Customer-driven design of the recharge infrastructure and Vehicle-to-Grid in urban areas: A large-scale application for electric vehicles deployment

Abstract

a b s t r a c tThe large scale deployment of electric vehicles in urban environment will play a key-role over the next decades to reduce air-pollutants in densely populated areas, but it will also require the development of an adequate recharge infrastructure. The purpose of this paper is to demonstrate how driving patterns databases and data mining can be used to appropriately design this infrastructure. This application focuses on the Italian province of Firenze, involving about 12,000 conventional fuel vehicles monitored over one month, estimating a fleet share shift from conventional fuel vehicles to battery electric vehicles ranging from 10% to 57%, and a mileage share shift from 1.6% to 36.5%. The increase of electric energy demand from electric vehicles ranges from 0.7% to 18% of the total demand in the province, with a number of charging spots three-to-six times higher than the number of circulating electric vehicles. Additionally the results show that a Vehicle-to-Grid interaction strategy can contribute to reduce from 5% to 50% the average daily electric energy demand in specific locations. This paper provides a description of the developed model and focuses on the valuable potential of the proposed methodology to support future policies for designing alternative fuel infrastructure in urban areas.

Utilization of electric vehicles and renewable energy sources used as distributed generators for improving characteristics of electric power distribution systems

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Survey of Smart Grid Concepts and Technological Demonstrations Worldwide Emphasizing on the Oman Perspective

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Performance of Electric Vehicle Charging Infrastructure: Development of an Assessment Platform Based on Charging Data

“…The models mentioned above tend to focus on the early phase of a charging infrastructure roll-out [5,7,8]. Traffic flow data and GPS data are used to model charging infrastructure locations [8,12], not taking into account real-life utilization of the charging infrastructure. Only a few studies use real-life charging data to either model or assess the utilization of the charging infrastructure.…”