The charging station and swapping station site selection with many-objective evolutionary algorithm

The battery swap mode is a novel way of energy supplement for electric vehicles. Inevitably, there are some business transactions between battery swapping station (BSS) and battery centralized charging station (BCCS) in the mode. Therefore, it is essential to plan the construction of BSS and BCCS uniformly. Moreover, the needs of enterprises and users are not taken into account simultaneously in the existing site selection model. To resolve this problem, a many-objective joint site selection (MOJSS) model of BSS and BCCS is proposed in this paper. It mainly includes four objective functions: construction cost, coverage rate, investment income and satisfaction, which consider distance constraint between user demand points and the BSS, distance constraint between BBS and BSS, and the service ability constraint of BSS and the BCCS. To better solve the proposed model, a Grid-based evolutionary algorithm based on hybrid environment selection strategy is proposed. Furthermore, the segmented integer coding strategy and the specific genetic operation are designed based on the characteristic of model. It is compared with the existing many-objective evolutionary algorithms on standard test problems. Then the algorithm is applied to solve the established model. The experimental result demonstrated the reasonableness and effectiveness of proposed model. Finally, the site selection results are illustrated by a set of solutions.

Automated summary

This paper proposes a many-objective joint site selection model for battery swapping stations and battery centralized charging stations. The model considers construction cost, coverage rate, investment income, and satisfaction as objective functions, aiming to address the issue of not simultaneously considering the needs of enterprises and users in existing site selection models. A Grid-based evolutionary algorithm with a segmented integer coding strategy is utilized to solve the optimization problem. Experimental results demonstrate the reasonableness and effectiveness of the proposed model.