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Optimizing Charging Strategies for Electric Vehicle Owners: A Comparison of Charging Strategies to Schedule Optimal Home Charging

Enger, Thea Kristin; Nøstvik, Maria Melby
Master thesis
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URI
https://hdl.handle.net/11250/3017727
Date
2022
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  • Master Thesis [4207]
Abstract
The rapid growth in the Norwegian electric vehicle market has put Norway in a unique

position as the leading country in electric vehicle adoption. With few challenges in the

establishment of charging infrastructure, most electric vehicle owners will at some point

charge their vehicle at home. The charging process of the vehicles can utilize business

analytics to schedule the charging to optimize the desired objectives.

In this thesis, we performed a comparison of charging strategies for electric vehicle owners

to schedule optimal charging at home. The charging strategies differ in the time periods of

charging and are based on the charging behavior of electric vehicle owners in Norway. In

order to compare the strategies, we developed a linear programming model that minimizes

the charging cost. The spot prices of electricity for 2021 was retrieved as the thesis is

conducted in a retrospective manner.

The thesis finds that the flexible night strategy would have experienced the lowest annual

charging cost of 1935.36 NOK. In addition, we find the most costly annual charging cost

of 2584.01 NOK associated with the forced afternoon strategy. This is a cost increase of

approximately 34% compared to the strategy with the lowest annual cost. The results

imply that the flexible strategies which can charge at any hour during the day choose to

charge the most at night.

This thesis further investigates how the charging costs would be affected if the new network

tariff model, to be implemented on July l, 2022, was implemented in 2021. The results

show that the new network tariffwould lead to an increase in the variable charging cost for

the strategies charging in the afternoon. In contrast, the results imply that the strategies

utilizing the off-peak hours of electricity would have experienced a decrease in the variable

cost. Lastly, adjustments in the battery capacity and driving range of the electric vehicle

were made to investigate the cost effect on the strategies. The results show a decrease in

the charging cost as the range increases. The most considerable cost reduction is seen

when the range increases from 200 km to 300 km for all the charging strategies.

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