@article{JRC112429,
	address = {BASEL (SWITZERLAND)},
	year = {2018},
	author = {Rocha Pinto Lucas A and Prettico G and Flammini M and Kotsakis E and Fulli G and Masera M},
	abstract = {Electric vehicle (EV) charging infrastructure rollout iswell underway in several power systems, namelyNorthAmerica, Japan, Europe, and China. In order to support EVcharging 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.
		},
	title = {Indicator-based methodology for assessing EV charging infrastructure using exploratory data analysis},
	type = {Full paper},
	url = {http://www.mdpi.com/1996-1073/11/7/1869},
	volume = {11},
	number = {7},
	journal = {ENERGIES},
	pages = {1869},
	issn = {1996-1073},
	publisher = {MDPI AG},
	doi = {10.3390/en11071869}