Network‐adaptive and capacity‐efficient electric vehicle charging site
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 statio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
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| Series: | IET Generation, Transmission & Distribution |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/gtd2.12301 |
| _version_ | 1819157564094414848 |
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| author | Kalle Rauma Toni Simolin Pertti Järventausta Antti Rautiainen Christian Rehtanz |
| author_facet | Kalle Rauma Toni Simolin Pertti Järventausta Antti Rautiainen Christian Rehtanz |
| author_sort | Kalle Rauma |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T16:10:46Z |
| format | Article |
| id | doaj.art-18b3f9ac79ec484692ce2e83fa0df9a1 |
| institution | Directory Open Access Journal |
| issn | 1751-8687 1751-8695 |
| language | English |
| last_indexed | 2024-12-22T16:10:46Z |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Generation, Transmission & Distribution |
| spelling | doaj.art-18b3f9ac79ec484692ce2e83fa0df9a12022-12-21T18:20:30ZengWileyIET Generation, Transmission & Distribution1751-86871751-86952022-02-0116354856010.1049/gtd2.12301Network‐adaptive and capacity‐efficient electric vehicle charging siteKalle Rauma0Toni Simolin1Pertti Järventausta2Antti Rautiainen3Christian Rehtanz4Institute of Energy Systems, Energy Efficiency and Energy Economics TU Dortmund University Emil‐Figge‐Str. 76 Dortmund 44227 GermanyUnit of Electrical Engineering Tampere University Korkeakoulunkatu 7 Tampere FinlandUnit of Electrical Engineering Tampere University Korkeakoulunkatu 7 Tampere FinlandUnit of Electrical Engineering Tampere University Korkeakoulunkatu 7 Tampere FinlandInstitute of Energy Systems, Energy Efficiency and Energy Economics TU Dortmund University Emil‐Figge‐Str. 76 Dortmund 44227 GermanyAbstract 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.https://doi.org/10.1049/gtd2.12301Optimisation techniquesTransportation |
| spellingShingle | Kalle Rauma Toni Simolin Pertti Järventausta Antti Rautiainen Christian Rehtanz Network‐adaptive and capacity‐efficient electric vehicle charging site IET Generation, Transmission & Distribution Optimisation techniques Transportation |
| title | Network‐adaptive and capacity‐efficient electric vehicle charging site |
| title_full | Network‐adaptive and capacity‐efficient electric vehicle charging site |
| title_fullStr | Network‐adaptive and capacity‐efficient electric vehicle charging site |
| title_full_unstemmed | Network‐adaptive and capacity‐efficient electric vehicle charging site |
| title_short | Network‐adaptive and capacity‐efficient electric vehicle charging site |
| title_sort | network adaptive and capacity efficient electric vehicle charging site |
| topic | Optimisation techniques Transportation |
| url | https://doi.org/10.1049/gtd2.12301 |
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