Charging electric vehicles using opportunistic stopovers

The diffusion of electric vehicles asks for efficient energy replenishment, which requires geographical and temporal coordination of shared charging resources. We introduce a novel charging methodology that exploits users' opportunistic mobility. This paper focuses on vehicle stopovers detecting potential charging opportunities. Our mobility-assisted methodology protects users privacy and permits a hybrid centralized/distributed approach avoiding clashes with other potential users. A preliminary analysis on our charging system, obtained with mobility data from the field, shows that among the available charging stations, some are more relevant and have a key role in serving electric vehicle recharge. This can be useful for further investigation on designing charging networks and aggregating electric vehicles towards charging stations.

[1]  Kay W. Axhausen,et al.  Plug-in hybrid electric vehicles and smart grids: Investigations based on a microsimulation , 2013 .

[2]  P. Gallo,et al.  Fairs for e-commerce: the benefits of aggregating buyers and sellers , 2016, 1602.09071.

[3]  Keith Corzine,et al.  Real-time modeling of distributed plug-in vehicles for V2G transactions , 2009, 2009 IEEE Energy Conversion Congress and Exposition.

[4]  George Gross,et al.  A conceptual framework for the vehicle-to-grid (V2G) implementation , 2009 .

[5]  Leonardo Badia,et al.  Markov models for electric vehicles: the role of battery parameters and charging point frequency , 2015, 2015 IEEE 20th International Workshop on Computer Aided Modelling and Design of Communication Links and Networks (CAMAD).

[6]  Tony Markel,et al.  Using Global Positioning System Travel Data to Assess Real-World Energy Use of Plug-In Hybrid Electric Vehicles , 2007 .

[7]  M. Ilic,et al.  Optimal Charge Control of Plug-In Hybrid Electric Vehicles in Deregulated Electricity Markets , 2011, IEEE Transactions on Power Systems.

[8]  M. Ferdowsi,et al.  Utilization and effect of plug-in hybrid electric vehicles in the United States power grid , 2008, 2008 IEEE Vehicle Power and Propulsion Conference.

[9]  Hao Liang,et al.  Mobility-Aware Coordinated Charging for Electric Vehicles in VANET-Enhanced Smart Grid , 2014, IEEE Journal on Selected Areas in Communications.

[10]  J. Driesen,et al.  The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid , 2010, IEEE Transactions on Power Systems.

[11]  Mike Marshall,et al.  A novel approach for evaluating the impact of electric vehicles on the power distribution system , 2010, IEEE PES General Meeting.

[12]  Thomas H. Bradley,et al.  The effect of communication architecture on the availability, reliability, and economics of plug-in hybrid electric vehicle-to-grid ancillary services , 2010 .

[13]  Mor Harchol-Balter Performance Modeling and Design of Computer Systems: The M/G/1 Queue and the Inspection Paradox , 2013 .

[14]  Fosca Giannotti,et al.  Mining mobility user profiles for car pooling , 2011, KDD.

[15]  Goran Andersson,et al.  On integration of plug-in hybrid electric vehicles into existing power system structures , 2010 .

[16]  Joeri Van Mierlo,et al.  Energy Consumption Prediction for Electric Vehicles Based on Real-World Data , 2015 .