To explore the influence of grid connected electric vehicle on microgrid and its collaborative control under the background of new energy power generation, in this study, the constraints of electric vehicle are established from two aspects of electric vehicle travel characteristics and battery charging and discharging characteristics. In view of the variety of controllable resources in microgrid, multi-agent microgrid coordination control architecture is used to control the multi-layer coordination of microgrid, and simulation is built to analyze four different scenes. The results show that in the microgrid load, it is found that the valley peak difference is the smallest when both the electric vehicle and the conventional load participate in the demand response (scene 4). In the change of SOC and charge discharge power of battery energy storage system, it is found that four scenes make the energy storage function of “low storage and high generation” play an effective role. In the economic and environmental benefits of microgrid daily operation, it is found that the daily operation cost and environmental benefits of scene 4 are significantly lower than that of scene 1. Therefore, in this study, the coordinated optimization method of integrating electric vehicle into microgrid based on multi-agent microgrid can effectively solve the coordinated optimization of multi controllable resources of microgrid, and provide experimental basis for the subsequent development and optimization of microgrid.

为了探讨并网电动汽车对新能源发电背景下微电网的影响及其协同控制，本研究从电动汽车行驶特性和电池充放电特性两个方面建立了电动汽车的约束条件。鉴于微电网中可控资源的多样性，本文采用多主体微电网协调控制体系结构来控制微电网的多层协调，并通过仿真来分析四个不同的场景。结果表明，在微电网负载中，当电动汽车和常规负载都参与需求响应时，谷值峰值差异最小（场景4）。在电池储能系统SOC和充放电功率的变化中，发现有四个场景使“低储高能”储能功能发挥了有效作用。在微电网日常运行的经济和环境效益中，发现场景4的日常运行成本和环境效益明显低于场景1。因此，本研究采用了将电动汽车集成到微电网中的协同优化方法。基于多智能体微电网的系统可以有效解决微电网可控资源的协同优化问题，为微电网的后续开发和优化提供实验依据。发现四个场景使“低储高能”储能功能发挥了有效作用。在微电网日常运行的经济和环境效益中，发现场景4的日常运行成本和环境效益明显低于场景1。因此，本研究采用了将电动汽车集成到微电网中的协同优化方法。基于多智能体微电网的系统可以有效解决微电网可控资源的协同优化问题，为微电网的后续开发和优化提供实验依据。发现四个场景使“低储高能”储能功能发挥了有效作用。在微电网日常运行的经济和环境效益中，发现场景4的日常运行成本和环境效益明显低于场景1。因此，本研究采用了将电动汽车集成到微电网中的协同优化方法。基于多智能体微电网的系统可以有效解决微电网可控资源的协同优化问题，为微电网的后续开发和优化提供实验依据。