Increasing participation in V2G through contract elements

Examining the preferences of Dutch EV users regarding V2G contracts using a stated choice experiment

Master Thesis (2019)
Author(s)

J. Zonneveld (TU Delft - Technology, Policy and Management)

Contributor(s)

Caspar Chorus – Mentor (TU Delft - Engineering, Systems and Services)

M Kroesen – Mentor (TU Delft - Transport and Logistics)

Emile J.L. Chappin – Graduation committee member (TU Delft - Energy and Industry)

R. Wolbertus – Coach (TU Delft - Transport and Logistics)

Faculty
Technology, Policy and Management
Copyright
© 2019 Jip Zonneveld
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Jip Zonneveld
Graduation Date
25-03-2019
Awarding Institution
Delft University of Technology
Programme
['Complex Systems Engineering and Management (CoSEM)']
Faculty
Technology, Policy and Management
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Abstract

The increased usage of Electric Vehicles and Renewable Energy Sources causes issues regarding the balancing of the electricity grid. To avoid investment costs, Distribution System Operators desire flexibility solutions. One of these flexibility solutions is the usage of the battery of the Electric Vehicle as an electricity source. This concept is known as Vehicle to Grid (V2G). However, providing V2G services might cause discomfort for the Electric Vehicle user. A contract can be used to compensate the user for the experienced discomfort. Literature on these contracts is lacking and the behaviour of EV user to these contracts is unknown. This study aims to close this gap. Data is collected by means of a web survey and evaluated with a multinomial logit model. It is shown that the difference in expected demand for price- and volume-based contracts is minimal. In addition, three contract elements can solely increase demand for V2G but require high levels. More value is created when a combination of these three contract elements is used. It would be valuable to understand how and where V2G can provide value. To do so, the results of this study can be used as input for a dynamic model that evaluates day-to-day electricity supply and demand.

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