Javascript must be enabled for the correct page display

Optimality Control and Social Behavior of Electric Vehicles with Vehicle-to-Grid Options

de Graaf, Piter (2020) Optimality Control and Social Behavior of Electric Vehicles with Vehicle-to-Grid Options. Research Project, Industrial Engineering and Management.

[img]
Preview
Text
mIEM_2020_deGraafP.pdf

Download (2MB) | Preview
[img] Text
toestemming.pdf
Restricted to Registered users only

Download (95kB)

Abstract

Due to the electrification of the transport sector, electric travel appears to become dominant. Alongside this, the penetration of renewable energy sources (RESs) increases. Smart charging addresses challenges resulting from both these trends. It reduces the peak load demand of EVs and brings flexible stabilizing capacity to the grid. For smart charging to be successful the participation of EV owners is required. However, the behavior of EV owners related to smart charging is neither well analyzed nor effectively quantified. This work's contributions include: (1) an analysis of survey results regarding EV owners' social behavior related to smart charging, (2) a proposal of a novice hierarchic and dynamic smart charging framework in which social behavior is embedded, (3) an expansion of this framework with wind power generation, and, (4) the simulation results of the proposed model. The simulation results confirm that smart charging is beneficial to the stability of the power grid. Furthermore, it shows that the willingness of EV owners to follow a smart charging contract should be increased, in order to increase the stabilizing capacity of EVs. Moreover, the survey results show that a financial incentive is not necessarily a strong motivator to convince EV owners to participate in smart charging. It is proposed that putting emphasis on the environmental benefits of smart charging will increase their willingness to smart charge.

Item Type: Thesis (Research Project)
Supervisor name: Scherpen, J.M.A. and Larsen, G.K.H.
Degree programme: Industrial Engineering and Management
Thesis type: Research Project
Language: English
Date Deposited: 23 Jun 2020 13:00
Last Modified: 23 Jun 2020 13:00
URI: https://fse.studenttheses.ub.rug.nl/id/eprint/22104

Actions (login required)

View Item View Item