Key points are not available for this paper at this time.
With global efforts underway to reduce greenhouse gas emissions and protect the world's finite oil sources, the advent of electric vehicles (EVs) has emerged as a viable solution to address these imperatives. The present study endeavors to establish a comprehensive framework for investigating the implications of EV integration within medium voltage distribution networks, considering both normal and faulty scenarios. Additionally, the study explores the impact of distributed generation units (DGs) on this integration. The impact assessment entails evaluating power losses and the total voltage stability index (TVSI) as indicators of normal system performance. In the case of abnormal conditions, the analysis shifts to examining fault currents. Notably, the study is conducted considering the uncertainty associated with both the loading ratio (LR) and the random power consumption of EVs during fast charging. To address this uncertainty, the proposed approach employs Hong's-Point Estimate Method (PEM), specifically utilizing the (2m+1) scheme. This methodology is applied to IEEE 69-bus and 85-bus systems using MATLAB software, supplemented by ETAP short circuit analysis to validate the results. In order to verify the framework, different locations of charging stations along the systems’ buses are tested with varying their number between one and two charging stations, while assuming a total of 250 EVs, which doubles to 500 in subsequent analyses. The study explores the impact of EV stations placement in DG-integrated distribution networks on power losses, voltage stability, and fault current levels, suggesting a trade-off in allocation strategies. The results underscore the critical challenges posed by the widespread adoption of EVs, particularly in terms of increased power losses and fault current levels. While the number of charging stations has a limited effect, the total number of EVs and their load characteristics are the primary factors affecting system stability.
Shaheen et al. (Tue,) studied this question.