A Bi-objective Optimization Study Based on Elite Selection for Electric Vehicle Charging. Issue 1 (1st February 2023)

• Record Type: Journal Article
• Authors: Song, Wenbo; Fu, LiYou
• Is Part Of: Journal of physics. Volume 2427:Issue 1(2023)
• Publication Date: 2023-02-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2427/1/012041
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Electric vehicle charging increases the grid-side load, and the safety and economy of grid operation are affected. First, we consider the influence of climatic factors on EV charging and simulate the daily load profile under disorderly charging using the Monte Carlo method. Then, the elite selection is proposed in the context of traditional algorithms to establish a dual-objective optimization model with the minimum peak-to-valley difference on the grid side and the minimum total cost on the customer side. Finally, a city grid is used as an example to verify that the model is effective. The results show that the establishment of a time-of-use tariff for electricity market supply and demand and the use of elite selection bi-objective optimization can reduce peak-to-valley differences and smooth out grid fluctuations, improving the safety and economy of grid operation.