Search

Large household electric vehicles charging will decrease the security of the power grid, and they can only charge by using a shared charging hub in the communities. Therefore, aiming at the above problems, a combined model of shared charging hub selection and electric vehicle charging scheme optimization was proposed. The model aimed to minimize the sum of the standard deviation of charging time between shared charging hubs and the standard deviation of all day charging load. Considering the importance of electric vehicle charging hub allocation scheme and electric vehicle charging scheme was different, a dynamic probabilistic genetic algorithm with changing probability with the increase of iteration times was proposed to solve the charging pile formula scheme and the optimization of electric vehicle charging scheme. The improved genetic algorithm is used to solve the model. The principle and process of the proposed algorithm are further illustrated by solving an example, which verifies the feasibility and effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)