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Mémoires Année : 2013

Distributed optimization of electric vehicles recharge in an urban environment

Résumé

The era of sustainable development has brought Electric Vehicles (EVs) to the spotlight. Since recharging an electric vehicle can take up to ten or more times the power consumption of a household, an increasing EV penetration in the market poses a challenge for the electricity companies. Using the Internet of Things (IoT) approach, we propose a model where electric vehicles communicate with the electrical grid infrastructure in order to determine the charging station where they should go to. We have consequently built a simulator, mixing both a microscopic traffic simulation and a complete network simulation including radio propagation analysis. In this work we run several simulations over a test map, taking service and network-level metrics, comparing four basic charging station assignment strategies. Our final analysis draws relevant conclusions concerning the fundamental aspects to take into account for developing a distributed system that optimizes the charging station assignation based on real-time network analysis and taking into account the grid's capacity.
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Dates et versions

dumas-00854863 , version 1 (28-08-2013)

Identifiants

  • HAL Id : dumas-00854863 , version 1

Citer

Julian Garbiso. Distributed optimization of electric vehicles recharge in an urban environment. Modeling and Simulation. 2013. ⟨dumas-00854863⟩
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