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GIS-based modelling of electric-vehicle–grid integration in a 100% renewable electricity grid

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  • Li, Mengyu
  • Lenzen, Manfred
  • Wang, Dai
  • Nansai, Keisuke

Abstract

We examine the spatio-temporal interactions of widespread electric vehicle (EV) charging with a future, 100% renewable electricity system in Australia. More specifically, we use a GIS-based electricity supply-demand model simulating an hourly competitive-bidding process over an entire year. We obtain least-cost grid configurations that include both renewable energy (RE) generators and EVs, the latter under both uncontrolled and controlled charging, and adoption rates between 0 and 100%. We characterise the vehicle-to-grid interaction in terms of overall installed capacity, hourly generation and spillage, levelized cost of electricity (LCOE), as well as transmission network expansion topology. We show that supplying 100% renewable electricity to cover current electricity needs in Australia, as well as powering all Australian passenger vehicles as controlled-charged EVs, requires 205 GW of installed capacity at an LCOE of 14.7 AUD¢/kWh. This 100% RE supply with EV charging leads to an additional electricity cost of 1710 AUD/capita annually, comparing to the current annual expenditure for electricity and conventional vehicle fuel.

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  • Li, Mengyu & Lenzen, Manfred & Wang, Dai & Nansai, Keisuke, 2020. "GIS-based modelling of electric-vehicle–grid integration in a 100% renewable electricity grid," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300891
    DOI: 10.1016/j.apenergy.2020.114577
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    References listed on IDEAS

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