Impact of Transformer Correlations in State Estimation Using the Unscented Transformation

This paper addresses the power system state estimation problem considering the correlations among instrument transformer signals. The correlations among processed measurements are estimated using the Unscented Transformation given the correlation and basic statistical information of internal measurements. In addition, the paper analyzes the impact of these correlations on the estimated states using the IEEE 118-bus test system under various operating conditions and measurement configurations.

[1]  Felix F. Wu,et al.  Estimation of parameter errors from measurement residuals in state estimation (power systems) , 1992 .

[2]  A. Conejo,et al.  State estimation via mathematical programming: a comparison of different estimation algorithms , 2012 .

[3]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[4]  Douglas P. Wiens,et al.  Designs for weighted least squares regression, with estimated weights , 2013, Stat. Comput..

[5]  A. Conejo,et al.  Calculation of Measurement Correlations Using Point Estimate , 2010, IEEE Transactions on Power Delivery.

[6]  Yu Erkeng,et al.  Novel algorithms to estimate and adaptively update measurement error variance using power system state estimation results , 1998 .

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

[8]  Antonio J. Conejo,et al.  Robust WLS estimator using reweighting techniques for electric energy systems , 2013 .

[9]  D. Simon.  Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[10]  Bikash C. Pal,et al.  Iteratively reweighted least-squares implementation of the WLAV state-estimation method , 2004 .

[11]  A. Abur,et al.  Auto tuning of measurement weights in WLS state estimation , 2004, IEEE Transactions on Power Systems.

[12]  J. Hammersley.  SIMULATION AND THE MONTE CARLO METHOD , 1982 .

[13]  Antonio J. Conejo,et al.  Probabilistic power flow with correlated wind sources , 2010 .

[14]  Lamine Mili,et al.  Iteratively reweighted least-squares state estimation through Givens Rotations , 1999 .

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

[16]  B. Stott,et al.  Generalized state estimation [power systems] , 1997, Proceedings of the 20th International Conference on Power Industry Computer Applications.

[17]  Fred C. Schweppe,et al.  Power System Static-State Estimation, Part III: Implementation , 1970 .

[18]  Lamine Mili,et al.  Robust state estimation of electric power systems , 1994 .

[19]  O. Alsaç,et al.  Generalized state estimation , 1998 .

[20]  A. Monticelli,et al.  Electric power system state estimation , 2000, Proceedings of the IEEE.

[21]  M. Irving,et al.  Robust Algorithm for Generalized State Estimation , 2009, IEEE Transactions on Power Systems.

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

[23]  A. Abur,et al.  Breaker Status Identification , 2010, IEEE Transactions on Power Systems.

[24]  A. G. Expósito,et al.  Power system state estimation : theory and implementation , 2004 .

[25]  P. Gill,et al.  MINOS: A Solver for Large-Scale Nonlinear Optimization Problems , 2002 .

[26]  S. Chakrabarti,et al.  A Constrained Formulation for Hybrid State Estimation , 2011, IEEE Transactions on Power Systems.

[27]  Lamine Mili,et al.  Algorithms for least median of squares state estimation of power systems , 1992, [1992] Proceedings of the 35th Midwest Symposium on Circuits and Systems.

[28]  Fred C. Schweppe,et al.  Power System Static-State Estimation, Part II: Approximate Model , 1970 .

[29]  K. A. Clements,et al.  Topology error identification using normalized Lagrange multipliers , 1998 .

[30]  Simon J. Julier,et al.  Skewed approach to filtering , 1998, Defense, Security, and Sensing.

[31]  W.-H. E. Liu,et al.  Parameter error identification and estimation in power system state estimation , 1995 .

[32]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[33]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[34]  A. Conejo,et al.  Power System State Estimation Considering Measurement Dependencies , 2009, IEEE Transactions on Power Systems.

[35]  G. Andersson,et al.  Multiple Bad Data Identification Considering Measurement Dependencies , 2011, IEEE Transactions on Power Systems.

[36]  Antonio Gómez Expósito,et al.  Reduced Substation Models for Generalized State Estimation , 2001 .