Print Email Facebook Twitter Design directions for reducing the peak load on the residential grid using electric vehicles Title Design directions for reducing the peak load on the residential grid using electric vehicles: Simulating the behaviour of electric vehicle owners using the concepts of Social Acceptance and Moral Acceptability in an Agent-Based model Author Bloemhof, Jesse (TU Delft Technology, Policy and Management) Contributor Chappin, E.J.L. (mentor) van de Poel, I.R. (graduation committee) Kwakkel, J.H. (mentor) de Wildt, T.E. (mentor) Degree granting institution Delft University of Technology Programme Complex Systems Engineering and Management (CoSEM) Date 2018-08-27 Abstract Due to the transition to sustainable transport, an increase of the share of electric vehicles is expected. The electric vehicles will increase the peak demand on the electricity grid. It is possible to shift the demand of the electric vehicles using smart grid technology. The electric vehicle owners have the option to use this smart electric vehicle system. Using the concepts of social acceptance and moral acceptability an agent-based model is used to simulate the use of the smart EV system. Based on this agent-based model possible design directions are identified for the smart EV system which reduce the expected electricity grid problems sufficiently in the long-term. For the smart EV system to be as effective as possible vehicle to grid technology in combination with an algorithm which optimizes on the network capacity have should be used. However, these options were the least accepted by the EV owners and therefore further research is required. The next step for research is to develop a businesses models for the design directions discussed in this thesis. Subject Electric VehiclesMoral AcceptabilitySocial AcceptanceAgent-Based Modelling and SimulationSmart Grid To reference this document use: http://resolver.tudelft.nl/uuid:88b5b49a-c7c5-45f0-95e8-3bf7fb3c8857 Part of collection Student theses Document type master thesis Rights © 2018 Jesse Bloemhof Files PDF Master_Thesis_Jesse_Bloemhof.pdf 4.14 MB Close viewer /islandora/object/uuid:88b5b49a-c7c5-45f0-95e8-3bf7fb3c8857/datastream/OBJ/view