Research on intelligent dispatching of micro-grid according to optimized particle swarm algorithm

Abstract

In the process of grid connection of irregular output micro-grid systems, it is of great research significance to make micro-grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro-grid intelligent scheduling system during grid connection, this study proposes a micro-grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non-dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro-grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro-grid.