A Constrained Programming-Based Algorithm for Optimal Scheduling of Aggregated EVs Power Demand in Smart Buildings

被引：6

作者：

El Idrissi, Rajaa Naji ^{[1
]}

Ouassaid, Mohammed ^{[1
]}

Maaroufi, Mohamed ^{[1
]}

机构：

[1] Mohammed V Univ Rabat, Engn Smart & Sustainable Syst Res Ctr, Mohammadia Sch Engineers, Rabat, Morocco

来源：

IEEE ACCESS | 2022年 / 10卷

关键词：

Electric vehicle charging; Load modeling; Peak to average power ratio; Optimal scheduling; Indexes; Batteries; Water heating; EV charging control; coordinated management; peak-to-average ratio; user satisfaction; ELECTRIC VEHICLES; STRATEGY; OPTIMIZATION; SYSTEMS;

D O I：

10.1109/ACCESS.2022.3154781

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a novel cooperative charging strategy for electric vehicles tuned by a constraint programming algorithm has been proposed. The implemented model handles heterogeneous and large-scale residential areas by not only reducing the EV peak charging load, but also improving the user satisfaction levels. The evaluation of the capability of the proposed model at both individual and aggregated levels is considered through various scenarios. The simulated results prove the potential of the proposed cooperative EV strategy in outperforming the uncoordinated EV charging model in terms of peak-to-average ratio reduction, user satisfaction level, and load factor improvement in addition to the suppression of the peak load increase. Furthermore, comparative analysis with existing models shows that the proposed algorithm can manage more complex policies and is performed significantly and efficiently.

引用

页码：28434 / 28444

页数：11

共 37 条

[1] Review on Scheduling, Clustering, and Forecasting Strategies for Controlling Electric Vehicle Charging: Challenges and Recommendations [J].