Latest revision as of 11:54, 16 February 2021

Abstract

This paper identifies the risks for the functionality and reliability of the grid that arise from the integration of the transport and supply chain. The electrification of transport is a promising option for the transition to a low carbon energy and transport system. But on the short term, the electrification of transport also creates risks. More specifically, when promising technological such as vehicle-to-grid and smart-grids are not yet available on a large scale, the rapid diffusion of electric vehicles and the recharging behaviour of consumers can create risks for grid functioning. In order to assess these risks, this paper present a GIS-based simulation method that assesses electricity demand and supply on the neighbourhood level. The paper combines local level electric vehicle diffusion forecasts, with neighbourhood level data about the grid additional capacity. Application of the model to the Netherlands shows that risks for grid functioning already appear as early as 2015. More specifically, the diffusion of electric vehicles is found to compromise the functioning of the grid on the short term in densely populated areas such as Amsterdam. In these neighbourhoods early and fast adoption of electric vehicles coincides with the presence of an older grid with less additional capacity. The model provides insights for grid operators as well as for policy makers that seek to stimulate the transition to sustainable energy and transport systems, and can be used as a strategic tool to plan (smart) grid investments.

Original document

The different versions of the original document can be found in:

• http://dx.doi.org/10.1016/j.apenergy.2013.12.017 under the license http://creativecommons.org/licenses/by-nc-nd/3.0/

• https://doi.org/10.1016/j.apenergy.2013.12.017 under the license cc-by-nc-nd

• https://dspace.library.uu.nl/handle/1874/314062

• https://api.elsevier.com/content/article/PII:S0306261913010167?httpAccept=text/xml,

https://api.elsevier.com/content/article/PII:S0306261913010167?httpAccept=text/plain,

http://dx.doi.org/10.1016/j.apenergy.2013.12.017 under the license https://www.elsevier.com/tdm/userlicense/1.0/

• https://www.sciencedirect.com/science/article/pii/S0306261913010167,

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https://academic.microsoft.com/#/detail/2138330733