Hybrid Differential Evolution With Biogeography-Based Optimization for Solution of Economic Load Dispatch

Abstract

This paper presents a hybrid technique combining differential evolution with biogeography-based optimization (DE/BBO) algorithm to solve both convex and nonconvex economic load dispatch (ELD) problems of thermal power units considering transmission losses, and constraints such as ramp rate limits, valve-point loading and prohibited operating zones. Differential evolution (DE) is one of the very fast and robust evolutionary algorithms for global optimization. Biogeography-based optimization (BBO) is a relatively new optimization. Mathematical models of biogeography describe how a species arises, migrates from one habitat (Island) to another, or gets extinct. This algorithm searches for the global optimum mainly through two steps: migration and mutation. This paper presents combination of DE and BBO (DE/BBO) to improve the quality of solution and convergence speed. DE/BBO improves the searching ability of DE utilizing BBO algorithm effectively and can generate the promising candidate solutions. The effectiveness of the proposed algorithm has been verified on four different test systems, both small and large. Considering the quality of the solution and convergence speed obtained, this method seems to be a promising alternative approach for solving the ELD problems in practical power system.