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A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

Author

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  • Neaimeh, Myriam
  • Wardle, Robin
  • Jenkins, Andrew M.
  • Yi, Jialiang
  • Hill, Graeme
  • Lyons, Padraig F.
  • Hübner, Yvonne
  • Blythe, Phil T.
  • Taylor, Phil C.

Abstract

This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.

Suggested Citation

  • Neaimeh, Myriam & Wardle, Robin & Jenkins, Andrew M. & Yi, Jialiang & Hill, Graeme & Lyons, Padraig F. & Hübner, Yvonne & Blythe, Phil T. & Taylor, Phil C., 2015. "A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts," Applied Energy, Elsevier, vol. 157(C), pages 688-698.
    • Handle: RePEc:eee:appene:v:157:y:2015:i:c:p:688-698
    DOI: 10.1016/j.apenergy.2015.01.144
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    References listed on IDEAS

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    1. Munkhammar, Joakim & Widén, Joakim & Rydén, Jesper, 2015. "On a probability distribution model combining household power consumption, electric vehicle home-charging and photovoltaic power production," Applied Energy, Elsevier, vol. 142(C), pages 135-143.
    2. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    3. Pudjianto, Danny & Djapic, Predrag & Aunedi, Marko & Gan, Chin Kim & Strbac, Goran & Huang, Sikai & Infield, David, 2013. "Smart control for minimizing distribution network reinforcement cost due to electrification," Energy Policy, Elsevier, vol. 52(C), pages 76-84.
    4. Salah, Florian & Ilg, Jens P. & Flath, Christoph M. & Basse, Hauke & Dinther, Clemens van, 2015. "Impact of electric vehicles on distribution substations: A Swiss case study," Applied Energy, Elsevier, vol. 137(C), pages 88-96.
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