Fully Distributed State Estimation for Wide-Area Monitoring Systems

This paper presents a fully distributed state estimation algorithm for wide-area monitoring in power systems. Through iterative information exchange with designated neighboring control areas, all the balancing authorities (control areas) can achieve an unbiased estimate of the entire power system's state. In comparison with existing hierarchical or distributed state estimation methods, the novelty of the proposed approach lies in that: 1) the assumption of local observability of all the control areas is no longer needed; 2) the communication topology can be different than the physical topology of the power interconnection; and 3) for DC state estimation, no coordinator is required for each local control area to achieve provable convergence of the entire power system's states to those of the centralized estimation. The performance of both DC and AC state estimation using the proposed algorithm is illustrated in the IEEE 14-bus and 118-bus systems.

[1]  Fred C. Schweppe,et al.  Power System Static-State Estimation, Part I: Exact Model , 1970 .

[2]  M. Ribbens-Pavella,et al.  A Two-Level Static State Estimator for Electric Power Systems , 1981, IEEE Transactions on Power Apparatus and Systems.

[3]  T. Van Cutsem,et al.  Critical Survey of Hierarchical Methods for State Estimation of Electric Power Systems , 1983, IEEE Power Engineering Review.

[4]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

[5]  Felix F. Wu,et al.  Power system state estimation: a survey , 1990 .

[6]  J. Teng,et al.  Distribution system state estimation , 1995 .

[7]  Fan Chung,et al.  Spectral Graph Theory , 1996 .

[8]  B. Gou,et al.  An Improved Measurement Placement Algorithm for Network Observability , 2001, IEEE Power Engineering Review.

[9]  Michael William Newman,et al.  The Laplacian spectrum of graphs , 2001 .

[10]  Mohammad Shahidehpour,et al.  Parallel and Distributed State Estimation , 2003 .

[11]  Yousef Saad,et al.  Iterative methods for sparse linear systems , 2003 .

[12]  A. Abur,et al.  Multi area state estimation using synchronized phasor measurements , 2005, IEEE Transactions on Power Systems.

[13]  Khosrow Moslehi,et al.  Power System Control Centers: Past, Present, and Future , 2005, Proceedings of the IEEE.

[14]  J. Moura,et al.  Cooperation for aggregating complex electric power networks to ensure system observability , 2008, 2008 First International Conference on Infrastructure Systems and Services: Building Networks for a Brighter Future (INFRA).

[15]  A. Gomez-Exposito,et al.  Two-Level State Estimation With Local Measurement Pre-Processing , 2009, IEEE Transactions on Power Systems.

[16]  Anjan Bose,et al.  Smart Transmission Grid Applications and Their Supporting Infrastructure , 2010, IEEE Transactions on Smart Grid.

[17]  Soummya Kar,et al.  Convergence Rate Analysis of Distributed Gossip (Linear Parameter) Estimation: Fundamental Limits and Tradeoffs , 2010, IEEE Journal of Selected Topics in Signal Processing.

[18]  Vahid Madani,et al.  Wide-Area Monitoring, Protection, and Control of Future Electric Power Networks , 2011, Proceedings of the IEEE.

[19]  George N Korres,et al.  A Distributed Multiarea State Estimation , 2011, IEEE Transactions on Power Systems.

[20]  Anjan Bose,et al.  Transition to a Two-Level Linear State Estimator—Part II: Algorithm , 2011, IEEE Transactions on Power Systems.

[21]  H. Vincent Poor,et al.  Distributed joint cyber attack detection and state recovery in smart grids , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[22]  Soummya Kar,et al.  Cooperative distributed state estimation: Local observability relaxed , 2011, 2011 IEEE Power and Energy Society General Meeting.

[23]  Le Xie,et al.  Fully distributed bad data processing for wide area state estimation , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[24]  Thierry Van Cutsem,et al.  A taxonomy of multi-area state estimation methods , 2011 .

[25]  R. Bass,et al.  Review: P. Billingsley, Convergence of probability measures , 1971 .

[26]  Antonio Gómez Expósito,et al.  A Multilevel State Estimation Paradigm for Smart Grids , 2011, Proceedings of the IEEE.

[27]  Soummya Kar,et al.  Distributed Parameter Estimation in Sensor Networks: Nonlinear Observation Models and Imperfect Communication , 2008, IEEE Transactions on Information Theory.

[28]  H. Vincent Poor,et al.  Distributed Linear Parameter Estimation: Asymptotically Efficient Adaptive Strategies , 2011, SIAM J. Control. Optim..

[29]  Robin Wilson,et al.  Modern Graph Theory , 2013 .