Abstract
This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city’s urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE’s characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.
Highlights
Transports are nowadays mainly dependent on fossil fuels, implying large greenhouse gas emissions (Chapman, 2007)
The dynamic-PROMETHEE methodology was applied to obtain an “optimized” electric vehicles (EV) charging network in Angra do Heroísmo, considering that these would be located on existing parking spaces
The main objective of this work was to test this methodology for solving the problem associated with the planning of the number and location of charging points for EVs to deploy in a given area throughout a period of predefined time. This objective is achieved with the proposed methodology, dynamic-PROMETHEE
Summary
Transports are nowadays mainly dependent on fossil fuels, implying large greenhouse gas emissions (Chapman, 2007). The refueling time is much higher but the autonomy will be much lower which implies more refueling cycles. On the other hand others will have to use public car parking, being important to assure that the most suitable locations are made available for charging stations or points, especially in urban areas and these identified forehand. This process could be a chicken-and-egg dilemma, when identifying what comes first: the charging network or the EV users (Mak et al, 2013). EV users must not be conditioned by the lack of an adequate EV charging network in their normal routes
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