Performance Assessment of Linear State Estimators Using Synchrophasor Measurements

This paper aims to assess the performance of linear state estimation (SE) processes of power systems relying on synchrophasor measurements. The performance assessment is conducted with respect to two different families of SE algorithms, i.e., static ones represented by weighted least squares (WLS) and recursive ones represented by Kalman filter (KF). To this end, this paper firstly recalls the analytical formulation of linear WLS state estimator (LWLS-SE) and Discrete KF state estimator (DKF-SE). We formally quantify the differences in the performance of the two algorithms. The validation of this result, together with the comprehensive performance evaluation of the considered state estimators, is carried out using two case studies, representing distribution (IEEE 123-bus test feeder) and transmission (IEEE 39-bus test system) networks. As a further contribution, this paper validates the correctness of the most common process model adopted in DKF-SE of power systems.

[1]  Mario Paolone,et al.  Efficient Computation of Sensitivity Coefficients of Node Voltages and Line Currents in Unbalanced Radial Electrical Distribution Networks , 2012, IEEE Transactions on Smart Grid.

[2]  Atif S. Debs,et al.  A Dynamic Estimator for Tracking the State of a Power System , 1970 .

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

[4]  A. Monticelli.  State estimation in electric power systems : a generalized approach , 1999 .

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

[6]  A. Rouhani,et al.  Tracking the machine states using a linear phasor estimator assisted dynamic state estimator , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.

[7]  M. Pau,et al.  WLS distribution system state estimator based on voltages or branch-currents: Accuracy and performance comparison , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[8]  C. Muscas,et al.  GPS-based System for the Measurement of Synchronized Harmonic Phasors , 2007, 2007 IEEE Instrumentation & Measurement Technology Conference IMTC 2007.

[9]  R. Cherkaoui,et al.  Probabilistic assessment of the process-noise covariance matrix of discrete Kalman filter state estimation of active distribution networks , 2014, 2014 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).

[10]  A.G. Phadke,et al.  Hybrid Linear State Estimation Utilizing Synchronized Phasor Measurements , 2007, 2007 IEEE Lausanne Power Tech.

[11]  Paolo Attilio Pegoraro,et al.  Effects of Measurements and Pseudomeasurements Correlation in Distribution System State Estimation , 2014, IEEE Transactions on Instrumentation and Measurement.

[12]  Junqi Liu,et al.  Trade-Offs in PMU Deployment for State Estimation in Active Distribution Grids , 2012, IEEE Transactions on Smart Grid.

[13]  K. Schneider,et al.  Feasibility studies of applying Kalman Filter techniques to power system dynamic state estimation , 2007, 2007 International Power Engineering Conference (IPEC 2007).

[14]  Mario Paolone,et al.  Enhanced Interpolated-DFT for Synchrophasor Estimation in FPGAs: Theory, Implementation, and Validation of a PMU Prototype , 2014, IEEE Transactions on Instrumentation and Measurement.

[15]  Przemyslaw Komarnicki,et al.  Observability of the distribution system , 2009 .

[16]  I. Kamwa,et al.  Dynamic State Estimation in Power System by Applying the Extended Kalman Filter With Unknown Inputs to Phasor Measurements , 2011, IEEE Transactions on Power Systems.

[17]  Greg Welch,et al.  Reduced Measurement-space Dynamic State Estimation (ReMeDySE) for power systems , 2011, 2011 IEEE Trondheim PowerTech.

[18]  A.H. Nielsen,et al.  Monitoring of power system events at transmission and distribution level , 2006, IEEE Transactions on Power Systems.

[19]  R.J. Best,et al.  Differential ROCOF relay for Loss-of-Mains protection of Renewable Generation using phasor measurement over Internet Protocol , 2009, 2009 CIGRE/IEEE PES Joint Symposium Integration of Wide-Scale Renewable Resources Into the Power Delivery System.

[20]  Nikolaos M. Manousakis,et al.  A two-stage state estimator for power systems with PMU and SCADA measurements , 2013, 2013 IEEE Grenoble Conference.

[21]  R. Mehra.  On the identification of variances and adaptive Kalman filtering , 1970 .

[22]  Thierry Van Cutsem,et al.  Reconstructing and tracking network state from a limited number of synchrophasor measurements , 2013, IEEE Transactions on Power Systems.

[23]  Antonello Monti,et al.  Multiarea Distribution System State Estimation , 2015, IEEE Transactions on Instrumentation and Measurement.

[24]  R. Podmore,et al.  A Practical Method for the Direct Analysis of Transient Stability , 1979, IEEE Transactions on Power Apparatus and Systems.

[25]  Jean-Yves Le Boudec.  Performance Evaluation of Computer and Communication Systems , 2010, Computer and communication sciences.

[26]  W. H. Kersting,et al.  Radial distribution test feeders , 1991, 2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194).

[27]  M. Najim.  Modeling, Estimation and Optimal Filtering in Signal Processing , 2008 .

[28]  Mario Paolone,et al.  A Hardware-in-the-Loop test platform for the performance assessment of a PMU-based Real-Time State Estimator for Active Distribution Networks , 2015, 2015 IEEE Eindhoven PowerTech.

[29]  P. S. Georgilakis,et al.  Taxonomy of PMU Placement Methodologies , 2012, IEEE Transactions on Power Systems.

[30]  Boming Zhang,et al.  Global state estimation for whole transmission and distribution networks , 2005 .

[31]  Sara Sulis,et al.  On the Measurement of Power Quality Indexes for Harmonic Distorsion in the Presence of Capacitors”, IEEE Transactions on Instrumentation and Measurement , 2007 .

[32]  M.E. Baran,et al.  A branch-current-based state estimation method for distribution systems , 1995 .

[33]  James S. Thorp,et al.  Three-phase linear state estimation using Phasor Measurements , 2013, 2013 IEEE Power & Energy Society General Meeting.

[34]  Marco Liserre,et al.  Integrated voltage control and line congestion management in Active Distribution Networks by means of smart transformers , 2014, 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE).

[35]  Ali Reza Seifi,et al.  A new coordinated approach to state estimation in integrated power systems , 2013 .

[36]  G. T. Heydt,et al.  A Linear State Estimation Formulation for Smart Distribution Systems , 2013, IEEE Transactions on Power Systems.

[37]  Amit Jain,et al.  Power system tracking and dynamic state estimation , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[38]  Greg Welch,et al.  A Two-Stage Kalman Filter Approach for Robust and Real-Time Power System State Estimation , 2014, IEEE Transactions on Sustainable Energy.

[39]  Mario Paolone,et al.  State estimation of Active Distribution Networks: Comparison between WLS and iterated kalman-filter algorithm integrating PMUs , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[40]  D John Morrow,et al.  Synchrophasor Broadcast Over Internet Protocol for Distributed Generator Synchronization , 2010, IEEE Transactions on Power Delivery.

[41]  David E. Culler,et al.  Micro-synchrophasors for distribution systems , 2014, ISGT 2014.

[42]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[43]  Mario Paolone,et al.  A Synchrophasor Estimation Algorithm for the Monitoring of Active Distribution Networks in Steady State and Transient Conditions , 2011 .

[44]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[45]  A. Abur,et al.  Observability analysis and measurement placement for systems with PMUs , 2004, IEEE PES Power Systems Conference and Exposition, 2004..

[46]  N. Singh,et al.  Power system modelling and analysis in a mixed energy management and distribution management system , 1998 .

[47]  X. Rong Li,et al.  Joint Estimation of State and Parameter With Synchrophasors—Part I: State Tracking , 2011, IEEE Transactions on Power Systems.

[48]  Mario Paolone,et al.  Real-time state estimation of the EPFL-campus medium-voltage grid by using PMUs , 2015, 2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT).

[49]  James B. Rawlings,et al.  A new autocovariance least-squares method for estimating noise covariances , 2006, Autom..

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

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

[52]  Venkatarama Krishnan,et al.  Nonlinear filtering and smoothing: An introduction to martingales, stochastic integrals, and estimation , 1984 .