| 引用本文: | 朱旭,孙元章,杨博闻,杨军,吴赋章,李高俊杰,詹祥澎.考虑不确定性与非完全理性用能行为的电动汽车集群可调度潜力计算方法[J].电力自动化设备,2022,42(10): |
| ZHU Xu,SUN Yuanzhang,YANG Bowen,YANG Jun,WU Fuzhang,LI Gaojunjie,ZHAN Xiangpeng.Calculation method of EV cluster’s schedulable potential capacity considering uncertainties and bounded rational energy consumption behaviors[J].Electric Power Automation Equipment,2022,42(10): |
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| 摘要: |
| 电动汽车(EV)的保有量与渗透率不断提高，且电力市场对售电侧放开，因此充分发挥需求侧资源的可调度潜力参与电力系统的优化调节显得愈加重要。提出了一种模型-数据混合驱动的EV集群可调度潜力计算方法。首先，根据闵可夫斯基求和理论将EV集群聚合为广义储能(GES)设备，基于双向长短期记忆网络形成GES模型参数的预测方法，根据EV用户的停驶数据进行用能规律挖掘以应对EV充电行为的随机性，并确定GES模型的容量、功率边界；然后，考虑EV用户的经济用能因素和非完全理性行为因素建立EV集群自调度模型，根据停驶数据的预测结果计算自调度负荷曲线；最后，计算GES设备的再调度容量、再调度功率，量化计算EV集群的可调度潜力。仿真算例结果表明，所提方法能够在明确EV集群用能行为与发挥可调度潜力参与需求响应之间界限的同时，量化EV集群的可调度潜力来为聚合商参与电力市场交易提供依据。 |
| 关键词: 电动汽车 可调度潜力 广义储能 车网互动 再调度容量 再调度功率 不确定性 |
| DOI：10.16081/j.epae.202209010 |
| 分类号:U469.72;TM734 |
| 基金项目:国家自然科学基金资助项目(51977154)；中央高校基本科研业务费专项资金资助项目(2042021kf0234,2042022kf1008) |
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| Calculation method of EV cluster’s schedulable potential capacity considering uncertainties and bounded rational energy consumption behaviors |
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ZHU Xu1, SUN Yuanzhang1, YANG Bowen2, YANG Jun1, WU Fuzhang1, LI Gaojunjie1, ZHAN Xiangpeng3
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1.School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China;2.Pudong Power Supply Company of State Grid Shanghai Municipal Electric Power Company, Shanghai 200120, China;3.Marketing Service Center of State Grid Fujian Electric Power Co.,Ltd.,Fuzhou 350011, China
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| Abstract: |
| The ownership and penetration rate of EVs(Electric Vehicles) are increasing and the electricity market is open to the power selling side. Therefore, it is more and more important to give full play to the schedulable potential of demand-side resources to participate in the optimization and regulation of the power system. A model-data hybrid driven method for calculating the schedulable potential capacity of EV cluster is proposed. Firstly, EV cluster is aggregated into GES(Generalized Energy Storage) device according to the Minkowski summation theory, and the prediction method of GES model parameters is formed based on Bi-LSTM(Bi-directional Long Short Term Memory network). According to the shutdown data of EV users, the energy consumption law is mined to cope with the randomness of EV charging behavior, and the capacity boundary and power boundary of GES model are determined. Then, considering EV users’ economic energy consumption factors and bounded rational behavior factors, the self-scheduling model of EV cluster is established, and the self-scheduling load curve is calculated according to the predicted results of shutdown data. Finally, the rescheduling capacity and rescheduling power of GES device are calculated, and the schedulable potential capacity of EV cluster is quantified. The results of simulation examples show that the proposed method can not only clarify the boundary between the energy consumption behavior of EV cluster and its schedulable potential capacity to participate in demand response, but also quantify the schedulable potential capacity of EV cluster to provide a basis for aggregators to participate in the electricity market transactions. |
| Key words: electric vehicles schedulable potential capacity generalized energy storage vehicle-to-grid rescheduling capacity rescheduling power uncertainties |
