Research on Economic Optimal Dispatching of Microgrid Cluster Based on Improved Butterfly Optimization Algorithm

Abstract

Microgrid optimal dispatching has become one of the core issues of microgrid energy management and integrated control, which is of great significance to reduce energy consumption and environmental pollution. As a natural heuristic algorithm, the butterfly optimization algorithm (BOA) has the advantages of simple adjustment parameters and fast convergence speed. It is widely used to solve nonlinear programming problems. However, BOA is easy to fall into local optimization and poor convergence accuracy. Therefore, an improved butterfly optimization algorithm (IBOA) based on skew tent chaotic map, Cauchy mutation, and simplex method is proposed, and compared with particle swarm optimization (PSO), whale optimization algorithm (WOA), sparrow search algorithm (SSA), and BOA, the results show that the IBOA has high convergence speed and optimization accuracy. Finally, the IBOA is used to solve the optimization model. The simulation results show that the IBOA can effectively reduce the power consumption cost of the system, promote the effective utilization of renewable energy, and improve the operation stability of the microgrid cluster system.