Online Voltage Control of DC Microgrids with Different Loading Conditions Using Particle Swarm Optimization

Abstract

This paper presents a contemplate study on online voltage control strategy with different loading conditions in a DC microgrid using particle swarm optimization (PSO). DC microgrids consist of many converters and it is an important issue to stabilize network voltage by properly designing their controllers. Conventional feedback controls have been often used as a primary control for voltage stabilization with optimizing control parameters such as droop gains. Moreover, the optimal control parameters should be flexibly updated when the system condition dynamically changes so as to maintain high voltage control performance under sudden and unexpected changes in system conditions. In that context, this paper introduces an online voltage control using an advanced PSO technique to frequently update control gains. The primary control was modeled as a proportional‐derivative controller, and the optimization problem was defined based on the eigenvalue analysis. A parallel operation of local and global searches is conducted in the proposed method to search optimal control gains by allocating a part of particles to move in a random pattern. The validation of the proposed method was performed using a simplified 3‐bus DC microgrid model with two generator sets and two constant power loads. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.