Solution of Non-Smooth Economic Dispatch Using Interactive Grouped Adaptive Bat Algorithm

Abstract

This article presents the application of new grouped adaptive Bat algorithm (GABA) based metaheuristic method to improve the solution of economic dispatch (ED) problem considering valve point effect, prohibited zones, ramp rate limits and total power loss. The Bat algorithm is a new swarm intelligence algorithm inspired by the echolocation phenomenon in bats. The Bat algorithm is easy to program, and like many metaheuristic methods has an exploration and exploitation phases which require fine adjustment to achieve the near global solution. A grouped search mechanism is introduced to enhance the performances of the original Bat algorithm. The robustness of the proposed algorithm in term of solution quality and convergence characteristic have been demonstrated of three test systems of various complexities 6 units considering simultaneously the prohibited zones, ramp rate limits and total power loss, 13 and 40 units considering valve point effect. Results show clearly the efficiency and superiority of the proposed algorithm compared with various techniques reported in the recent literature.