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)

Authors

Y.D. Snow Electrical Engineering, Mathematics and Computer Science

Contributors

A.J.M. van Wijk Energy Technology - Mechanical, Maritime and Materials Engineering (supervisor 1)
R. Ghotge Energy Technology - Mechanical, Maritime and Materials Engineering (supervisor 1)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Yitzi Snow
Optimization Modeling Electric Vehicle Solar Forecasting Smart grid Smart charging Uncertain systems
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Published Date

29-08-2019

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

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.