Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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基于数据简化拟合的电动公交车充电负荷预测

来源:电体育下注网站电体育下注平台发布时间:2020-03-27 13:27 浏览次数:90
基于数据简化拟合的电动公交车充电负荷预测
 
端祝超
(江苏省送变电有限公司,江苏 南京 210028)
 
    摘 要:在测量统计大量电动公交车相关数据的基础上,对电动公交车的行驶和充电规律进行了量化分析和数据简化处理。根据电动公交车电池容量、行驶里程、环境条件等信息构建了基于数据简化的电动公交车充电功率模型和计算方法。基于上述简化后的数据信息和相关计算模型,利用优化的蒙特卡洛法对某市电动公交车的充电负荷进行了预测,并分析了不同时长预测负荷的误差及其原因,验证了该方法准确性和可行性。数据的简化处理有效地提高了该预测方法的可实施性,且其预测结果能够满足充电设施规划建设和电网运行规划的要求。
    关键词:电动公交车;行驶规律;充电负荷预测;蒙特卡洛法;数据简化
    中图分类号:TM714     文献标识码:A     文章编号:1007-3175(2020)03-0023-05
 
Electric Bus Charging Load Forecast Based on Data Simplification Fitting
 
DUAN Zhu-chao
(Jiangsu Power Transmission and Transfer Co., Ltd, Nanjing 210028, China)
 
    Abstract: Based on the measurement and statistics of a large number of relevant data of electric bus, the quantitative analysis and data simplification of the driving and charging rules are carried out. According to the information of battery capacity, driving distance and environmental conditions, the charging power model and calculation method based on data simplification are constructed. Based on the simplified data information and related calculation model, the optimized Monte Carlo method is used to predict the charging load of electric buses in a city, and the error of the forecasting load with different duration and its causes are analyzed. The accuracy and feasibility of the method are verified. The simplified processing of the data can effectively improve the operability of the prediction method, and the prediction result can meet the requirements of the charging facility planning construction and the grid operation planning.
    Key words: electric bus; driving rules; charging load forecasting; Monte Carlo method; data simplification
 
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