AUTHOR=Yang Wenqiang , Li Ran , Yuan Ying , Mou Xiaolin 

TITLE=Economic dispatch using modified bat algorithm

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.977883

DOI=10.3389/fenrg.2022.977883

ISSN=2296-598X

ABSTRACT=Due to the frequent opening and shutting of turbine valves in the power system, valve point effect (VPE) that makes the economic dispatching problem non-linear, non-smooth and non-convex may be generated. Moreover, various constraints appear in the operation process, such as network transmission loss, and power balance during unit operation, which make it more difficult to find the global optimum through traditional mathematical methods. Nowadays, swarm intelligent algorithms have successfully become a useful optimization tool to deal with nonlinear problems. In this paper, an improved bat algorithm (IBA), into which random black hole strategy and Gaussian mutation are introduced, is proposed to solve the ED problem. Furthermore, the random black hole strategy can enhance the diversity of the population and improve the convergence speed of IBA. Gaussian mutation is adopted to help jumping out of the local optimum. Numerical experiments, that include comparisons with the methods in the literature, are conducted on well-known benchmark functions, as well as ED with different scale generation units commonly reported in the literature to validate the feasibility of the proposed IBA. Computational results are analyzed in terms of solution quality by the statistical method, which show that IBA has obvious advantages and practical applications.