Electric Vehicle Charging Scheduling Optimization Method Based on Improved Ant Colony. Issue 1 (1st February 2023)

• Record Type: Journal Article
• Authors: Cheng, Nuo; She, Lizhen; Chen, Dacai
• Is Part Of: Journal of physics. Volume 2418:Issue 1(2023)
• Publication Date: 2023-02-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2418/1/012112
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The influx of electric vehicles significantly impacts the power grid. In the process of power grid operation, the operation of charging and discharging of electric vehicles can be used to dispatch the load of power grid operation. The optimization method of charging and dispatching electric vehicles based on improved ant colony is studied. Pheromones generated during the charging of the electric vehicle are obtained, and the charging limit range of the battery is delimited. The dynamic window constructs the charging scheduling model improved ant colony algorithm, and the optimal charging path is selected to complete the scheduling method design. The experimental results show that the proposed method can adjust the charging and discharge in the period of valley price and peak price, play the role of peak clipping, and realize the load regulation in different periods, which has application value.