This monograph is a research compendium on the modelling, control, fault diagnosis, and optimization of electric machines, renewable energy systems, and microgrids using advanced computational methods and metaheuristic algorithms, such as genetic algorithms (GA), particle swarm optimization (PSO) algorithms, artificial bee colony (ABC) algorithms, runner root (RR) algorithms, and cuckoo search (CS) algorithms. Intelligent Optimization in Electric Machines, Renewable Energy Systems, and Microgrids offers in-depth analysis of core components, including parameter estimation and energy-efficient control of induction machines, along with the modelling and maximum power point tracking (MPPT) of solar photovoltaic (PV) and wind energy systems. The book also covers modern techniques for fault location in transmission lines, the optimization of hybrid renewable energy systems, and the planning and control of microgrids. Designed for power systems engineers, researchers, academics, and students, this book offers the practical knowledge and advanced methodologies needed to address the most pressing challenges in a modern grid. It is an ideal textbook for graduate courses in electric power systems, renewable energy systems, and microgrids, providing both theoretical foundations and real-world applications.