Smarter Charging

Modeling optimal EV charging in solar parking lots for reducing peak demand, considering uncertainty in solar power forecasting and EV energy demand

Master Thesis (2019)
Author(s)

Y.D. Snow (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Ad J.M. van Wijk – Mentor (TU Delft - Energy Technology)

R. Ghotge – Mentor (TU Delft - Energy Technology)

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2019 Yitzi Snow
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Yitzi Snow
Graduation Date
29-08-2019
Awarding Institution
Delft University of Technology
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Smart charging offers the potential for electric vehicles to use renewable energy more efficiently, lowering costs and improving the stability of the electricity grid. Many computer models have been developed to simulate the behavior of smart charging. Yet these models often assume that future information is known perfectly, including when vehicles will begin charging and how much solar energy will be available at that time. In reality, this information is subject to uncertainty, meaning the performance of smart charging may be worse than predicted by these models. This report details the development of an improved model which considers future uncertainty in smart charging behavior. It is determined that uncertainty does decrease the effectiveness of smart charging, but with strategies that are able to robustly consider this uncertainty smart charging can still offer tremendous benefits over traditional uncoordinated charging.

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