Smart distribution power losses estimation: A hybrid state estimation approach

This paper presents a method to estimate and identify technical and non-technical power losses in distribution systems based in a hybrid state estimation approach. The proposed method is divided in two steps. In the first step, non-technical power losses are detected, identified and corrected using a geometrical based state estimator technique. In the second step, a pattern recognition technique is applied on consumers aiming intelligent weight of load measurements. On this second step, power losses are estimated with the updated weight matrix. The proposed approach was numerically analyzed in a 69-bus distribution system considering an advanced metering infrastructure. The results show a potential improvement of the proposed method when compared with the state-of-the-art residual based state estimator approach.

[1]  Newton G. Bretas,et al.  A two steps procedure in state estimation gross error detection, identification, and correction , 2015 .

[2]  Julio Romero Aguero Improving the efficiency of power distribution systems through technical and non-technical losses reduction , 2012, T&D 2012.

[3]  VARUN CHANDOLA,et al.  Anomaly detection: A survey , 2009, CSUR.

[4]  Newton Geraldo Bretas,et al.  Bad data analysis in distribution state estimation considering load models , 2015, 2015 IEEE Power & Energy Society General Meeting.

[5]  Arturo S. Bretas,et al.  HYBRID FORMULATION FOR TECHNICAL AND NON-TECHNICAL LOSSES ESTIMATION AND IDENTIFICATION IN DISTRIBUTION NETWORKS: APPLICATION IN A BRAZILIAN POWER SYSTEM , 2015 .

[6]  C C O Ramos,et al.  A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest , 2011, IEEE Transactions on Power Systems.

[7]  Nelson Kagan,et al.  A new method for the computation of technical losses in electrical power distribution systems , 2001 .

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

[9]  Chan-Nan Lu,et al.  Non-technical loss detection using state estimation and analysis of variance , 2013, 2013 IEEE Power & Energy Society General Meeting.

[10]  Newton G. Bretas,et al.  A Geometrical View for Multiple Gross Errors Detection, Identification, and Correction in Power System State Estimation , 2013, IEEE Transactions on Power Systems.