Capova, K.A. and Wardle, R. and Bell, S. and Lyon, S. and Bulkeley, H.A. and Matthews, P.C. and Powells, G. (2015) 'High level summary of learning : electrical vehicle users.', Technical Report. Northern Powergrid (Northeast) Limited, Newcastle upon Tyne.
This report describes the CLNR trial which examined electric vehicles usage patterns and expected network loading in the event of large-scale take-up of electric vehicles. The trial involved domestic customers who owned an electric vehicle and had access to a home charger, analysis being carried out by Durham University’s CLNR project engineering and social science teams. Observations are based on a semi-qualitative analysis of EV dataset collated from online survey, face to face interviews with householders enrolled in the CLNR project, and power monitoring data collected from households and electric vehicle (EV) chargers. The CLNR project output is the largest socio-technical study of domestic EV charging in the UK and brings together monitoring data to examine electric vehicle usage patterns and expected network loading in the event of large-scale take-up of electric vehicles. Customers on the trial exhibit “working household” house demand profiles with EV demand profiles that track these. EV charging strongly follows domestic occupancy, especially as it relates to working patterns; the standard working day rhythms define and constrain EV charging patterns with weekend charging load different from weekdays. The EV charging practices show diurnal as well as seasonal patterns of activities. The EV load increases in winter months, likely due to battery charging demand (increased vehicle heating) and decreases in summer months (possibly) due to other factors such as summer holidays. This supports the predominant use the EV as a week-day car used to commute to work.
|Item Type:||Monograph (Technical Report)|
|Full text:||(VoR) Version of Record|
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|Publisher Web site:||http://www.networkrevolution.co.uk/project-library/high-level-summary-learning-electric-vehicle-users/|
|Date accepted:||23 January 2015|
|Date deposited:||28 October 2015|
|Date of first online publication:||January 2015|
|Date first made open access:||No date available|
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