Seamless Operation of Microgrid Using PI Controller Based on Artificial Neural Network

This paper explores seamless operation of microgrids through the integration of artificial (ANN) and particle swarm optimization (PSO) algorithms. Microgrids, pivotal for enhancing energy efficiency, reliability, and resilience in power systems, benefit from a sophisticated and adaptive control strategy. The ANN, a powerful tool for modeling complex systems, enhances real-time control by learning and adapting to the dynamic nature of microgrid operation. The synergistic integration of the ANN controller and PSO algorithm leverage their respective strengths, providing a baseline for stability and an adaptive component for learning and adjusting to changing operational scenarios. The proposed approach demonstrates computational efficiency and speed, contributing to the microgrid’s swift response to disturbances. Experimental results highlight the effectiveness of this integrated approach, showcasing improved performance over traditional control methods.