A Computationally Efficient Method for Solving Mixed-Integer AC Optimal Power Flow Problems

TL;DR

This paper introduces an efficient iterative method for solving complex mixed-integer AC optimal power flow problems, improving accuracy and scalability over existing approaches for practical power system applications.

Contribution

The paper presents a novel iterative deflation algorithm that solves relaxed problems and systematically eliminates candidate solutions, enhancing efficiency and accuracy in MI-AC-OPF problems.

Findings

Achieves higher solution accuracy than state-of-the-art methods.

Computational complexity grows linearly with integer variables.

Demonstrates scalability and practicality through simulations.

Abstract

Stepwise controllable devices, such as switched capacitors or stepwise controllable loads and generators, transform the nonconvex AC optimal power flow (AC-OPF) problem into a nonconvex mixed-integer (MI) programming problem which is generally hard to solve optimally. Existing methods for solving MI-AC-OPF problems usually suffer from either limited accuracy or computational intractability, making them impractical for real-world applications. To address these challenges, we propose an efficient iterative deflation approach providing high-quality approximate solutions. In each iteration, a continuously relaxed version of the MI-AC-OPF problem is solved and one candidate integer value is systematically eliminated based on the evaluation of a simple power flow result. The computational complexity of the proposed algorithm grows linearly with the number of integer optimization variables, ensuring scalability. Simulations demonstrate that the proposed approach achieves significant improvements in solution accuracy compared to a state-of-the-art approach. Thus, the proposed method is promising for solving practical MI-AC-OPF problems.