摘要
随着全球能源危机和环境污染问题日益严峻，新能源汽车作为绿色交通的重要组成部分得到快速发展，其充电设施的合理布局成为影响新能源汽车推广的关键因素。本研究旨在通过系统分析城市空间结构与交通流量特征，构建科学合理的充电设施布局优化模型，以提高充电设施的服务效率与利用率。基于地理信息系统（GIS）平台，融合多源数据，采用层次分析法确定各影响因素权重，运用遗传算法对充电设施布局进行全局优化。研究结果表明，在考虑交通流量、人口密度、土地利用类型等多重因素下，优化后的充电设施布局能够显著缩短用户平均充电距离，提升充电设施整体服务效能。特别是在城市中心区及交通枢纽周边，充电设施的可达性明显改善。本研究创新性地将时空大数据分析引入充电设施布局规划领域，提出了动态调整机制，为政府相关部门制定政策提供了科学依据，也为新能源汽车产业健康发展提供了重要支撑。
关键词：新能源汽车；充电设施布局；地理信息系统
Abstract
As global energy crises and environmental pollution become increasingly severe, new energy vehicles (NEVs), as a crucial component of green transportation, have experienced rapid development. The rational layout of charging infrastructure has emerged as a key factor influencing the promotion of NEVs. This study aims to construct a scientifically sound optimization model for charging facility layout by systematically analyzing urban spatial structure and traffic flow characteristics, thereby enhancing the service efficiency and utilization rate of charging facilities. Leveraging the Geographic Information System (GIS) platform and integrating multi-source data, this research employs the Analytic Hierarchy Process (AHP) to determine the weights of various influencing factors and utilizes Genetic Algorithms for global optimization of the charging facility layout. The results indicate that, when considering multiple factors such as traffic flow, population density, and land use types, the optimized layout of charging facilities can significantly reduce the average charging distance for users and improve overall service performance. Notably, accessibility to charging facilities in urban central areas and around transportation hubs has been markedly enhanced. Innovatively, this study introduces spatiotemporal big data analysis into the field of charging facility layout planning and proposes a dynamic adjustment mechanism, providing scientific evidence for policy-making by relevant government departments and offering critical support for the healthy development of the NEV industry.
Keywords：New Energy Vehicles; Charging Facility Layout; Geographic Information System
目 录
摘要 I
Abstract II
一、绪论 1
(一) 新能源汽车充电设施研究背景 1
(二) 国内外研究现状综述 1
(三) 研究方法与技术路线 2
二、充电设施布局影响因素分析 2
(一) 用户行为特征分析 2
(二) 城市空间结构影响 3
(三) 交通流量分布特征 4
三、充电设施布局优化模型构建 4
(一) 模型构建原则与目标 4
(二) 关键参数选取与确定 5
(三) 模型求解算法设计 6
四、实证研究与案例分析 7
(一) 研究区域选择依据 7
(二) 数据收集与处理方法 7
(三) 结果分析与优化建议 8
结 论 10
参考文献 11
随着全球能源危机和环境污染问题日益严峻，新能源汽车作为绿色交通的重要组成部分得到快速发展，其充电设施的合理布局成为影响新能源汽车推广的关键因素。本研究旨在通过系统分析城市空间结构与交通流量特征，构建科学合理的充电设施布局优化模型，以提高充电设施的服务效率与利用率。基于地理信息系统（GIS）平台，融合多源数据，采用层次分析法确定各影响因素权重，运用遗传算法对充电设施布局进行全局优化。研究结果表明，在考虑交通流量、人口密度、土地利用类型等多重因素下，优化后的充电设施布局能够显著缩短用户平均充电距离，提升充电设施整体服务效能。特别是在城市中心区及交通枢纽周边，充电设施的可达性明显改善。本研究创新性地将时空大数据分析引入充电设施布局规划领域，提出了动态调整机制，为政府相关部门制定政策提供了科学依据，也为新能源汽车产业健康发展提供了重要支撑。
关键词：新能源汽车；充电设施布局；地理信息系统
Abstract
As global energy crises and environmental pollution become increasingly severe, new energy vehicles (NEVs), as a crucial component of green transportation, have experienced rapid development. The rational layout of charging infrastructure has emerged as a key factor influencing the promotion of NEVs. This study aims to construct a scientifically sound optimization model for charging facility layout by systematically analyzing urban spatial structure and traffic flow characteristics, thereby enhancing the service efficiency and utilization rate of charging facilities. Leveraging the Geographic Information System (GIS) platform and integrating multi-source data, this research employs the Analytic Hierarchy Process (AHP) to determine the weights of various influencing factors and utilizes Genetic Algorithms for global optimization of the charging facility layout. The results indicate that, when considering multiple factors such as traffic flow, population density, and land use types, the optimized layout of charging facilities can significantly reduce the average charging distance for users and improve overall service performance. Notably, accessibility to charging facilities in urban central areas and around transportation hubs has been markedly enhanced. Innovatively, this study introduces spatiotemporal big data analysis into the field of charging facility layout planning and proposes a dynamic adjustment mechanism, providing scientific evidence for policy-making by relevant government departments and offering critical support for the healthy development of the NEV industry.
Keywords：New Energy Vehicles; Charging Facility Layout; Geographic Information System
目 录
摘要 I
Abstract II
一、绪论 1
(一) 新能源汽车充电设施研究背景 1
(二) 国内外研究现状综述 1
(三) 研究方法与技术路线 2
二、充电设施布局影响因素分析 2
(一) 用户行为特征分析 2
(二) 城市空间结构影响 3
(三) 交通流量分布特征 4
三、充电设施布局优化模型构建 4
(一) 模型构建原则与目标 4
(二) 关键参数选取与确定 5
(三) 模型求解算法设计 6
四、实证研究与案例分析 7
(一) 研究区域选择依据 7
(二) 数据收集与处理方法 7
(三) 结果分析与优化建议 8
结 论 10
参考文献 11
