Network‐adaptive and capacity‐efficient electric vehicle charging site. Issue 3 (19th September 2021)

• Record Type: Journal Article
• Authors: Rauma, Kalle; Simolin, Toni; Järventausta, Pertti; Rautiainen, Antti; Rehtanz, Christian
• Is Part Of: IET generation, transmission & distribution. Volume 16:Issue 3(2022)
• Page Start: 548
• Page End: 560
• Publication Date: 2021-09-19
• Subjects: Optimisation techniques -- Transportation; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/gtd2.12301
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract: The adaptive charging algorithms of today divide the available charging capacity of a charging site between the electric vehicles without knowing how much current each vehicle draws in reality. Thus, they are not able to detect deviations between the current set point at the charging station and the real charging current. This leads to a situation where the charging capacity of the charging site is not used optimally. This paper presents an algorithm including a novel feature, Expected Characteristic Expectation and tested under realistic circumstances. It is demonstrated that the proposed algorithm enhances the adaptability of the charging site, increasing the efficiency of the used network capacity up to about 2 kWh per charging point per day in comparison with the previous benchmark algorithm. The algorithm is able to increase the average monetary benefits of the charging operators by up to around 5.8%, that is 0.6 € per charging point per day. No input, such as departure time, is required from the user. The proposed algorithm has been tested with real electric vehicles and charging stations and is compatible with the IEC 61851 charging standard. The charging algorithm is applicable in practice as it is described in this paper.