engleski

A Data-driven Framework for Extending Electric Vehicle Charging Infrastructure

Nowadays, CO2 emissions are considered one of prime factors in global warming and the concentration of greenhouse gasses (GHG) is constantly growing. Main contributor to the CO2 emission is a transportation sector. Possible solution for the rising GHG problem is the wide acceptance of the green transportation such as electric vehicles (EVs) [1]. Although EV popularity and market penetration are growing, a range anxiety, defined as the fear of running out of electricity before reaching available (i.e. unoccupied) charging station (CS) [2], is still a key factor with a high (negative) influence on (potential) EV owners. Based on the described, the following research question was formed: “Where should an EV charging infrastructure provider add a new CS?”. Answering that question is a very important step towards a higher acceptance of EVs because a higher amount of available CSes, as well as their strategical geo-distribution, would significantly lower the EV owner range anxiety.

Energy informatics ; Computational framework ; Electric vehicles

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