Failure Probability Constrained AC Optimal Power Flow

TL;DR

This paper introduces a reliability-aware AC optimal power flow model that minimizes cascade risk by constraining failure probabilities, leading to more resilient power dispatch solutions with minimal cost increase.

Contribution

It develops a novel failure probability-constrained ACOPF formulation using an analytical cascade failure model and efficient optimization techniques, enhancing power system reliability.

Findings

Significantly reduces cascade probabilities compared to traditional methods.

Maintains near-optimal costs with improved reliability.

Demonstrates effectiveness on IEEE 118-bus system simulations.

Abstract

Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting from any single component outage. By exploiting a recently developed analytical model of the probability of component failure, our Failure Probability-constrained ACOPF (FP-ACOPF) utilizes the system's expected first failure time as a smoothly tunable and interpretable signature of cascade risk. We use techniques from bilevel optimization and numerical linear algebra to efficiently formulate and solve the FP-ACOPF using off-the-shelf solvers. Extensive simulations on the IEEE 118-bus case show that, when compared to the unconstrained and N-1 security-constrained ACOPF, our probability-constrained dispatch points can significantly lower the probabilities of long severe cascades and of large demand losses, while incurring only minor increases in total generation costs.