A Simple Multi-Parameter Method for Efficient Charging Scheduling of Electric Vehicles

• Main Authors: George Konstantinidis, Fotios D. Kanellos, Kostas Kalaitzakis
• Format: Article
• Language: English
• Published: MDPI AG 2021-08-01
• Series: Applied System Innovation
• Subjects: electric vehicles; efficient charging scheduling; energy management; PSO; V2G
• Online Access: https://www.mdpi.com/2571-5577/4/3/58

In this article, a method for the efficient charging of electric vehicles (EVs) at the parking lot (PL) level, including V2G operation and taking into account lifetime of EV batteries, distribution network and local transformer loading, is proposed. The main targets of the method are to minimize the total charging cost of the PLs hosting the EVs and to satisfy all technical and operation constraints of EVs and PLs. The proposed method exploits particle swarm optimization (PSO) to derive the charging schedule of the EVs. The proposed method is compared with conventional charging strategies, where the EVs are charged with the maximum power of their charging power converter or the average power required to achieve their state-of-charge target, and a conventional charging scheduling method using the aggregated behavior of the plug-in EVs. Real-world data series of electricity price and parking lot activity were used. The results obtained from the study of indicative operation scenarios prove the effectiveness of the proposed method, while no sophisticated computing, measurement and communication systems are required for its application.