Binary whale optimization algorithm and its application to unit commitment problem

Abstract

Whale optimization algorithm is a novel metaheuristic algorithm that imitates the social behavior of humpback whales. In this algorithm, the bubble-net hunting strategy of humpback whales is exploited. However, this algorithm, in its present form, is appropriate for continuous problems. To make it applicable to discrete problems, a binary version of this algorithm is being proposed in this paper. In the proposed approach, the solutions are binarized and sigmoidal transfer function is utilized to update the position of whales. The performance of the proposed algorithm is evaluated on 29 benchmark functions. Furthermore, unpaired t test is carried out to illustrate its statistical significance. The experimental results depict that the proposed algorithm outperforms others in respect of benchmark test functions. The proposed approach is applied on electrical engineering problem, a real-life application, named as “unit commitment”. The proposed approach uses the priority list to handle spinning reserve constraints and search mechanism to handle minimum up/down time constraints. It is tested on standard IEEE systems consisting of 4, 10, 20, 40, 80, and 100 units and on IEEE 118-bus system and Taiwan 38-bus system as well. Experimental results reveal that the proposed approach is superior to other algorithms in terms of lower production cost.