Comprehensive Assessment of Electric Vehicle Charging Impact on Distribution Networks: Integrating Diversity in Fleet and Electricity Tariffs

With the ongoing trend of electrification in transportation, the charging demand from electric vehicles (EVs) is imposing an increasingly significant additional load on the existing power grid, especially on distribution networks. To reduce the short-term high peak demand of the distribution network, cost-effective electricity prices, such as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">time-of-use</i> (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TOU</i>) tariffs, have been introduced to encourage EV customers to shift their load demand to off-peak periods. However, no existing studies have comprehensively analyzed the impacts of EV charging on distribution networks considering the effects of key parameters such as the proportion of customers on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TOU tariffs, EV penetration levels</i>, various <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">daily charging frequencies</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">charging power levels</i>. To address this gap, this paper proposes an innovative modelling approach that incorporates various proportions of these parameters. Critical analyses are presented for a real distribution network in South Australia with year-round smart meter data. The results indicate that this approach enhances the ability to assess the impact of EV charging on distribution networks by integrating the combined effects of key parameters. At <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">80% EV penetration</i>, the evening peak demand under 100% <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Flat tariff</i> increases by over 30%. If 25% of the customers charge EVs using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TOU tariffs</i>, the maximum transformer utilization during the evening peak can be reduced by approximately 8.5%; however, this results in a new demand peak at the beginning of the TOU <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off-peak period</i>. For most load scenarios, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">existing TOU tariffs</i> exacerbates network load fluctuations and increases maximum transformer utilization.