Abstract
This paper presents a new approach for thermal generating units scheduling using binary differential evolution (BDE) algorithm. Solving the unit commitment (UC) problem by BDE is a two stage process. In the first stage, the economic dispatch of the units are solved and hourly optimum solution of UC is obtained considering all constraints except the minimum up time (MUT) and minimum down time (MDT) constraints. In the second stage, the MUT and MDT are enforced by defining a probability function followed by modifying the schedule obtained in the first step. To validate the results obtained by BDE, a version of genetic algorithm (GA), namely as, PNUCO is applied for comparison. Also, the results obtained by BDE and PNUCO are compared with the previous approaches reported in the literature. The results show that the BDE produces optimal or nearly optimal solutions for the study systems
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