A Decomposition Algorithm for Large-Scale Security-Constrained AC Optimal Power Flow

TL;DR

This paper introduces a decomposition algorithm tailored for large-scale security-constrained AC optimal power flow problems, emphasizing techniques that enhance computational efficiency and robustness in power system optimization.

Contribution

The paper presents a novel decomposition approach incorporating contingency selection, fast evaluation, and parallelism, specifically designed for large-scale security-constrained AC optimal power flow.

Findings

The proposed algorithm outperforms alternative strategies in numerical experiments.

Effective contingency handling improves solution speed and reliability.

Parallel processing significantly reduces computation time.

Abstract

A decomposition algorithm for solving large-scale security-constrained AC optimal power flow problems is presented. The formulation considered is the one used in the ARPA-E Grid Optimization (GO) Competition, Challenge 1, held from November 2018 through October 2019. The techniques found to be most effective in terms of performance in the challenge are presented, including strategies for contingency selection, fast contingency evaluation, handling complementarity constraints, avoiding issues related to degeneracy, and exploiting parallelism. The results of numerical experiments are provided to demonstrate the effectiveness of the proposed techniques as compared to alternative strategies.