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This paper presents new approach for thermal unit commitment problem. Unit commitment (UC) problem plays a major role in power systems since the improvement of commitment schedules results in the reduction of operating cost. However, the unit commitment problem is one of the most difficult optimization problems in power system, because they have many constraints. Further, these constraints vary with each unit. To handle these constraints, some cording methods have been proposed. However, these methods require computation time. To overcome these problems, a new genetic operator based on unit characteristic classification and intelligent techniques generating initial populations are introduced. The proposed algorithm was tested on a reported UC problem. From simulation results, satisfactory solutions are obtained in comparison with previously reported results. Numerical results for system of up to 100 units are compared to previously reported results.
Senjyu et al. (Wed,) studied this question.