Date of Award


Document Type


Degree Name

Master of Science (MS)


Electrical and Computer Engineering (Holcomb Dept. of)

Committee Chair/Advisor

Dr. Johan Enslin

Committee Member

Dr. Sukumar Brahma

Committee Member

Dr. Christopher Edrington


Electric vehicles (EV) are growing in popularity and therefore adoption rate. Best estimates predict a 6.2% EV adoption rate by 2035 in the southeastern United States. With this level of EV adoption, utility planners must begin to consider the impact that EVs will have on the power grid. This paper aims to help predict these EV impacts on the power grid. Specifically, an urban-commercial feeder is analyzed in detail to provide worst-case and most-likely results of varying levels of EV impact. Results show that a 26.2% peak increase is the most likely result for this feeder in 2035.

Mitigation techniques are used to lower the impact that EVs will have on the power grid. A number of mitigation techniques are specifically analyzed for this urban-commercial feeder. The cost of each of these mitigation techniques is compared to their effectiveness. The best mitigation strategy is chosen to be a combination of time-of-use and a battery energy storage system because it gives the best results relative to cost and provides emergency capabilities.

In this study, system data is extracted from this urban-commercial feeder and combined with other feeder types to provide a utility scale EV impact. The scale-up model provides the most-likely scenario for future EV impacts on the entire utility’s power grid. This system level scale-up data can be used for integrated resource planning purposes.



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