Dynamic Electric Vehicle Charging Optimization Model Based on PSO and GA Algorithms
摘要
The present paper deals with an overview of particle swarm algorithms and hybrid genetic-particle swarm algorithms, and a comparison between the related convergence speed and correlation error. The work includes also a dynamic mutic-objective charging model that is important for the security, stability, and economics of the smart grids. Finally, a brief analysis of GA-PSO multi-objective electric vehicle charging dynamic optimization is reported.