Abstract
This paper proposes a new approach based on modified binary artificial bee colony (MBABC) algorithm and dynamic economic dispatch (DED) method for unit commitment problem (UCP). MBABC algorithm is used for committing/decommitting the thermal units, while optimum dispatch solution is determined using DED method. Proposed MBABC algorithm utilizes a new mechanism based on the measure of dissimilarity between binary strings for generating the new binary solutions for UCP. Moreover, in MBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The solution quality achieved by MBABC is enhanced by hybridizing the genetic crossover (GC) that provides the diversified search space. Performance of the proposed MBABC-GC algorithm is tested up to 300 thermal units over 24-hour time interval. The comparison of obtained results with other methods in the literature has confirmed the superiority of the MBABC-GC algorithm in terms of production cost and robustness. Copyright © 2015 John Wiley & Sons, Ltd.
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