Quantifying Distribution System State Estimation Accuracies Achieved By Adding Telemetry and Operational Forecasting

Abstract

Distribution System State Estimation (DSSE) is a fundamental application for the realization of other Distribution Management System (DMS) applications such as Volt-Var Optimization (VVO) and Fault Location Isolation and Service Restoration (FLISR). The small number of sensors typically available on distribution circuits and consequential scarcity of field data presents a major challenge for DSSE, and it is crucial that the few sensors available are placed at optimal locations in order to maximize DSSE accuracy. Electric distribution utilities lack a methodology that allows them to evaluate the DSSE performance based on sensor placement strategies and other operational measures such as forecasting improvement. This paper presents a Monte Carlo simulation based DSSE performance evaluation methodology that allows utilities to quantify the accuracy of DSSE results for simulated sensor placement scenarios. The methodology provides a basis for the selection of sensor placements that provide DSSE results that are sufficiently accurate to support DMS applications.