摘 要
随着全球能源危机和环境污染问题的日益加剧，电动汽车作为可持续交通的重要组成部分，其普及对推动绿色出行具有重要意义。然而，充电基础设施布局不合理及充电策略缺乏优化已成为制约电动汽车发展的关键瓶颈。为此，本研究以提升充电网络效率和服务水平为目标，综合考虑用户需求、电网负荷及城市空间特征，提出了一种基于多目标优化模型的电动汽车充电站布局方法，并结合动态调度算法设计了智能化充电策略。研究采用地理信息系统（GIS）与数学规划相结合的技术手段，通过构建层次分析法权重评估体系和遗传算法求解模型，实现了充电站选址与规模配置的科学决策。同时，引入分时电价机制和车辆到电网（V2G）技术，进一步优化了充电过程中的能量流动与成本分配。结果表明，所提出的布局优化方法能够显著提高充电设施的利用率，降低建设成本，而智能充电策略则有效缓解了高峰时段电网压力，提升了系统整体经济性和环保效益。本研究的主要创新点在于将时空分布特征与动态需求预测融入优化框架，为实际工程应用提供了理论支持和技术参考，对未来电动汽车充电网络的规划与管理具有重要指导意义。
关键词：电动汽车充电站；多目标优化模型；动态调度算法；车辆到电网（V2G）；分时电价机制
Abstract
With the aggravation of global energy crises and environmental pollution, electric vehicles (EVs), as a crucial component of sustainable transportation, play a significant role in promoting green travel. However, the irrational layout of charging infrastructure and the lack of optimized charging strategies have become critical bottlenecks constraining the development of EVs. To address these challenges, this study proposes an EV charging station layout method based on a multi-ob jective optimization model, aiming to enhance the efficiency and service quality of the charging network. By comprehensively considering user demand, grid load, and urban spatial characteristics, this research integrates geographic information system (GIS) technology with mathematical programming to construct a hierarchical analytical fr amework for weight evaluation and employs genetic algorithms to solve the optimization model. This approach facilitates scientific decision-making regarding the location and scale configuration of charging stations. Furthermore, the study incorporates time-of-use pricing mechanisms and vehicle-to-grid (V2G) technology to optimize energy flow and cost distribution during the charging process. The results demonstrate that the proposed layout optimization method can substantially improve the utilization rate of charging facilities while reducing construction costs. Meanwhile, the intelligent charging strategy effectively alleviates peak-hour grid pressure, enhancing the overall economic and environmental benefits of the system. A key innovation of this study lies in integrating spatiotemporal distribution features and dynamic demand forecasting into the optimization fr amework, providing theoretical support and technical references for practical engineering applications. This research holds important guiding significance for the planning and management of future EV charging networks.
Keywords: Electric Vehicle Charging Station；Multi-ob jective Optimization Model；Dynamic Scheduling Algorithm；Vehicle To Grid (V2G)；Time-Of-Use Pricing Mechanism
目 录
摘 要 I
Abstract II
一、绪论 1
（一）电动汽车充电站研究背景与意义 1
（二）国内外研究现状分析 1
（三）研究方法与技术路线 1
二、充电站布局优化模型构建 2
（一）布局优化的数学建模基础 2
（二）关键影响因素分析 2
（三）优化算法选择与改进 3
（四）模型验证与案例分析 3
三、充电策略设计与性能评估 4
（一）充电策略的核心要素分析 4
（二）动态调度与负荷平衡策略 4
（三）用户行为对策略的影响 5
（四）策略实施效果评估 5
四、实际应用与优化方案改进 6
（一）现实场景中的问题识别 6
（二）数据驱动的优化方案调整 6
（三）多目标优化的实际应用 7
（四）改进方案的效果验证 7
结 论 8
致 谢 9
参考文献 10
