Hosting Capacity Assessment of Residential Distribution Network for Growing Electric Vehicle Charging Demand

The widespread adoption of EVs will pose challenges to the planning and operation of the electric power grid if their charging is not coordinated and controlled. Therefore, the projection of EV load growth and hosting capacity analysis of EV charging infrastructure is critical for the power distribution grid. This study has investigated EV load projection in the state of North Dakota based on EV sales information, daily travel data, and temperature variations in North Dakota and investigated the load hosting capacity of a residential distribution system. An incremental hosting capacity analysis (HCA) was performed, and results show that the delayed/midnight charging strategy performs significantly better than the immediate/uncontrolled charging of EVs in the residential distribution grid. The addition of distributed generators with storage systems also improves the overall hosting capacity of the distribution network.

I. Introduction

Global warming and climate change have altered the energy landscape for the last decade. The rise of sustainable and green energy has played a critical role in de-escalating energy and environmental issues. Electric vehicles (EVs) are critical in reducing global carbon emissions and promoting green energy. However, the growth of the EV fleet can contribute to a significant increase in energy demand and will require extensive integration studies. Uncoordinated EV charging in any location with a large concentration of EV can coincide with local peak loads and substantially impact the distribution network. The EV-charging demand is intermittent and relies on the vehicle’s energy consumption, the user’s charging preference, and the ambient temperature. Typically, EV owners charge their vehicles either at home or away. The charging behavior is generally erratic, as EV owners can charge for an indefinite duration at any time of the day. Ambient temperature also plays a significant role in determining EV battery-charging efficiency. Overall, EV charging demand projection needs an in-depth study of all these variables.