摘 要
电动汽车产业的快速增长凸显了充电基础设施的重要性。本文旨在优化充电站布局和充电策略，采用地理信息系统和多目标优化算法，构建了一个综合考虑交通、人口和土地利用等因素的选址模型，并提出动态充电调度策略。研究通过建立充电负荷预测模型，精准预估充电需求，结果显示优化模型能提升服务水平并降低运营成本。引入分时电价和智能调度系统相结合的创新方法，实现资源最优配置。案例分析验证了方法的有效性和实用性，为城市规划提供了决策支持，有助于促进电动汽车产业和城市交通效率的提升。
关键词：电动汽车充电站布局 多目标优化算法 动态充电调度策略 充电负荷预测 分时电价机制
Abstract
The rapid growth of the electric vehicle industry underscores the importance of charging infrastructure. This paper aims to optimize the charging station layout and charging strategy, adopt geographic information system and multi-ob jective optimization algorithm, construct a site selection model that comprehensively considers factors such as traffic, population and land use, and propose a dynamic charging scheduling strategy. Through establishing the charging load prediction model to accurately estimate the charging demand, the results show that the optimization model can improve the service level and reduce the operating cost. The innovative method of tOU electricity price and intelligent dispatching system is introduced to realize the optimal allocation of resources. The case analysis verifies the effectiveness and practicability of the method, provides decision support for urban planning, and helps to promote the improvement of electric vehicle industry and urban transportation efficiency.
Keyword:Electric Vehicle Charging Station Layout Multi-ob jective Optimization Algorithm Dynamic Charging Scheduling Strategy Charging Load Forecasting Time-Of-Use Pricing Mechanism
目 录
1 绪论 1
1.1 研究背景与意义 1
1.2 国内外研究现状 1
1.3 研究方法与技术路线 2
2 充电站布局影响因素分析 2
2.1 用户行为特征研究 2
2.2 地理位置与交通流量 3
2.3 城市规划与发展需求 3
2.4 能源供应与电网承载 4
3 充电站布局优化模型构建 4
3.1 数学模型建立原则 4
3.2 关键参数确定方法 5
3.3 模型求解算法选择 5
3.4 实证案例分析验证 6
4 充电策略优化方案设计 6
4.1 不同场景充电需求 7
4.2 动态调度机制研究 7
4.3 价格激励机制设计 8
4.4 用户引导策略制定 8
结论 9
参考文献 10
致谢 11
电动汽车产业的快速增长凸显了充电基础设施的重要性。本文旨在优化充电站布局和充电策略，采用地理信息系统和多目标优化算法，构建了一个综合考虑交通、人口和土地利用等因素的选址模型，并提出动态充电调度策略。研究通过建立充电负荷预测模型，精准预估充电需求，结果显示优化模型能提升服务水平并降低运营成本。引入分时电价和智能调度系统相结合的创新方法，实现资源最优配置。案例分析验证了方法的有效性和实用性，为城市规划提供了决策支持，有助于促进电动汽车产业和城市交通效率的提升。
关键词：电动汽车充电站布局 多目标优化算法 动态充电调度策略 充电负荷预测 分时电价机制
Abstract
The rapid growth of the electric vehicle industry underscores the importance of charging infrastructure. This paper aims to optimize the charging station layout and charging strategy, adopt geographic information system and multi-ob jective optimization algorithm, construct a site selection model that comprehensively considers factors such as traffic, population and land use, and propose a dynamic charging scheduling strategy. Through establishing the charging load prediction model to accurately estimate the charging demand, the results show that the optimization model can improve the service level and reduce the operating cost. The innovative method of tOU electricity price and intelligent dispatching system is introduced to realize the optimal allocation of resources. The case analysis verifies the effectiveness and practicability of the method, provides decision support for urban planning, and helps to promote the improvement of electric vehicle industry and urban transportation efficiency.
Keyword:Electric Vehicle Charging Station Layout Multi-ob jective Optimization Algorithm Dynamic Charging Scheduling Strategy Charging Load Forecasting Time-Of-Use Pricing Mechanism
目 录
1 绪论 1
1.1 研究背景与意义 1
1.2 国内外研究现状 1
1.3 研究方法与技术路线 2
2 充电站布局影响因素分析 2
2.1 用户行为特征研究 2
2.2 地理位置与交通流量 3
2.3 城市规划与发展需求 3
2.4 能源供应与电网承载 4
3 充电站布局优化模型构建 4
3.1 数学模型建立原则 4
3.2 关键参数确定方法 5
3.3 模型求解算法选择 5
3.4 实证案例分析验证 6
4 充电策略优化方案设计 6
4.1 不同场景充电需求 7
4.2 动态调度机制研究 7
4.3 价格激励机制设计 8
4.4 用户引导策略制定 8
结论 9
参考文献 10
致谢 11
