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Master Thesis

Distributed optimization of electric vehicles recharge in an urban environment

Abstract : 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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https://dumas.ccsd.cnrs.fr/dumas-00854863
Contributor : Co-Responsables Du Mri V. Gouranton Et S. Blazy <>
Submitted on : Wednesday, August 28, 2013 - 11:47:03 AM
Last modification on : Friday, July 31, 2020 - 10:44:09 AM
Long-term archiving on: : Monday, December 2, 2013 - 8:49:52 AM

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  • HAL Id : dumas-00854863, version 1

Citation

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

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