Planning for electric vehicle needs by coupling charging profiles with urban mobility
Yanyan Xu,
Serdar Çolak,
Emre C. Kara,
Scott J. Moura and
Marta C. González ()
Additional contact information
Yanyan Xu: Massachusetts Institute of Technology
Serdar Çolak: Massachusetts Institute of Technology
Emre C. Kara: SLAC National Accelerator Laboratory
Scott J. Moura: University of California
Marta C. González: Massachusetts Institute of Technology
Nature Energy, 2018, vol. 3, issue 6, 484-493
Abstract:
Abstract The rising adoption of plug-in electric vehicles (PEVs) leads to the temporal alignment of their electricity and mobility demands. However, mobility demand has not yet been considered in electricity planning and management. Here, we present a method to estimate individual mobility of PEV drivers at fine temporal and spatial resolution, by integrating three unique datasets of mobile phone activity of 1.39 million Bay Area residents, census data and the PEV drivers survey data. Through coupling the uncovered patterns of PEV mobility with the charging activity of PEVs in 580,000 session profiles obtained in the same region, we recommend changes in PEV charging times of commuters at their work stations and shave the pronounced peak in power demand. Informed by the tariff of electricity, we calculate the monetary gains to incentivize the adoption of the recommendations. These results open avenues for planning for the future of coupled transportation and electricity needs using personalized data.
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natene:v:3:y:2018:i:6:d:10.1038_s41560-018-0136-x
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DOI: 10.1038/s41560-018-0136-x
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