Work

An Improved NSGA-II Based Multi-Objective Optimization Model for Electric Vehicle Charging Station Selection

Year: 2025

Type: article

Abstract: Facing the challenge of balancing electric vehicle (EV) user experience with distribution network security, this paper develops a multi-objective optimization model for charging station selection that simultaneously considers user-side costs and grid-side stability indicators, including voltage deviation and system power loss. To solve this complex problem, an improved NSGA-II algorithm with enhanced constraint handling is introduced. Case studies on the IEEE 33-bus system demonstrate that the proposed approach effectively limits maximum voltage deviation to 2% with only a minimal 3% increase in user cost and reduces network losses by 12%. This achieves an optimal balance between user satisfaction and grid security, providing quantitative support for coordinated charging management and infrastructure planning.

Source: Mathematics

DOI: 10.3390/math13233855

Authors: Jingxuan Li, Hezhong Tang, Pengcheng Li, Zehao Li, Chengbin Liang

Institutions: Guizhou University, Guizhou Power Grid Co., Ltd. (China)

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $3,137