| 安徽省2020年电动汽车保有量及充电负荷预测探讨 |
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| 引用本文： | 蒋从伟,吴斌,张健,段传科,冯飞波,闫兴德. 安徽省2020年电动汽车保有量及充电负荷预测探讨[J]. 电力需求侧管理, 2018, 20(2): 29-33 |
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| 作者姓名： | 蒋从伟 吴斌 张健 段传科 冯飞波 闫兴德 |
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| 作者单位： | 国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000,国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000,国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000,国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000,国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000,国网安徽省电力公司蚌埠供电公司，安徽蚌埠 233000 |
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| 摘 要： | 年来电动汽车发展迅速，将成为电力负荷预测中不可忽视的重要组成部分。准确的电动汽车负荷数据是电力系统规划和运行的重要数据基础，因此对电动汽车负荷的预测具有重要意义。探索提出了利用政府规划目标推算法、千人保有量法和电动汽车产业调研等方法开展安徽省 2020年电动汽车保有量预测。并基于实用化方法预测了安徽省 2020年电动汽车保有量；提出不同情景条件下预测安徽省 2020年电动汽车充电负荷最大规模，并采用标准车折算法对电动汽车充电负荷预测结果进行了合理校核，相关算法应用可为电动汽车负荷预测工作的方法和流程提供参考。
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| 关 键 词： | 电动汽车；保有量；充电负荷；预测 |
| 收稿时间： | 2017-12-28 |
| 修稿时间： | 2018-01-16 |
Discussion on forecasting of electric vehicle ownership andcharging load in Anhui Province in 2020 |
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| JIANG Cong.wei,WU Bin,ZHANG Jian,DUAN Chuan.ke,FENG Fei.bo and YAN Xing.de. Discussion on forecasting of electric vehicle ownership andcharging load in Anhui Province in 2020[J]. Power Demand Side Management, 2018, 20(2): 29-33 |
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| Authors: | JIANG Cong.wei WU Bin ZHANG Jian DUAN Chuan.ke FENG Fei.bo YAN Xing.de |
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| Affiliation: | Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China,Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China,Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China,Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China,Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China and Bengbu Power Supply Company, State Grid Anhui Electric Power Company, Bengbu 233000, China |
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| Abstract: | In recent years, the rapid development of electricvehicles makes its load an important part in electric power load fore.casting.Accurate electric vehicle load data is an important datafoundation for the planning and operation of power system, so theforecast of electric vehicle load is of great significance.Methods in.cluding government planning goal calculation method, thousands ofpossession method and electric vehicle industry research are pro.posed to carry out electric vehicle ownership forecast in 2020 in An.hui Province.In addition, the ownership is predicted based on practi.cal methods.A forecast of the largest scale of EV charging load inAnhui Province in different scenarios is proposed and the forecast.ing result is checked with standard car conversion algorithm.The ap.plication of these algorithms provides reference for the predictionand evaluation of EV load forecasting methods and processes.casting |
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| Keywords: | electric vehicle ownership charging load fore. |
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