Environmental Economic Dispatch of Power System Based on Artificial Fish Swarm Algorithm

Abstract

Environmental economic dispatch(EED) of power system is a multi-variable, strongly constrained, non-convex multi-objective optimization problem (Liu et al. Electric Power Automation Equipment 38:1–7, 2018). Aiming at this multi-objective optimization problem, This paper proposes an improved multi-objective artificial fish swarm algorithm (DE-AFSA). The algorithm optimization improves the shortcomings of the artificial fish swarm algorithm (AFSA) that is easy to fall into local optimum, the optimization accuracy may not be high in the later stage of the algorithm, and the convergence speed is slow. The improved algorithm mainly adopts a variable artificial fish shoal field of view and step size. As the number of iterations increases, the field of view and step size will gradually decrease to achieve the purpose of enhancing the optimization accuracy and improving the later convergence speed; At the same time, the differential evolution algorithm (DE) is introduced. The algorithm solves the power system scheduling to obtain the Pareto optimal front, and selects the compromise optimal solution according to the fuzzy decision. Finally, the algorithm is simulated and calculated on a standard test system with 6 IEEE30 nodes, and compared with other improved methods, it is concluded that the DE-AFSA has good feasibility and superiority (Shuai et al. Control and Decision 37:997–1004, 2022).