A Power System State Estimation Technique in Consideration of Network Topology

In this paper, a new method is proposed for network topology identification in power systems. The proposed method is based on tabu search (TS) and state estimation with the L1-norm. The North American blackout occurred in August 2003 brings about a new aspect that topology identification plays a key role in security control. This paper introduces the Boolean algebra into state estimation to deal with topological state. That allows power system operators to carry out reliable state estimation in a sense that network topology is identified while estimate is evaluated. In this paper, the mathematical formulation may be expressed as a nonlinear mixed integer programming problem. To solve it, this paper makes use of TS and the L1-norm state estimator. TS is useful for solving a combinatorial optimization problem efficiently. The L1-norm estimator gives a reliable solution as a robust state estimation method. The proposed method is successfully applied to the IEEE 14-node and 57-node systems.

[1]  A. Abur,et al.  A fast algorithm for the weighted least absolute value state estimation (for power systems) , 1991 .

[2]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[3]  Felix F. Wu,et al.  Detection of topology errors by state estimation (power systems) , 1989 .

[4]  E.E. Fetzer,et al.  Observability in the state estimation of power systems , 1975, IEEE Transactions on Power Apparatus and Systems.

[5]  Hiroyuki Mori,et al.  Recent trends of meta-heuristics applications in power systems , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[6]  Elizete M. Lourenco,et al.  GEOMETRICALLY-BASED HYPOTHESIS TESTING FOR TOPOLOGY ERROR IDENTIFICATION , 2002 .

[7]  M. Vidyasagar,et al.  Bad Data Rejection Properties of Weughted Least Absolute Value Techniques Applied to Static State Estimation , 1982, IEEE Transactions on Power Apparatus and Systems.

[8]  Y. Hassaine,et al.  Identification of the topology of power system networks via mixed integer inequalities , 2004, IEEE Power Engineering Society General Meeting, 2004..

[9]  M. Ribbens-Pavella,et al.  Critical Survey of Hierarchical Methods for State Estimation of Electric Power Systems , 1983, IEEE Transactions on Power Apparatus and Systems.

[10]  Felix F. Wu,et al.  Detection of Topology Errors by State Estimation , 1989, IEEE Power Engineering Review.

[11]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[12]  Fernando L. Alvarado,et al.  Weighted Least Absolute Value state estimation using interior point methods , 1994 .

[13]  Simulation Algorithm.  Detection ofTopology Errors byState Estimation , 1989 .

[14]  E. Handschin,et al.  Bad data analysis for power system state estimation , 1975, IEEE Transactions on Power Apparatus and Systems.

[15]  Fen Wu,et al.  RECENT PROGRESS IN REAL-TIME NETWORK SECURITY ANALYSIS , 1987 .

[16]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[17]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[18]  O. Alsac,et al.  Fast Decoupled Load Flow , 1974 .

[19]  A. Abur,et al.  A fast algorithm for the weighted least absolute value state estimation , 1991, IEEE Power Engineering Review.

[20]  G. Krumpholz,et al.  Power System Observability: A Practical Algorithm Using Network Topology , 1980, IEEE Transactions on Power Apparatus and Systems.