A Review of Advancements in AI-Based Control Techniques for Microgrids

Abstract

Microgrids are among the most important sources of energy in developing countries, and their operation and management have become a key issue in the transition towards a sustainable and resilient energy future. The integration of artificial intelligence- (AI-) based control techniques offers unprecedented opportunities for enhancing energy resilience, sustainability, and efficiency. In this review paper, we provide insights into the recent developments and applications of AI-based control technologies for microgrid systems, including predictive energy management, distributed control architectures, adaptive learning, fault detection, and cybersecurity. The review of recent research highlights the effectiveness of AI in addressing key challenges in the operation and managing of microgriders, including distributed control strategies, and intelligent decision-making processes supported by robust algorithms, and communication frameworks.