:3262-3267. [23]Simon D.Kalman filtering with state constraints:a survey of linear and nonlinear algorithms[J].IET Control Theory and Applications,2010,4(8):1303-1318. [24]李滨,杜孟远,祝云,等.基于准实时数据的智能配电网状态估计[J].电工技术学报,2016,31(1):34-44. Li Bin,Du Mengyuan,Zhu Yun,et al.A state estimator for smart distribution networks with Quasi-real time data[J].Transactions on China Electrotechnical Society,2016,31(1):34-44. [25]毕天姝,陈亮,薛安成,等.基于鲁棒容积卡尔曼滤波器的发电机动态状态估计[J].电工技术学报,2016,31(4):163-169. Bi Tianshu,Chen Liang,Xue Ancheng,et al.Dynamic state estimator for synchronous machines based on robust cubature kalman filter[J].Transactions on China Electrotechnical Society,2016,31(4):163-169.
2017, Vol. 32 
