Two-Stage Homotopy Method to Incorporate Discrete Control Variables into AC-OPF

TL;DR

This paper introduces a two-stage homotopy algorithm for solving AC-OPF problems that include discrete control variables, enabling more accurate modeling of power grid controls without prior knowledge of settings.

Contribution

The paper presents a novel two-stage homotopy method that effectively incorporates discrete control variables into AC-OPF without requiring initial guesses or prior control settings.

Findings

Outperforms existing solvers on large networks

Successfully handles switched shunts and adjustable transformers

Maintains robustness without prior control setting knowledge

Abstract

Alternating-Current Optimal Power Flow (AC-OPF) is an optimization problem critical for planning and operating the power grid. The problem is traditionally formulated using only continuous variables. Typically, control devices with discrete-valued settings, which provide valuable flexibility to the network and improve resilience, are omitted from AC-OPF formulations due to the difficulty of integrality constraints. We propose a two-stage homotopy algorithm to solve the AC-OPF problem with discrete-valued control settings. This method does not rely on prior knowledge of control settings or other initial conditions. The first stage relaxes the discrete settings to continuous variables and solves the optimization using a robust homotopy technique. Once the solution has been obtained using relaxed models, second homotopy problem gradually transforms the relaxed settings to their nearest feasible discrete values. We test the proposed algorithm on several large networks with switched shunts and adjustable transformers and show it can outperform a similar state-of-the-art solver.