Skip to Main content Skip to Navigation
New interface
Conference papers

Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production

Abstract : Simultaneous development of photovoltaic generation and electric vehicles strengthens the solicitations on the electric power system. This paper investigates the possible synergy between these players to jointly improve the production predictability while ensuring a low carbon mobility. It stands for a step towards a quantification of its economic and environmental fallout. First a context is described for a PV-EV collaboration. Then this is gathered into an optimization problem. Grid commitment constraints, battery aging and mobility needs are here considered from the environmental point of view of equivalent primary energy. Finally, a resolution method is presented which achieve an time-efficient optimization of the power flow for each vehicle, based on upstream computed charging policies. It relies on a stochastic modeling of both vehicles availability and forecast error of the PV production. The resolution framework is the stochastic dynamic programming, coupled with on-line minimization so as to avoid the curse of dimensionality. The proposed resolution enables to compute optimal power flow for each vehicle, even among large fleets. The emphasis is here set on a versatile resolution method which could take over many detailed objective functions.
Complete list of metadata

Cited literature [23 references]  Display  Hide  Download
Contributor : Roman Le Goff Latimier Connect in order to contact the contributor
Submitted on : Monday, May 9, 2016 - 11:36:57 AM
Last modification on : Friday, October 7, 2022 - 3:58:11 AM
Long-term archiving on: : Wednesday, May 25, 2016 - 8:02:54 AM


Files produced by the author(s)



Roman Le Goff Latimier, B Multon, Hamid Ben Ahmed, Franck Baraer, Mickael Acquitter. Stochastic optimization of an Electric Vehicle Fleet Charging with Uncertain Photovoltaic Production. 4th International Conference on Renewable Energy Research and Applications (ICRERA 2015), Nov 2015, Palerme, Italy. pp.721-726, ⟨10.1109/ICRERA.2015.7418505⟩. ⟨hal-01312894⟩



Record views


Files downloads