电动汽车放电时可作为电网的一种分布式储能装置，参与缓解高比例新能源接入微电网的供电压力。基于多时间尺度下分时电价的特点，提出一种考虑电动汽车集群的微电网多时间尺度优化调度方法。在日前调度阶段，基于分时电价对微电网内部储能、可中断负荷、可转移负荷等设备出力进行优化调度；在日内优化调度阶段，将电动汽车集群纳入到微电网能量调度中来，通过分析各电动汽车集群的调度潜力来实现合理的充放电。为验证所提方案的有效性，选取不同的用电峰平谷时段分时电价，让电动汽车集群参与微电网能量调度，结果证明考虑电动汽车集群参与的微电网多时间尺度优化调度能充分利用电动汽车集群的储能资源，提升微电网调度运行的灵活性和经济性。

When discharging, electric vehicles can serve as distributed energy storage units of the power grid to alleviate the power supply pressure of microgrids with high proportions of new energy integration. Capitalizing on the characteristics of time-of-use tariffs across multi-time scales, this study proposes a multi-time scale optimization scheduling method for microgrids that takes into account clusters of electric vehicles. In day-ahead scheduling phase, the equipment output such as internal energy storage, interruptible loads and transferable loads in the microgrid is optimized based on time of use tariffs; During intra-day optimization scheduling phase, electric vehicle clusters will be included in the energy scheduling of microgrids, and reasonable charging and discharging can be achieved by analyzing the scheduling potential of each electric vehicle cluster. To verify the effectiveness of the proposed scheme, electric vehicle clusters are selected to participate in microgrid energy scheduling based on variable time of use tariffs during peak, flat, and valley periods. The results show that the multi-time scale optimization scheduling for microgrids considering the participation of electric vehicle clusters can make full use of the energy storage resources of electric vehicle clusters and improve the flexibility and economy of microgrid scheduling operation.

新能源以分布式电源的形式接入配电网，给系统带来了不可控性、随机性和波动性问题。借助现代电力电子、信息通信及自动控制等技术，灵活可控的主动配电网成为发展趋势，其中主动配电网规划是近年来研究的热点之一。综合国内外在这一领域的研究成果，对主动配电网规划相关研究内容及其方法进行总结、分析及展望。对主动配电网基本结构进行了描述，介绍了配电网组成元素的特点；根据其控制变量的不同，对主动配电网规划模型进行了归类，总结了模型中的优化目标；针对常用模型求解算法及其优缺点进行分析、总结；通过对关键性问题的讨论，分析了未来主动配电网的发展趋势。

The new energy is connected to the distribution network in the form of distributed generation, which brings uncontrollability, randomness and volatility to the system. With the help of modern power electronics, information and communication and automatic control technologies, the active distribution network with flexibility and controllability has become a development trend. The active distribution network planning is one of the major research fields in recent years. Based on the research results in this field at home and abroad, the research contents and methods of active distribution network planning were summarized, analyzed and prospected. The basic structure of the active distribution network was described, and the characteristics of the components of the distribution network were introduced. According to the different control variables, the planning models of active distribution network were classified, the optimization objectives in the model were summarized. The commonly used model solving algorithms and their advantages and disadvantages were analyzed and summarized. Through the discussion of key issues, the development trend of active distribution network in the future was analyzed.

近年来，为应对频发的极端事件，配电网弹性提升技术迅猛发展。在实际应用中，技术方案经济成本过高成为制约其应用落地的重要因素。针对上述问题，本文提出了一个融合移动储能与电动汽车并网（V2G）技术的配电网弹性提升方案，其具体目标为优化灾后供电恢复过程中的经济成本，同时确保恢复效能。在灾害初期，通过建立预先的电动汽车调度模型来获取电动汽车的分布状况以及各个V2G站点的最大供电能力。接着，基于实际的道路网络规划和电力负荷数据，决定临时的移动储能（MESS）仓库的安置地点。在灾害后期，将恢复过程中的综合经济成本作为优化目标，通过调整V2G站点的输出和MESS的调度策略来进行优化决策。对所提方法运用多组算例进行了验证，仿真结果表明，所提协同恢复方案在降低系统灾后失电量的同时能够有效改善弹性策略的经济性。

In recent years, the distribution network resilience enhancement technology developed in response to extreme events has developed rapidly. However, in practical applications, the high economic cost of technical solutions is one of the important factors restricting its implementation. Based on the above problems, this paper proposes an economic post-disaster restoration decision-making method for resilient distribution network with MESS and electric vehicle V2G, which reduces the economic cost of restoration while ensuring the restoration effect. In the pre-disaster stage, a pre-disaster electric vehicle scheduling model is established to obtain the distribution of electric vehicles and the maximum output of each V2G station. According to the actual line layout and load information, the MESS temporary warehouse deployment location is determined. In the post-disaster stage, the comprehensive economic cost of post-disaster restoration is taken as the objective function to optimize the V2G station output and MESS scheduling in the restoration process. The proposed method is verified by multiple sets of examples. The simulation results show that the proposed collaborative restoration scheme can effectively improve the economy of the resilient strategy while reducing the post-disaster power loss of the system.