含大规模电动汽车的主动配电系统及充电基础设施协同规划理论研究

The large scale deployment of electric vehicles (EV)in the future presents significant challenges to the planning of the distribution system and charging facilities. Firstly, the integration of EV brings a lot of uncertainties, such as the load complexity of spatial and temporal distribution, and the diversity of charging/discharging characteristics, etc. Meanwhile, as a kind of mobile energy storage system, EVs can realize friendly interaction with the distribution sytem, which endows the distribution system with a multi-source initiative characteristic. So many complex factors interacting with each other not only makes the planning of distribution system, which is already a NP-hard problem, even more complex, but also brings resonable planning requirement to the EV charging facilities. To address this problem, this research project intends to achieve breakthroughs in the following areas: 1) A Spatial-Temporal Model (STM) based on intelligent transportation simulation technique will be developed to accurately predict the EV charging load and Vehicle-to-Grid (V2G) capability spatially and temporally; 2) A coordination planning model for the planning of the distribution system and charging facilities based on Collaborative Optimization (CO) will be studied, which consists of two subsystems. One is the optimal siting and sizing of EV charging facilites, and the other one is the planning of distribution system. Also, a novel intelligent optimization algorithm will be developed to obtain the optimum planning scheme of the coordination planning model. 3) Finally, the STM and the coordination planning model will be developed into practical algorithm libaries and software packages, which will be applied into real planning projects of distribtuion systems and charging facilities. The researches in this project will provide theoretical and technical support to the popularity of EVs and the planning of distribution system with charging facilities.

未来电动汽车(EV)的大规模应用给配电系统及充电基础设施的规划提出了挑战：首先EV并网引入大量不确定性环节，如负荷时空分布的复杂性，电池充放电特性的多样性等；同时作为移动储能装置，EV经充电基础设施可与系统实现友好互动，使得配电系统具有多源主动性特征。众多交织复杂因素不仅使原本已NP难的配电系统规划问题愈加复杂，还需充电设施的合理规划。针对此难题，本项目拟在如下领域取得突破：结合智能交通仿真技术构建EV的时空分布模型，以精确预测EV负荷的时空分布及系统响应能力；进一步，利用协同优化算法构建配电系统及充电基础设施的协同规化模型，包含充电基础设施选址与容量配置、配电系统规划两个子系统规化问题，并研究高效智能算法求取最优协同规划方案；最后将前述研究成果转化为实用算法和程序，并在实际配电系统及充电设施规划中加以应用。本项目研究成果将为EV的普及、配电系统及充电基础设施的规划提供理论支持和技术保障。

未来电动汽车(EV)的大规模应用给配电系统及充电基础设施的规划提出了挑战：首先 EV 并网引入大量不确定性环节，如负荷时空分布的复杂性，电池充放电特性的多.样性等；同时作为移动储能装置，EV 经充电基础设施可与系统实现友好互动，使得配电系统具有多源主动性特征。众多交织复杂因素不仅使原本已 NP 难的配电系统规划问题愈加复杂，还需充电设施的合理规划。针对此难题，本项目通过深入研究在如下领域取得了如下突破：.1) 提出基于智能交通仿真的EV的时空分布模型，可精确预测EV负荷的时空分布及系统响应能力，为配电网规划提供数据基础；.2) 提出了“车-路-网”模式下电动汽车接入后对配电网的影响评估模型，从电压、负载率等多个角度进行全方位评估；.3) 提出了考虑用户参与度的电动汽车能效电厂响应能力评估模型，可充分挖掘电动汽车群体有功和无功的响应能力，实现电动汽车与电网的协调互动，缓解电动汽车充电负荷对配电网的冲击，减少系统规划减少成本；.4) 提出综合考虑配电网潮流约束和交通出行需求的高速公路快速充电站协同规划方法，包含充电基础设施选址与容量配置、配电系统规划两个子系统规化问题，成果在海南环岛高速实际路网中进行了测试和应用；.5) 研究了电动汽车充放电功率不确定性以及充放电管理对电网风险的影响，可对规划方案进行后评估，支撑最终决策。.本项目研究成果将为EV的普及、配电系统及充电基础设施的规划提供理论支持和技术保障，具有显著的社会经济效益。