考虑多方利益的居民小区电动汽车有序充电策略

肖建康; 邱晓燕; 潘胤吉; 吴甲武

肖建康,邱晓燕,潘胤吉,吴甲武.考虑多方利益的居民小区电动汽车有序充电策略[J].电测与仪表,2019,56(10):1-7,26.
Xiao Jiankang,Qiu Xiaoyan,Pan Yinji,Wu Jiawu.A Coordinated Charging Strategy for Electric Vehicles in Residential Communities Considering multiple interests[J].Electrical Measurement & Instrumentation,2019,56(10):1-7,26.

考虑多方利益的居民小区电动汽车有序充电策略

A Coordinated Charging Strategy for Electric Vehicles in Residential Communities Considering multiple interests

DOI：10.19753/j.issn1001-1390.2019.010.001

中文关键词: 电动汽车有序充电指导曲线负荷跟随移峰填谷

英文关键词:electric vehicles coordinated charging guide curve load following load shifting

基金项目:四川省科技厅重点研发项目(2017FZ0103)

作者中文名	作者英文名	单位
肖建康	Xiao Jiankang	四川大学
邱晓燕	Qiu Xiaoyan	四川大学
潘胤吉	Pan Yinji	四川大学
吴甲武	Wu Jiawu	四川大学

摘要点击次数: 2087

中文摘要:

随着电动汽车的普及率越来越高,大规模电动汽车的充电会造成电网负荷峰上加峰的现象,给电力系统的稳定运行带来风险和负担,如何进行移峰填谷、减小负荷波动成了当今电网非常关注的一个问题。对此,本文提出了一种上层优化指导曲线和下层实时负荷跟随相结合的实时优化模型。在上层总控中心,基于典型日常规负荷曲线和车辆出行预测数据,建立了以总负荷(常规负荷和EV充电负荷)峰谷差最小为目标的优化模型,得出一条电动汽车充电功率指导曲线；在下层智能控制中心,根据返回EV的状态和充电需求,计算EV充电优先级,以上层优化得到的功率指导曲线为跟随目标,来指导电动汽车的有序充电,实现负荷跟随。然后以某小区的常规负荷数据和EV用户出行的概率模型数据进行充电模拟,计算出相关的指标,与无序充电的结果进行对比。仿真结果表明,此有序充电控制策略能够有效地实现EV充电负荷的移峰填谷、降低负荷波动,同时也能够增加代理商的充电服务收益,满足用户的充电需求。

英文摘要:

As electric car penetration is higher and higher, the charging of large-scale electric vehicle will cause power grid load to a peak and peak phenomenon，burden to risk and the stable operation of power system. Therefore, how to shift peak load and reduce load fluctuations has become an important problem for power grids to solve the question of EV charging. In this paper, a real - time rolling optimization model is proposed, in which the upper optimize guidance curve and the lower realizes load real - time following. In upper master control center, based on typical daily routine load curve and vehicle travel forecast data, establishes a optimization with the minimum of total load (normal load and EV charging load) peak valley, draw a optimization guide curve; The lower intelligent control center calculates EV charging priority according to the return of EV charging status and demand, then guide electric vehicles to charge in order following the power guide curve optimized in the upper. Then, the conventional load data of a community and the probability model data of EV users travel were used to simulate the charging, and the related indicators were calculated and compared with the results of unordered charging. Orderly charge simulation results show that this control strategy can effectively achieve the EV charging load peak shift, to reduce the load fluctuation, at the same time also can increase the recharge of the agent service revenue, meet the requirements of charging users.

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