Publication

Abstract : The Unit Commitment (UC) issue, a crucial optimization work in power system management, seeks to identify the best commitment schedule for power generating units over a given time horizon. By meeting demand while considering numerous operational restrictions, the UC problem is crucial in guaranteeing the reliable and economical functioning of power systems[1]. Researchers and practitioners have created a wide range of solutions to the UC issue over the years. The solution techniques used for Unit Commitment in power systems are thoroughly reviewed in this review paper. The study opens by providing a thorough formulation of the UC problem, considering factors such as demand variation, generator constraints, transmission limitations, and fuel costs. Subsequently, it discusses the key challenges associated with the UC problem, including computational complexity, uncertainty modeling, and the integration of renewable energy sources. The review then proceeds to categorize the existing solution methods for Unit Commitment into several classes, including mathematical programming, heuristic algorithms, metaheuristics, and hybrid approaches. The study presents an in-depth evaluation of sample strategies for each category, noting their advantages, disadvantages, and potential uses. Heuristic algorithms, such as dynamic programming, priority lists, and Lagrangian relaxation, offer effective solutions but could forgo optimality. A compromise between solution quality and computation time is provided by metaheuristic methods like genetic algorithms, particle swarm optimization, and simulated annealing.. Furthermore, the paper discusses recent advancements in solution methods that address the emerging challenges in Unit Commitment, such as the incorporation of renewable energy source.