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2019 SoutheastCon - Quantifying Distribution System State Estimation Accuracies Achieved By Adding Telemetry and Operational Forecasting by Humayun, Muhammad; Schoene, Jens; Poudel, Bikash; Russell, Brenden; Sun, Gary; Bui, Josh; Salazar, Armando; Badayos, Noah; Lak, Moein; Clarke, Christopher R.; Zhong, Minqi is a scholarly article available to read on EtoBox.

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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.

Author

Humayun, Muhammad; Schoene, Jens; Poudel, Bikash; Russell, Brenden; Sun, Gary; Bui, Josh; Salazar, Armando; Badayos, Noah; Lak, Moein; Clarke, Christopher R.; Zhong, Minqi

Publisher

IEEE

Published

2019

Language

EN