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

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

doi:10.1016/j.apenergy.2015.01.144

Myriam Neaimeh, Robin Wardle + Show 7 more

Open Access

https://doi.org/10.1016/j.apenergy.2015.01.144

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Journal: Applied Energy	Publication Date: Mar 13, 2015
Citations: 161	License type: cc-by

Affiliation: Newcastle University, Durham University

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.

Highlights

The UK government passed the Climate Change Act which established a legally binding target of cutting the UK’s greenhouse gas emissions by at least 80% compared to 1990 levels by 2050 [1]
The datasets were used to study the impact of the uptake of Electric Vehicles (EVs) on distribution networks
The range of networks used demonstrated that Low Voltage (LV) networks are not a homogenous group and have different characteristics, sets of parameters and customer behaviour which illustrates the importance of bespoke studies

Summary

Introduction

The UK government passed the Climate Change Act which established a legally binding target of cutting the UK’s greenhouse gas emissions by at least 80% compared to 1990 levels by 2050 [1]. In order to make the transition to a low carbon economy, the government published the Carbon Plan in 2011 which sets outs a strategy to achieve the decarbonisation target across sectors. A quarter of the UK emissions come from the domestic transport sector which needs to substantially reduce its emissions by 2050. The q This paper is included in the Special Issue of Clean Transport edited by Prof.

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