Research Area:  Metaheuristic Computing

Abstract:

This study proposes improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem. The DEED optimization target is to reduce the fuel cost and pollutant emission of the power system. In addition, DEED is a complex optimization problem and contains multiple optimization goals. To strengthen the ability of the ITSA algorithm for solving DEED, the tent mapping is employed to generate initial population for improving the directionality in the optimization process. Meanwhile, the gray wolf optimizer is used to generate the global search vector for improving global exploration ability, and the Levy flight is introduced to expand the search range. Three test systems containing 5, 10 and 15 generator units are employed to verify the solving performance of ITSA. The test results show that the ITSA algorithm can provide a competitive scheduling plan for test systems containing different units. ITSA proposed algorithm gives the optimal economic and environmental dynamic dispatch scheme for achieving more precise dispatch strategy.

Keywords:  
Improved tunicate swarm algorithm
dynamic economic emission dispatch problems

Author(s) Name:  Ling-Ling Li, Zhi-Feng Liu, Ming-Lang Tseng, Sheng-Jie Zheng, Ming K. Lim

Publisher name:  Elsevier

DOI:  10.1016/j.asoc.2021.107504

Volume Information:  Volume 108, September 2021, 107504

Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S1568494621004270