SPEECh Model for Study on Grid Impacts of Charging Infrastructure Access

This data set accompanies the github repository - https://github.com/SiobhanPowell/speech-grid-impact - and supports the research paper, "Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption", submitted in 2021. This paper uses a novel, data-driven model of electric vehicle drivers' charging behaviours to study the grid impacts of charging infrastructure access and control at deep levels of electric vehicle adoption.

The files here include five folders: (1) a Data folder containing models of driver charging behaviour that should be downloaded to run the Github model; (2) normalized load profiles for each driver group, giving the per vehicle daily load profile in kW; (3) the charging profiles produced for each of the main WECC grid scenarios studied in the paper; (4) the control objects learned to model workplace charging control; and (5) objects needed to run the grid dispatch model. Note in (3) those with suffix _20220313 are the main estimate of WECC demand while those with suffix _20211119 give the demand as if there were one timezone in WECC (used for illustration).

Authors: Siobhan Powell ([e-mail]), Gustavo Vianna Cezar, Liang Min, Prof Ines Azevedo, and Prof Ram Rajagopal ([e-mail]).

本数据集伴随github代码仓库 - https://github.com/SiobhanPowell/speech-grid-impact -，并支撑于2021年提交的研究论文《充电基础设施的接入与运营以减少深度电动汽车普及对电网的影响》。该论文采用一种新颖的数据驱动模型来研究电动汽车驾驶员的充电行为，进而探讨在深度电动汽车普及背景下，充电基础设施的接入与控制对电网的影响。数据包中包含五个文件夹：（1）一个数据文件夹，包含驾驶员充电行为模型，需下载以运行Github模型；（2）每个驾驶员群体的标准化负荷曲线，提供每辆车的日负荷曲线，单位为千瓦；（3）针对论文中研究的WECC主要电网场景产生的充电曲线；（4）用于建模工作场所充电控制的控制对象；（5）运行电网调度模型所需的对象。请注意，（3）中后缀为_20220313的文件是WECC需求的主体估计，而那些后缀为_20211119的文件则提供了如果WECC只有一个时区时的需求（用于说明）。作者包括：Siobhan Powell（[e-mail]）、Gustavo Vianna Cezar、Liang Min、Ines Azevedo教授和Ram Rajagopal教授（[e-mail]）。