Toward Efficient Wide-Area Identification of Multiple Element Contingencies in Power Systems

TL;DR

This paper introduces a novel method combining Line Outage Distribution Factors and group betweenness centrality to efficiently identify critical contingencies in large power systems, addressing the exponential complexity challenge.

Contribution

It presents a new approach that constructs subgraphs with distance and search parameters, improving the identification of critical elements far from initial outages.

Findings

Successfully applied to 200- and 500-bus systems

Effectively identifies multiple N-x contingencies causing violations

Reduces computational complexity compared to exhaustive methods

Abstract

Power system N-x contingency analysis has inherent challenges due to its combinatorial characteristic where outages grow exponentially with the increase of x and N. To address these challenges, this paper proposes a method that utilizes Line Outage Distribution Factors (LODFs) and group betweenness centrality to identify subsets of critical branches. The proposed LODF metrics are used to select the high-impact branches. Based on each selected branch, the approach constructs the subgraph with parameters of distance and search level, while using branches' LODF metrics as the weights. A key innovation of this work is the use of the distance and search level parameters, which allow the subgraph to identify the most coupled critical elements that may be far away from a selected branch. The proposed approach is validated using the 200- and 500-bus test cases, and results show that the proposed approach can identify multiple N-x contingencies that cause violations.