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The widespread adoption of electric vehicles (EVs) has induced profound transformations in the resulting power demand and voltage profile of the low-voltage utility grids. The impact of this paradigm shift is contingent upon subtle factors, including the power rating of EV chargers, point of installation, prevailing power demand profiles, and driving patterns (dictating kWh energy of EV load). The introduction of EV loads without considering these factors and the subsequent comprehensive analysis will result in grid congestion, heightened peak demand, and augmented system losses. To address this, this paper presents a comprehensive case study of determining the EV hosting capacity of Qatar's utility grid, considering real-world demand profile data, existing load types, and their corresponding variation pattern. Secondly, considering the energy and instantaneous power requirement of EV load, the EV hosting is estimated using a 24-hour profile considering all EV charger types (DC fast chargers, level-2 chargers, and domestic chargers). A 2-step optimization algorithm is proposed to maximize the hosting capacity by optimally distributing the charging load among the residential nodes, without any events of grid congestion. Detailed simulation results show that EV charging load up to 11.4% of the distribution system rating can be accommodated without grid congestions.
Rahman et al. (Sun,) studied this question.