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Solution methodology of unit commitment using genetic algorithms (Gas) is presented. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start-up cost, and spinning reserve, which is defined as minimization of the total objective function while satisfying the associated constraints. Problem-specific operators are proposed for the satisfaction of time-dependent constraints. Problem formulation, representation, and the simulation results for a 10-generator-scheduling problem are presented.
Swarp et al. (Tue,) studied this question.
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