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Quantifying the long-term power system benefits of electric vehicles
Author(s)
Date Issued
2012-01
Date Available
2013-10-11T15:41:50Z
Abstract
The re-emergence of battery electric vehicles presents a potentially vast flexible resource to the power system at a time when renewable generation is pushing the ability of power systems to respond to increased levels of variability in production. Large installed quantities of wind and solar power in certain systems will cause changes in the operation of conventional generators that, over time, will reduce the economic feasibility of cost-effective but inflexible forms of generation. This can be avoided if electric vehicles can be used to mitigate the overall level of system variability by charging at times when production by conventional generators is at its lowest. This paper presents a methodology for determining the degree to which electric vehicles will influence future generation plant investment and a means of calculating the reduction in total system costs owing to the presence of optimally charged electric vehicles. This model is applied to a test system based on the state of Texas. It is found that the long-term benefits of electric vehicles are significant and continue to increase for all vehicle penetration levels studied. However, the relationship between levels of installed variable renewables and electric vehicle benefit was found to be highly dependent on the extent to which both of these parameters influenced the least-cost plant portfolio.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1
End Page
6
Copyright (Published Version)
2012 Institute of Electrical and Electronics Engineers
Language
English
Status of Item
Peer reviewed
Conference Details
2012 IEEE PES Innovative Smart Grid Technologies (ISGT), , Washington, DC, USA
ISBN
978-1-4577-2159-5
This item is made available under a Creative Commons License
File(s)
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Name
Shortt_ISGT_2012 Quantifying the Long-term Power.pdf
Size
717.29 KB
Format
Adobe PDF
Checksum (MD5)
47463c798ea0ad4cea0e9a1341d2a448
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