Metaheuristic Optimization Review MOR 3066-280X 10.54216/MOR https://www.americaspg.com/journals/show/3408 2024 2024 Electrical Engineering Department, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt Mohammed Mohammed Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia Amal H. Alharbi Smart electrical grids (SGs) have emerged to advance the management of power systems by solving issues such as voltage instability, reactive loads, power loss, and the integration of renewable energy resources. This review focuses on the applicability of metaheuristic algorithms to energy distribution systems, improve operation, and overcome the repercussions affecting the environment and overall costs. PSO, GA, and GWO have been identified for their effectiveness in dealing with the complexity of PS due to the nonlinear and dynamic nature of today's energy systems. The review also addresses the extension of methods in machine learning for enhancing load forecasting and real-time energy control, which are key factors for shifting to innovative and renewable energy systems. Based on the literature review of the state of the art over the last five years, this research highlights some achievements and limitations. It provides recommendations for further directions in advancing Smart Grid algorithms. These results highlight the use of meta-heuristics in redesigning processes that offer optimal, reliable and sustainable energy facilities. 2024 2024 42 52 10.54216/MOR.020104 https://www.americaspg.com/articleinfo/41/show/3408