Solving unit commitment problem by using particle swarm optimization technique / Muhammad Aqil Ab Rahman

This paper proposed one of the Evolutionary Computation (EC) components which is Particle Swarm Optimization (PSO) in solving a problem of unit commitment (UC). In fact, one of the common problems in electrical power system is unit commitment (UC) which is complicated decision making for a various constraints and may affect the economical scheduling of units. Basically, the unit commitment problems involve scheduling on/off states of generating units, which minimizes the operating cost, start-up cost and shut-down cost as mentioned for various operating constraints. So, the objective of this study is to analyze and search for the UC schedule which generates minimum operational cost by using 10 generators. This system had been tested in satisfying the total output with load demand which is divided into number of small intervals of 24 hours. By using programming method, the problem of UC has been solved efficiently by a lot of discussion on PSO technique based on IEE Transaction on Power System data. Therefore, the optimal time and losses can be minimized which may affect the total cost operating by determining which and how many units should be operate in one time to meet a required load demand while satisfying specified operating criteria in order to reach an economic operation.