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Energies 2018, 11(7), 1869; https://doi.org/10.3390/en11071869

Indicator-Based Methodology for Assessing EV Charging Infrastructure Using Exploratory Data Analysis

European Commission, JRC, Directorate C Energy, Transport and Climate, PO Box 2, 1755 ZG Petten, The Netherlands
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Received: 27 June 2018 / Revised: 13 July 2018 / Accepted: 16 July 2018 / Published: 18 July 2018
(This article belongs to the Special Issue 10 Years Energies - Horizon 2028)
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Abstract

Electric vehicle (EV) charging infrastructure rollout is well under way in several power systems, namely North America, Japan, Europe, and China. In order to support EV charging infrastructures design and operation, little attempt has been made to develop indicator-based methods characterising such networks across different regions. This study defines an assessment methodology, composed by eight indicators, allowing a comparison among EV public charging infrastructures. The proposed indicators capture the following: energy demand from EVs, energy use intensity, charger’s intensity distribution, the use time ratios, energy use ratios, the nearest neighbour distance between chargers and availability, the total service ratio, and the carbon intensity as an environmental impact indicator. We apply the methodology to a dataset from ElaadNL, a reference smart charging provider in The Netherlands, using open source geographic information system (GIS) and R software. The dataset reveals higher energy intensity in six urban areas and that 50% of energy supplied comes from 19.6% of chargers. Correlations of spatial density are strong and nearest neighbouring distances range from 1101 to 9462 m. Use time and energy use ratios are 11.21% and 3.56%. The average carbon intensity is 4.44 gCO2eq/MJ. Finally, the indicators are used to assess the impact of relevant public policies on the EV charging infrastructure use and roll-out. View Full-Text
Keywords: charging infrastructure; electric vehicles; service ratio; network design; exploratory data analysis charging infrastructure; electric vehicles; service ratio; network design; exploratory data analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Lucas, A.; Prettico, G.; Flammini, M.G.; Kotsakis, E.; Fulli, G.; Masera, M. Indicator-Based Methodology for Assessing EV Charging Infrastructure Using Exploratory Data Analysis. Energies 2018, 11, 1869.

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