检索结果-南通市图书馆

A novel forecasting approach to schedule aggregated electric vehicle charging

Energy and AI 2023年第4期14卷 522-535页

作者： Nico Brinkel Lennard Visser Wilfried van Sark tarek alskaif Copernicus Institute of Sustainable Development Utrecht UniversityPrincetonlaan 8aUtrecht3584 CBThe Netherlands Information Technology Group(INF) Wageningen University and Research(WUR)Hollandseweg 1Wageningen6706 KNThe Netherlands

To be able to schedule the charging demand of an electric vehicle fleet using smart charging,insight is required into different charging session characteristics of the considered fleet,including the number of charging sessions,their charging demand and arrival and departure *** use of forecasting techniques can reduce the uncertainty about these charging session characteristics,but since these characteristics are interrelated,this is not ***,forecasting frameworks that cover all required characteristics to schedule the charging of an electric vehicle fleet are absent in scientific *** cover this gap,this study proposes a novel approach for forecasting the charging requirements of an electric vehicle fleet,which can be used as input to schedule their aggregated charging *** the first step of this approach,the charging session characteristics of an electric vehicle fleet are translated to three parameter values that describe a virtual ***,optimal predictor variable and hyperparameter sets are *** serve as input for the last step,in which the virtual battery parameter values are *** approach has been tested on a real-world case study of public charging stations,considering a high number of predictor variables and different forecasting models(Multivariate Linear Regression,Random Forest,Artificial Neural Network and k-Nearest Neighbors).The results show that the different virtual battery parameters can be forecasted with high accuracy,reaching R^(2) scores up to 0.98 when considering 400 charging *** addition,the results indicate that the forecasting performance of all considered models is somehow similar and that only a low number of predictor variables are required to adequately forecast aggregated electric vehicle charging characteristics.

关键词： Forecasting Electric vehicle smart charging Electric vehicle aggregation Virtual battery method

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：