Evaluating Long-Term Residential EV Charging Impacts on Distribution Systems

The transition from internal combustion vehicles to all electric and plug-in hybrid vehicles creates the potential for significant load growth for residential distribution systems. This paper provides a detailed EV charging impact study methodology using an EPRI test distribution feeder and parameters specific to the southeastern United States, particularly North Carolina. EV penetration is forecasted for NC for the years 2024–2035 based on historical EV registration data. Uncoordinated EV charging profiles are stochastically created using trip data from the 2017 National Household Travel Survey. EV load is stochastically allocated using household property tax values. A Monte-Carlo simulation approach with full year hourly (8760) power flows is used to determine the potential overloading and undervoltage impacts due to the additional EV load on the test feeder over a 12-year study period. The results found that the addition of the EV charging loads will cause significant overloading of grid assets and bus voltage violations with customer transformers being the most impacted.

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Publication Details

Published
2024-10-13
DOI
https://doi.org/10.1109/naps61145.2024.10741742
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.21
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article

Evaluating Long-Term Residential EV Charging Impacts on Distribution Systems

Wenyuan Tang, Mesut Baran, Matthew Gosnell
1 citations
Electric Vehicles and Infrastructure
0.21
article

Evaluating Long-Term Residential EV Charging Impacts on Distribution Systems

Wenyuan Tang, Mesut Baran, Matthew Gosnell
article en
1 citations

Abstract

The transition from internal combustion vehicles to all electric and plug-in hybrid vehicles creates the potential for significant load growth for residential distribution systems. This paper provides a detailed EV charging impact study methodology using an EPRI test distribution feeder and parameters specific to the southeastern United States, particularly North Carolina. EV penetration is forecasted for NC for the years 2024–2035 based on historical EV registration data. Uncoordinated EV charging profiles are stochastically created using trip data from the 2017 National Household Travel Survey. EV load is stochastically allocated using household property tax values. A Monte-Carlo simulation approach with full year hourly (8760) power flows is used to determine the potential overloading and undervoltage impacts due to the additional EV load on the test feeder over a 12-year study period. The results found that the addition of the EV charging loads will cause significant overloading of grid assets and bus voltage violations with customer transformers being the most impacted.

North Carolina State University (US)
Openalex Percentile: Top 46%
Electric Vehicles and Infrastructure
0.21
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