Terrier, CédricMiddelhauve, LuiseMaréchal, François2023-06-152023-06-152023-06-152022-07-07https://infoscience.epfl.ch/handle/20.500.14299/198276The electrification of private mobility is becoming a popular solution to reduce the reliance on fossil fuels. However, uncontrollable charging of a large electric vehicle fleet challenges the distribution grid due to transmission bottlenecks, voltage limit violation or excessive wearing. In contrast, the additional storage capacities represent a potential flexibility service for grid operators. Therefore, the optimal integration of electric vehicles in urban multi-energy systems is key to minimize the power grid reliance and to maximize the self-consumption of renewable energy resources. The aim of this paper is to integrate electric mobility in the concept of a renewable energy hub formulated at the district scale. The model is a mixed-integer linear programming problem, and the Dantzig-Wolfe decomposition is applied to reduce the computational time. The electric vehicles are considered as controllable reserves offering services to grid operators. An electric mobility integration of 20% is considered. The results demonstrated the economic feasibility of electric mobility integration where services to the grid allowed for a 70% reduction in charging costs and a 50% reduction in global warming potential. The grid services allowed for an increase in self-consumption (70% with respect to 55%) and the charging of the vehicle was managed by up to 82% of renewable electricity. The optimal battery management of the vehicles demonstrated peak load reductions and promoted a grid-aware design of the renewable energy hub.DecompositionElectric mobilityGrid integrationMulti-objective optimizationRenewable energy hubtext::conference output::conference proceedings::conference paper