Electric vehicles are accelerating the world's transition to sustainable energy. Nevertheless, the lack of a proper charging station infrastructure in many real implementations still represents an obstacle for the spread of such a technology. In this paper, we present a real case application of optimization techniques in order to solve the location problem of electric charging stations in the district of Biella, Italy. The plan is composed by several progressive installations and decision makers pursue several objectives that might be in contrast. For this reason, we present an innovative framework based on the comparison of several ad-hoc Key Performance Indicators for evaluating many different aspects of a location solution.

KPIs for Optimal Location of charging stations for Electric Vehicles: the Biella case-study / Fadda, Edoardo; Manerba, Daniele; Tadei, Roberto; Camurati, Paolo Enrico; Cabodi, Gianpiero. - ELETTRONICO. - 18:(2019), pp. 123-126. (Intervento presentato al convegno 12th International Workshop on Computational Optimization tenutosi a Leipzig, Germany nel September 1-4) [10.15439/2019F171].

KPIs for Optimal Location of charging stations for Electric Vehicles: the Biella case-study

Edoardo Fadda;Daniele Manerba;Roberto Tadei;Paolo Camurati;Gianpiero Cabodi
2019

Abstract

Electric vehicles are accelerating the world's transition to sustainable energy. Nevertheless, the lack of a proper charging station infrastructure in many real implementations still represents an obstacle for the spread of such a technology. In this paper, we present a real case application of optimization techniques in order to solve the location problem of electric charging stations in the district of Biella, Italy. The plan is composed by several progressive installations and decision makers pursue several objectives that might be in contrast. For this reason, we present an innovative framework based on the comparison of several ad-hoc Key Performance Indicators for evaluating many different aspects of a location solution.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2768132
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