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.
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).