Optimization Effect Analysis of ACM-PSO Integrating Individual Adjustment and Cross Operation on Microgrid DG Technology

Microgrid, as a distributed power technology, has deep potential at present. This study deeply researches microgrid and electric vehicles. A grid-connectedmicrogrid power optimization management model is established, and an adaptive crossover multi particle swarm optimization (ACM-PSO) is proposed, which can adjust and operate individually. The proposed algorithm introduces individual adjustment operation and considers the start and stop state of the micro power supply. Besides, it does not need to decompose the unit commitment problem into two levels of optimization problems, which reduces the complexity of the optimization problem. A-PSO algorithm is prone to fall into local optimum. This problem can be avoided and its global search ability can be improved by introducing the crossover operation of ACM-PSO. According to the analysis of examples, the ACM-PSO algorithm has the best economic effect in different operation schemes among experimental methods. The running cost of the algorithm is <tex-math notation="LaTeX">$$ $ </tex-math> 3111.17, <tex-math notation="LaTeX">$$ $ </tex-math> 2932.62 and <tex-math notation="LaTeX">$$ $ </tex-math> 2929.93, respectively, which is <tex-math notation="LaTeX">$$ $ </tex-math> 0.3, <tex-math notation="LaTeX">$$ $ </tex-math> 13.54 and <tex-math notation="LaTeX">$$ $ </tex-math> 15.08 lower than that of A-PSO algorithm. The proposed method has better optimization performance and can effectively reduce the operation cost of microgrid (MG).