.png){kind=icon}
返回
A Data-Driven Approach for EV Electricity Demand Modeling Using Spatial Regression: A UAE Case Study
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2024.3390992.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The growing global interest in developing environment-friendly and sustainable transportation solutions is motivating mass adoption of Electric Vehicles (EVs). This increasing EV penetration is anticipated to result in a growing electricity demand to address the EV charging requirements. Therefore, precise demand modeling is essential to enable optimal sizing of the electricity generation and distribution networks as well as optimal placement of the EV charging infrastructure. Furthermore, microscopic modeling of EV traffic patterns and trip-wise energy requirements is essential to enable effective charging coordination and demand distribution for on-the-move EVs. However, microscopic EV demand modeling is typically hindered by the scarcity of open-access data that integrates EV charging and driving patterns. Accordingly, this work proposes a methodology for microscopic modeling of the trip-wise electricity demand of mobile EVs in the spatial and temporal domains, using both multiple linear regression and spatial autoregressive models. Secondary open-access data is extracted, wrangled, and pre-processed from a number of data sources to test and validate the proposed methodology on a case study of Dubai - UAE, acknowledging the growing EV adoption rates in the city. The proposed models are benchmarked against baseline models to confirm their superior performance.
Keyword:
Autoregressive models
demand modeling
electric vehicles
microscopic demand
multiple linear regression
spatial regression
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Technical Review on Advanced Approaches for Electric Vehicle Charging Demand Management, Part I: Applications in Electric Power Market and Renewable Energy Integration电动汽车充电需求管理高级方法技术综述，第一部分: 在电力市场和可再生能源整合中的应用
PREAI
分享收藏Are travel surveys a good basis for EV models? Validation of simulated charging profiles against empirical data.png)
APPLIED ENERGY
OAAI
APPLIED ENERGYIF11
OAAI分享收藏A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impactsAPPLIED ENERGYOAAI
APPLIED ENERGYIF11
OAAI分享收藏
查看更多内容