An enhanced exploratory whale optimization algorithm for dynamic economic dispatch

Dynamic economic dispatch (DED) considering valve-point effects and transmission losses is a complex constrained optimization problem with non-smooth, non-linear and non-convex characteristics which has always been a significant challenge. To tackle the DED problem, an enhanced exploratory whale optimization algorithm (EEWOA) and a constraint handling technique considering the unit efficiency are proposed. Firstly, an adaptive enhanced exploratory prey mechanism is created to enhance population diversity of whale swarm, and the EEWOA method is developed. Secondly, a constraint handling technology is designed to improve the variable repairing ability, including coarse-tuning by heuristics and fine-tuning by forced repair technique. The proposed EEWOA is compared with several state-of-the-art optimization algorithms in terms of efficiency and effectiveness on 13 classical benchmarks, and three DED with different scales. According to the simulation results, EEWOA shows outstanding advantages on the benchmarks and the DED cases. (C) 2021 Published by Elsevier Ltd.

Automated summary

An enhanced exploratory whale optimization algorithm (EEWOA) is proposed to solve the complex Dynamic Economic Dispatch (DED) problem efficiently and effectively, by enhancing population diversity and improving variable repairing ability. EEWOA shows significant advantages over several state-of-the-art optimization algorithms on various benchmarks and DED cases.