A hybrid whale optimization-differential evolution and genetic algorithm based approach to solve unit commitment scheduling problem: WODEGA

Background: Unit Commitment (UC) is a complication in the domain of power systems engineering which is integral to the secure, efficient, and economic daily operation of a power system. UC is an optimization problem that aims at scheduling which generating units will be on at what time to meet electricity demand over a given horizon and that horizon it's typically 24-48 hours from now. Objective: This research paper proposes a hybrid approach which is the extension of hGADE algorithm aims at solving mixed-integer optimization problem known as the Unit Commitment scheduling problem. The Whale Optimization Algorithm has been incorporated for the calculation of total operation cost of power system operation. Method: The technique has been tested on a 6 unit system by taking into consideration various system and unit constraints. The hybridization of differential evolution, genetic algorithm, and whale optimization algorithm has produced a significant improvement in overall results. Result: It has been found that the average cost of operation is 142814.9603 INR and it gets reduced to 142809.8944 INR after applying optimization (hGADE). The cost is further reduced to 142790.0 INR after the application of the Whale Optimization Algorithm (WOA). Conclusion: In this paper, we present a hybrid approach which involves the blending of Differential Evolution, Genetic Algorithm, and Whale Optimization aim at solving mixed-integer optimization problem known as Unit Commitment scheduling problem and has given promising results.