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Unit commitment problem is associated with satisfying load demand and minimizing the total operating cost of the generating unit without violation of unit and system constraints. The solution of unit commitment should be reliable which has adequate spinning reserve in order to anticipate the uncertainty issue. This research proposes a method to handle two uncertainty issues, i.e. unit unavailability and load forecast uncertainty. The unit commitment problem is solved by genetic algorithm with priority list approach. The evaluation of spinning reserve capacity is based on probabilistic criterion by incorporating two reliability indices, i.e. loss of load probability (LOLP) and expected unserved energy (EUE). The effectiveness of the proposed method is tested using IEEE Reliability Test System-1996. The simulation results show that the proposed method is capable for solving unit commitment problem at total operational cost of $ 722186.93 and risk index at 0.347% (while EUE 0.01%, LOLP 1% and standard deviation (SD) 5%). The simulation results also demonstrate that several solution of the method have slightly lower cost up to 0.43% than those obtained in benchmark which the solution based on Simulated Annealing method.

Unit Commitment dengan Kekangan Keandalan Menggunakan Algoritme Genetika Mempertimbangkan Ketidakpastian Beban