Technical Coordination of Aggregated Electric Vehicle Charging and Residential Loads at the Medium Voltage Level


Dumlu F., ZEHİR M. A.

4th IEEE Global Power, Energy and Communication Conference (IEEE GPECOM), Cappadocia, Türkiye, 14 - 17 Haziran 2022, ss.546-551 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/gpecom55404.2022.9815665
  • Basıldığı Şehir: Cappadocia
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.546-551
  • Anahtar Kelimeler: charging station, electric vehicle, energy management, fast charging, residential demand
  • Marmara Üniversitesi Adresli: Evet

Özet

Despite the coronavirus pandemic, the market share of electric vehicles (EV) has increased in recent years. For this reason, planning of new charging stations and active operation of charging stations have become more important. Studies about the integration of electric vehicles are very common, but the parameters and models adopted in these studies are simplified and analyses are made by making contradictory general assumptions. Therefore, there is a need for electric vehicle studies to be carried out with more detailed and realistic parameters. This study includes a wide range of normal and fast charging sessions and the housing demand of several customers. An aggregated charging management solution is developed, to keep the overall demand below the maximum limit at the medium voltage transformer level. This study provides a way to determine the suitability of the infrastructure or the integration challenges in the areas where the installation of parking and charging stations is aimed and proposes solutions. Initial simulation results show peaks at specific time intervals, especially in evening hours and these peaks cause overloads. To solve this problem two different methods were used. The first method is the random selection method, the second method is the sorted selection method. After the solutions are applied, high load values decrease, both worked successfully but the sorted selection method was more flexible and obtained more usable results. On the other hand, random method generally gave mix of good and bad results.