Impacts of EV residential charging and charging stations on quasi-static time-series PV hosting capacity

The increasing adoption of distributed energy resources, such as rooftop photovoltaic (PV) systems and electric vehicles (EVs), can cause adverse impacts in distribution systems, including the growth in PV hosting capacity (PVHC) and the depreciation of on-load tap changers (OLTC) lifetime. To analyze the impacts of these technologies in the network over the day, the quasi-static time series (QSTS) can be used with a resolution capable of performing the start and end times of the EVs charging and PV generation profile to observe the role of the OLTC in the grid. This work investigates the QSTS PVHC from the integration of EVs residential charging and in a public charging station (PCS) considering an unbalanced medium voltage (MV) network with and without OLCT. For this, a set of random variables for EV behavior are used, such as home and PCS arrival and departure times. The model is developed in Python and OpenDSS in a Monte Carlo simulation. In addition, the results show that the PCSs along the grid can increase the QSTS PVHC in MV networks that do not have OLTC. However, when the distribution system presents OLTC, the number of tap changes increases significantly if many EVs use the PCS. This result can drive actions by the distribution network operator to consider the distance between PCSs and OLTCs.