Unit Commitment Problem with Emission Cost Constraints by Using Genetic Algorithm

A power system’s operating cost needs to be minimized by satisfying varying load demand while taking into account the prevailing constraints in a multiple unit electrical system. In this study, using genetic algorithms (GA), short-term thermal commitment problem was solved and an economical generating schedule made with solution obtained. Taking negative effects of emissions due use fossil fuels, emission costs were added objective function together fuel start-up costs. The GA chromosome structure formed binary encoding, new generations selected roulette wheel selection mechanism single point crossover applied. representation, formulation simulation results for 5-unit test system during scheduling hours period are presented. number units committed determined constraints. During planning period, 13360 MW met 755 spinning reserve. Total calculated as $430330. Of total cost, 32% consists