Multi-parameters dynamic scheduling with energy management for electric vehicle charging stations

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Haodong Wang, Ning Chen, Zan Liu, Songwei Zhang, Zhiguo Li, Tie Qiu
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引用次数: 0

Abstract

To make charging of electric vehicles (EVs) more convenient, the service providers of charging stations (CSs) establish a large number of CSs. Existing methods address the problem of reducing costs and increasing revenue for the service providers from multiple aspects, such as CS location optimisation and charging pricing strategy. This study proposes multi-parameters-based-dynamic scheduling with energy management for the CSs, considering energy management and EV charging scheduling (EVCS). A fully functional battery management system is designed for energy storage. A multi-parameters optimisation algorithm is proposed by designing the CS selection operator based on alternative set and adjusting parameters. The experiments show that our proposed algorithms got better performance in terms of optimisation effect, the number of iterations, and stability.

Abstract Image

基于能量管理的电动汽车充电站多参数动态调度
为了方便电动汽车的充电,充电站服务商建立了大量的充电站。现有的方法从CS位置优化和收费定价策略等多个方面解决了服务提供商降低成本和增加收入的问题。本文从能源管理和电动汽车充电调度的角度出发,提出了一种基于多参数的电动汽车能源管理动态调度方法。设计了一套功能齐全的电池存储管理系统。通过设计基于备选集和参数调整的CS选择算子,提出了一种多参数优化算法。实验结果表明,本文提出的算法在优化效果、迭代次数和稳定性方面都取得了较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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