Abstract
AbstractThis paper presents an approach for solving the unit commitment problem based on genetic algorithm with integer representation of the unit start‐up and shut‐down times. The new definition of the decision variables in the unit commitment problem reduces the solution space and computational time of the genetic algorithm. The method incorporates time‐dependent start‐up costs, demand and reserve constraints, minimum up and down time constraints, ramp rate limit constraints, and units power generation limits. Penalty functions are applied to the infeasible solutions. Test results showed an improvement in effectiveness and computational time compared to results obtained from genetic algorithm with standard binary representation of the unit states and other techniques. Copyright © 2006 John Wiley & Sons, Ltd.
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