Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/5245
Title: Hosting capacity assessment of electric vehicle charging in residential low voltage distribution networks
Authors: Umoh, Vincent Bassey 
Keywords: Electric vehicles (EVs);Low voltage (LV) distribution networks
Issue Date: Sep-2023
Abstract: 
The necessity for environmentally friendly transportation systems and the ongoing energy crisis have incited the proliferation of electric vehicles (EVs) in low voltage (LV) distribution networks. However, large-scale integration and simultaneous charging of EVs can have a huge negative impact on the distribution network, disrupting the standard operating conditions by creating several technical challenges for the distribution grid such as voltage violations, transformer and lines overloading, and an increase in electrical losses. These challenges make it important to carry out studies that will assess the impact of connecting multiple EVs simultaneously for charging in existing low voltage electrical networks and further determine the hosting capacity (HC) of such networks. This study assesses the impact of three-phase and single-phase EV charging in an eThekwini residential network, determines the HC from the assessment, investigates how the threephase EV charging HC changes based on different circumstances, and also estimates the single-phase HC for different EV charging power. To achieve this, a residential low voltage distribution network containing 21 households is modeled using DIGSiLENT PowerFactory with the network parameters obtained from the utility. The deterministic and time series method is used for the three-phase HC determination while a stochastic method based on a simplified Monte Carlo simulation method is adopted for single-phase HC analysis. Voltage drop and equipment loading are the performance indices (PI) considered for the study and their limit is set according to the South African standard NRS097. The impact assessment result shows that increasing EV charging penetration will result in a corresponding movement of the PI toward the allowable limits. The HC results show that 5-8 three-phase connected EVs can charge simultaneously for the worst-case and 9-13 EVs for the best-case. Furthermore, the single-phase HC for the popular 3.7 kW EV charger is 15 and 8 EVs for the best-case and worst-case scenarios respectively. The result showing the seasonal variation in HC and for other EV charging power is also presented. It is observed that three-phase EV charging HC of the network is highest during the summer and the lowest during the winter season, while the difference in HC for the worst-case and best-case scenarios portrays the effect that the location of charging has on the HC.
Description: 
A dissertation submitted in fulfillment of the requirements for the degree of Master of Engineering in Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2023.
URI: https://hdl.handle.net/10321/5245
DOI: https://doi.org/10.51415/10321/5245
Appears in Collections:Theses and dissertations (Engineering and Built Environment)

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