Optimization of Power Systems Using AI: A Review of Modern Approaches

Abstract

This review paper reviews recent Artificial Intelligence (AI) techniques for power system optimization. It underscores the shortcomings of conventional approaches and stresses the importance of AI approaches such as machine learning, evolutionary algorithms, swarm intelligence and deep learning in addressing complex problems such as economic dispatch, unit commitment and optimal power flow. The research also explores applications for renewable energy, smart grids, and demand response. Challenges such as data quality, computational efficiency and interpretability are discussed. Emerging challenges include explainable AI, real-time operation, and hybrid approaches. In conclusion, AI improves efficiency, reliability, and sustainability of power systems.