基于能量路由器的交直流混合电动汽车充电站能量管理

电动汽车作为一种新型的交通工具，在世界上已经受到越来越多的欢迎。与传统燃油汽车相比，电动汽车可以减少碳排放并降低社会对化石能源的依赖。如今具有灵活充电功能的电动汽车充电站已经成为大多数城市常见的基础设施。电动汽车的充电行为具有时空分布随机性的特点，大规模无序充电不仅极大地增加了电力系统负荷，也可导致部分馈线节点出现电压降低、频率失稳、线路损耗增加等问题，导致电网运行的稳定性和安全性受到威胁。以微电网形态重构传统充电站电力管理架构，对于实现可再生能源高效集成，电动汽车有序充放电管理以及站点经济、电网友好型运行具有重要意义。本文针对电动汽车充电站新型电力网络架构、控制管理体系及优化调度方法展开研究。具体完成了如下工作：

本文针对包含可再生能源接入的交直流混合微网充电站提出一种基于能量路由单元的充电站架构，该架构具有集成化、多即插即用接口、供电可靠性高的特点。基于该架构提出了系统分层控制策略，在本地控制层实现了对相关变换器单元的短时间尺度控制。在能流调度层，提出了一种实时能流调度策略，提高光伏消纳的同时实现交直流子网的能量互补。

在所提出充电站微网架构的基础上，本文以电动汽车充电站充电成本最小、电网净负荷峰谷差最小作为双优化目标建立数学模型，充分考虑电动汽车放电电池损耗与光伏本地消纳情况，并充分挖掘电动汽车辅助服务潜力。优化结果验证了模型及调度算法的经济性及电网友好运行，同时也实现了车与车之间、交流子网与直流子网间的功率互助互济。

针对车网能量管理提出了一种智能充电桩互联网能量管理架构及调度算法。该架构特点在于每个充电桩都配备相应的计算和存储单元，可实现车网能量交互分布式调度优化，并可实现电动汽车用户敏感信息的本地存储、本地利用，避免了信息泄露的风险，设计了相关的高效算法以提高光伏消纳和负荷的削峰填谷能力，同时应用电压调节与控制保证电网的稳定性，仿真实验表明了所提出架构及调度算法的有效性和高计算效率。

As a new type of transportation, electric vehicles have been more and more popular in the world. Compared with traditional cars, electric vehicles can not only reduce carbon emissions, but also reduce society's dependence on fossil energy. Electric vehicle charging stations with flexible charging capabilities are now a common infrastructure in most cities. Electric vehicle charging has the characteristics of randomness in time and space distribution. Large-scale electric vehicle disorderly charging not only greatly increases the load of the power system, but also leads to voltage reduction, frequency instability, and increased line loss in some feeder nodes, resulting in grid operation. stability and security are threatened. Reconstructing the power management architecture of the traditional charging station in the form of a microgrid is of great significance for realizing the efficient integration of renewable energy, orderly charging and discharging management of electric vehicles, and economical and grid-friendly operation of the site. This paper studies the new power network architecture, control management system and optimal scheduling method of electric vehicle charging stations. Specifically completed the following work:

This paper proposes a charging station architecture based on energy routing units for AC/DC hybrid microgrid charging stations including renewable energy access. The architecture has the characteristics of integration, multiple plug-and-play interfaces, and high power supply reliability. The architecture proposes a hierarchical control strategy for the system, which implements short-time-scale control of the associated converter units at the local control level. In the energy flow scheduling layer, a real-time energy flow scheduling strategy is proposed, which can effectively improve the photovoltaic consumption and realize the energy complementation of the AC and DC sub-networks.

Based on the proposed charging station microgrid architecture, a mathematical model is established with the minimum charging cost of the electric vehicle charging station and the minimum peak-to-valley difference of the grid net load as the dual optimization objectives, and fully considers the electric vehicle discharge battery loss and photovoltaic local consumption. And fully tap the potential of electric vehicle auxiliary services. The optimization result verifies the economical and grid-friendly operation of the established model and scheduling algorithm, which realizes the power mutual assistance between vehicles and between the AC sub-network and the DC sub-network.

Finally, for the vehicle network energy management, a smart charging pile Internet energy management architecture and scheduling algorithm are proposed. The characteristic of this architecture is that each charging pile is equipped with corresponding computing and storage units, which can realize the distributed scheduling optimization of vehicle-network energy interaction, and realize the local storage and local utilization of sensitive information of electric vehicle users, avoiding the risk of information leakage. Relevant high-efficiency algorithms are designed to improve the capacity of photovoltaic absorption and load peak-shaving and valley-filling, and voltage regulation and control are applied to ensure the stability of the power grid. Simulation experiments show the effectiveness and high computational efficiency of the proposed architecture and scheduling algorithm.

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