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.
Original language | English |
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Pages (from-to) | 548-560 |
Number of pages | 13 |
Journal | IET Generation, Transmission and Distribution |
Volume | 16 |
Issue number | 3 |
DOIs | |
Publication status | Published - Feb 2022 |
MoE publication type | A1 Journal article-refereed |
Funding
Kalle Rauma would like to thank the support of the German Federal Ministry of Transport and Digital Infrastructure through the project Parken und Laden in der Stadt (03EMF0203). Kalle Rauma would also like to thank the project partners supporting this work. The work of Toni Simolin and Pertti J?rventausta was supported by the European Commission through LIFE-IP CANEMURE-FINLAND project (Towards Carbon Neutral Municipalities andRegions in Finland, LIFE17 IPC/FI/000002) and by Business Finland through Prosumer Centric Energy Communities?Towards Energy Ecosystem (ProC emPlus). The authors would also like to thank Laura Spies from TU Dortmund University for her help during the experiments (Parken und Laden in der Stadt). Kalle Rauma would like to thank the support of the German Federal Ministry of Transport and Digital Infrastructure through the project Parken und Laden in der Stadt (03EMF0203). Kalle Rauma would also like to thank the project partners supporting this work. The work of Toni Simolin and Pertti Järventausta was supported by the European Commission through LIFE‐IP CANEMURE‐FINLAND project (Towards Carbon Neutral Municipalities andRegions in Finland, LIFE17 IPC/FI/000002) and by Business Finland through Prosumer Centric Energy Communities–Towards Energy Ecosystem (ProC emPlus). The authors would also like to thank Laura Spies from TU Dortmund University for her help during the experiments (Parken und Laden in der Stadt) .