Enhancing topology error detection via multiple measurement scans

Abstract

In today’s energy management systems, the network model being fed into state estimation (SE) is assumed to be free of topology errors. In this conventional approach, bus-branch (BB) models are created as electrical equivalents of the actual network. If any topology error goes undetected while forming BB models, the subsequent SE solution will be either biased or divergent. To deal with topology errors, in this paper, a topology tracking method, using the detailed node-breaker (NB) models, is formulated. In large systems, it is computationally intensive to run SE and the following bad data tests. Therefore, SE analysis is carried out every few minutes, which is less frequent than the measurement updates (every few seconds). Since contingencies develop quickly (less than a second), the switching device flows in a few substations can change significantly from one measurement scan to the next. To identify the substation most impacted by the event, an efficient SE procedure based on the Lasso (least absolute shrinkage and selection operator) method is developed. Then, the correct topology is obtained by running a localized SE centered around the identified substation. The efficacy of the proposed approach is demonstrated both in a small 13-bus and a large 300-bus IEEE test cases.