PhD Position F/M PhD Optimal techniques for Smart grid Charging of Autonomous electrical vehicles with Renewable energy sources
Inria
Universidad Estatal, Examinar oportunidades similares
es
Universidad Estatal, Examinar oportunidades similares
This project aims to remove obstacles to the transport electrification and tackles two societal challenges regarding green mobility : CO2 reduction in cities and dusts for the planet as well as development of charging infrastructures The task is to establish the concepts and frameworks allowing autonomous or semi-autonomous electric vehicles (AEV) to interact and communicate in symbiosis with an intelligent electrical network including renewable energy production and storage.
The project consists in defining a tool: i) to design and locate charging infrastructures equipped with renewable energy (RE) production in order to meet users expectations taking into account the uncertainty of the RE production and ii) to inform and guide unoccupied AEV to the available and most “suitable” charging infrastructure (“Autopilot” option by telephone). This last step is performed in order to satisfy local constraints in the distribution network (exceeding the maximum capacity, under voltage, etc. ), maximise the RES use and minimize the charging costs.
This project raises strategical and operational issues. From a strategical point of view, the design in terms of locations, sizes of charging stations as well as RE production capacities has to be determined. From an operational point of view, where and when to charge EV has to be determined in order to minimize the energy cost as well as the production and network distribution electricity peaks, and maximize the use of renewable generation. Considering autonomous vehicles or semi-autonomous vehicles allow us to assume that the EV charging decisions are defined by a central energy management system in charge of managing all the system.
In this project, our goal is to solve two problems. i) A Stochastic design problem to jointly determine the design variables (location, number of charging station and renewable energy production) in two different time scales in an uncertain environment related to the transportation demand, the renewable energy production and electricity peaks ii) A deterministic AEV charging problem leading to the resolution of a deterministic mixed-integer optimization problem in a short period of time for which the production of renewable energy can be finely estimated at the temporal level.
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