A PSO-Optimized ANFIS-Based Control Strategy for DC Bus Voltage Regulation in PV-Battery DC Microgrids

Abstract

This paper addresses the challenge of DC bus voltage regulation in a photovoltaic (PV)-battery DC microgrid operating under variable solar irradiance conditions. The intermittent nature of solar energy and the bidirectional power exchange with the battery make stable DC bus voltage regulation particularly difficult to achieve. To overcome these challenges, an advanced control strategy combining a Sugeno-type Adaptive Neuro-Fuzzy Inference System (ANFIS) with Particle Swarm Optimization (PSO) is proposed. The ANFIS controller captures system nonlinearities, while PSO is employed to tune the input scaling gains and the output correction gain of the ANFIS-based voltage regulation loop, contributing to competitive voltage regulation performance and improved transient response. In addition, an energy management scheme based on state-of-charge (SOC) constraints is integrated to ensure safe battery operation by preventing overcharging and deep discharge. Simulation results under varying irradiance conditions and an additional sudden load-change disturbance scenario demonstrate that the proposed approach maintains the DC bus voltage around the reference value of 230 V, while achieving efficient power extraction and reliable energy management. Furthermore, the proposed strategy supports stable system operation and improved transient response under the considered irradiance-varying and load-step operating conditions.