| 基于时空活动模型的电动汽车充电功率计算和需求响应潜力评估 |
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| 引用本文： | 钱甜甜,李亚平,郭晓蕊,陈星莺,刘建涛,毛文博.基于时空活动模型的电动汽车充电功率计算和需求响应潜力评估[J].电力系统保护与控制,2018,46(23):127-134. |
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| 作者姓名： | 钱甜甜 李亚平 郭晓蕊 陈星莺 刘建涛 毛文博 |
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| 作者单位： | 中国电力科学研究院有限公司南京分院，江苏 南京 210003,中国电力科学研究院有限公司南京分院，江苏 南京 210003,中国电力科学研究院有限公司南京分院，江苏 南京 210003,河海大学, 江苏 南京 210098,中国电力科学研究院有限公司南京分院，江苏 南京 210003,中国电力科学研究院有限公司南京分院，江苏 南京 210003 |
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| 基金项目： | 国家重点研发计划项目资助(2016YFB0901100) |
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| 摘 要： | 电动汽车用户行为的差异导致了电动汽车的时空分布特征不同。为了能够精准计算出电动汽车集群在某时刻、某地点的充电功率及其可提供的需求响应潜力,提出了一种基于时空活动模型的电动汽车充电功率计算和需求响应潜力评估方法。首先考虑了电动汽车的时空分布特性,分析了电动汽车的出行活动模型。然后基于实际数据得出了电动汽车充电的关键影响因素分布模型。最后采用蒙特卡洛和二项分布法计算出了单台电动汽车和电动汽车集群在工作日和非工作日的充电功率曲线,并分析了其需求响应潜力。所提方法能够在兼顾电动汽车时空分布的基础上,简便快捷地计算出电动汽车的充电功率。
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| 关 键 词： | 电动汽车 充电负荷 活动事件 需求响应 |
| 收稿时间： | 2018/6/26 0:00:00 |
| 修稿时间： | 2018/9/1 0:00:00 |
Calculation of electric vehicle charging power and evaluation of demand response potential based on spatial and temporal activity model |
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| QIAN Tiantian,LI Yaping,GUO Xiaorui,CHEN Xingying,LIU Jiantao and MAO Wenbo.Calculation of electric vehicle charging power and evaluation of demand response potential based on spatial and temporal activity model[J].Power System Protection and Control,2018,46(23):127-134. |
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| Authors: | QIAN Tiantian LI Yaping GUO Xiaorui CHEN Xingying LIU Jiantao and MAO Wenbo |
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| Affiliation: | China Electric Power Research Institute Nanjing Branch, Nanjing 210003, China,China Electric Power Research Institute Nanjing Branch, Nanjing 210003, China,China Electric Power Research Institute Nanjing Branch, Nanjing 210003, China,Hohai University, Nanjing 210098, China,China Electric Power Research Institute Nanjing Branch, Nanjing 210003, China and China Electric Power Research Institute Nanjing Branch, Nanjing 210003, China |
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| Abstract: | The difference in user behavior of electric vehicles leads to different spatial and temporal distribution characteristics of electric vehicles. In order to accurately calculate the charging power and the demand response potential of electric vehicle cluster at a certain time and place, this paper proposes a method for calculating the charging power and demand response potential of electric vehicles based on space-time activity model. Firstly, the spatial and temporal distribution characteristics of electric vehicles are considered, and the travel activity model of electric vehicles is analyzed. Then based on the actual data, the distribution model of key influencing factors of electric vehicle charging is obtained. Finally, Monte Carlo and binomial distribution method are used to calculate the charging power curve of single electric vehicle and electric vehicle cluster on working days and non-working days, and the demand response potential are analyzed. The proposed algorithm can calculate the charging power of electric vehicles simply and quickly on the basis of taking into account the space-time distribution of electric vehicles. This work is supported by National Key Research and Development Program of China (No. 2016YFB0901100). |
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| Keywords: | electric vehicle charging load activity event demand response |
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