We consider a network of electric vehicles (EVs) and its components: vehicles, charging stations, and coalitions of stations. For such a setting, we propose a model in which individual stations, coalitions of stations, and vehicles interact in a market revolving around the energy for battery recharge. We start by separately studying 1) how autonomously operated charging stations form coalitions; 2) the price policy enacted by such coalitions; and 3) how vehicles select the charging station to use, working toward a time/price tradeoff. Our main goal is to investigate how equilibrium in such a market can be reached. We also address the issue of computational complexity, showing that, through our model, equilibria can be found in polynomial time. We evaluate our model in a realistic scenario, focusing on its ability to capture the advantages of the availability of an intelligent transportation system supporting the EV drivers. The model also mimics the anticompetitive behavior that charging stations are likely to follow, and it highlights the effect of possible countermeasures to such a behavior.
A Holistic View of ITS-Enhanced Charging Markets / Malandrino, Francesco; Casetti, CLAUDIO ETTORE; Chiasserini, Carla Fabiana. - In: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS. - ISSN 1524-9050. - STAMPA. - 16:4(2015), pp. 1736-1745. [10.1109/TITS.2014.2371478]
A Holistic View of ITS-Enhanced Charging Markets
MALANDRINO, FRANCESCO;CASETTI, CLAUDIO ETTORE;CHIASSERINI, Carla Fabiana
2015
Abstract
We consider a network of electric vehicles (EVs) and its components: vehicles, charging stations, and coalitions of stations. For such a setting, we propose a model in which individual stations, coalitions of stations, and vehicles interact in a market revolving around the energy for battery recharge. We start by separately studying 1) how autonomously operated charging stations form coalitions; 2) the price policy enacted by such coalitions; and 3) how vehicles select the charging station to use, working toward a time/price tradeoff. Our main goal is to investigate how equilibrium in such a market can be reached. We also address the issue of computational complexity, showing that, through our model, equilibria can be found in polynomial time. We evaluate our model in a realistic scenario, focusing on its ability to capture the advantages of the availability of an intelligent transportation system supporting the EV drivers. The model also mimics the anticompetitive behavior that charging stations are likely to follow, and it highlights the effect of possible countermeasures to such a behavior.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2574938
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