Scheduling electric vehicle charging to minimise carbon emissions and wind curtailment. (December 2020)
- Record Type:
- Journal Article
- Title:
- Scheduling electric vehicle charging to minimise carbon emissions and wind curtailment. (December 2020)
- Main Title:
- Scheduling electric vehicle charging to minimise carbon emissions and wind curtailment
- Authors:
- Dixon, James
Bukhsh, Waqquas
Edmunds, Calum
Bell, Keith - Abstract:
- Abstract: This paper presents an investigation of the potential for coordinated charging of electric vehicles to i) reduce the CO2 emissions associated with their charging by selectively charging when grid carbon intensity (gCO2/kWh) is low and ii) absorb excess wind generation in times when it would otherwise be curtailed. A method of scheduling charge events that seeks the minimum carbon intensity of charging while respecting EV and network constraints is presented via a time-coupled linearised optimal power flow formulation, based on plugging-in periods derived from a large travel dataset. Schedules are derived using real half-hourly grid intensity data; if charging in a particular event can be done entirely through use of renewable energy that would otherwise have been curtailed, its carbon intensity is zero. It was found that if 'dumb' charged from the current UK mainland (GB) grid, average emissions related to electric vehicle (EV) charging are in the range 35–56 gCO2/km; this can be reduced to 28–40 gCO2/km by controlled charging – approximately 20–30% of the tailpipe emissions of an average new petrol or diesel car sold in Europe. There is potential for EVs to absorb excess wind generation; based on the modelled charging behaviour, 500, 000 EVs (20% of Scotland's current car fleet) could absorb around three quarters of curtailment at Scotland's largest onshore wind farm. Highlights: Electric vehicle (EV) charging is scheduled for minimum carbon intensity. EVs'Abstract: This paper presents an investigation of the potential for coordinated charging of electric vehicles to i) reduce the CO2 emissions associated with their charging by selectively charging when grid carbon intensity (gCO2/kWh) is low and ii) absorb excess wind generation in times when it would otherwise be curtailed. A method of scheduling charge events that seeks the minimum carbon intensity of charging while respecting EV and network constraints is presented via a time-coupled linearised optimal power flow formulation, based on plugging-in periods derived from a large travel dataset. Schedules are derived using real half-hourly grid intensity data; if charging in a particular event can be done entirely through use of renewable energy that would otherwise have been curtailed, its carbon intensity is zero. It was found that if 'dumb' charged from the current UK mainland (GB) grid, average emissions related to electric vehicle (EV) charging are in the range 35–56 gCO2/km; this can be reduced to 28–40 gCO2/km by controlled charging – approximately 20–30% of the tailpipe emissions of an average new petrol or diesel car sold in Europe. There is potential for EVs to absorb excess wind generation; based on the modelled charging behaviour, 500, 000 EVs (20% of Scotland's current car fleet) could absorb around three quarters of curtailment at Scotland's largest onshore wind farm. Highlights: Electric vehicle (EV) charging is scheduled for minimum carbon intensity. EVs' potential to absorb excess renewables by charging selectively is investigated. Real GB grid carbon intensity (gCO2 /kWh) and wind curtailment data used. Scheduling can reduce EV emissions from 35 to 56 gCO2 /km to 28–40 gCO2 /km. 500, 000 EVs can absorb 75% of curtailment at GB's largest onshore wind farm. … (more)
- Is Part Of:
- Renewable energy. Volume 161(2020)
- Journal:
- Renewable energy
- Issue:
- Volume 161(2020)
- Issue Display:
- Volume 161, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 161
- Issue:
- 2020
- Issue Sort Value:
- 2020-0161-2020-0000
- Page Start:
- 1072
- Page End:
- 1091
- Publication Date:
- 2020-12
- Subjects:
- Electric vehicles -- Renewable energy -- Carbon intensity -- Optimisation -- Scheduling
Renewable energy sources -- Periodicals
Power resources -- Periodicals
Énergies renouvelables -- Périodiques
Ressources énergétiques -- Périodiques
333.794 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09601481 ↗
http://www.elsevier.com/journals ↗
http://www.journals.elsevier.com/renewable-energy/ ↗ - DOI:
- 10.1016/j.renene.2020.07.017 ↗
- Languages:
- English
- ISSNs:
- 0960-1481
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7364.187000
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British Library HMNTS - ELD Digital store - Ingest File:
- 14314.xml