TY - GEN
T1 - Assessing the Impact of Electric Vehicle Charging on Distribution Network
AU - Gad, Mohammed Khalid
AU - Al-Qahtani, Muneera
AU - Karaki, Anas
AU - Sharida, Ali
AU - Wanik, Mohd Zamri Che
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/5/22
Y1 - 2025/5/22
N2 - This study explores the impact of electric vehicle (EV) integration on the distribution network of the Education City Community Housing (ECCH) in Qatar, with a particular emphasis on voltage stability, line loading, and transformer loading. Leveraging DIgSILENT PowerFactory and Quassi Dynamic Simulation models, EV charging logic was developed to simulate varying penetration levels of EVs, reflecting real-world charging behaviors. Real-time pPhasor measurement unit (PMU) data was incorporated to assess the consequences of uncontrolled EV charging on voltage drop and the load distribution across the network. To enhance the analytical flexibility, a custom graphical user interface is designed and integrated with DIgSILENT using Python, allowing for real-time manipulation of EV penetration levels and enabling comprehensive analysis of multiple charging scenarios. The results underscore the significant risks associated with high levels of EV penetration, such as voltage instability and alterations in load patterns, offering critical insights into the need for advanced grid management strategies.
AB - This study explores the impact of electric vehicle (EV) integration on the distribution network of the Education City Community Housing (ECCH) in Qatar, with a particular emphasis on voltage stability, line loading, and transformer loading. Leveraging DIgSILENT PowerFactory and Quassi Dynamic Simulation models, EV charging logic was developed to simulate varying penetration levels of EVs, reflecting real-world charging behaviors. Real-time pPhasor measurement unit (PMU) data was incorporated to assess the consequences of uncontrolled EV charging on voltage drop and the load distribution across the network. To enhance the analytical flexibility, a custom graphical user interface is designed and integrated with DIgSILENT using Python, allowing for real-time manipulation of EV penetration levels and enabling comprehensive analysis of multiple charging scenarios. The results underscore the significant risks associated with high levels of EV penetration, such as voltage instability and alterations in load patterns, offering critical insights into the need for advanced grid management strategies.
KW - Distribution network
KW - EV charging
KW - Modeling
KW - phasor measurement Unit
UR - https://www.scopus.com/pages/publications/105009406120
U2 - 10.1109/CPE-POWERENG63314.2025.11027247
DO - 10.1109/CPE-POWERENG63314.2025.11027247
M3 - Conference contribution
AN - SCOPUS:105009406120
SN - 979-8-3315-1518-8
T3 - Compatibility Power Electronics And Power Engineering
BT - 2025 Ieee 19th International Conference On Compatibility, Power Electronics And Power Engineering, Cpe-powereng
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 19th IEEE International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2025
Y2 - 20 May 2025 through 22 May 2025
ER -