An integrated optimal control framework for smart cities: Distributed renewable generation, storage, EV charging, and inter-node energy transfers with trading flexibility

This study develops an integrated optimal control framework for smart-city energy systems that jointly coordinates renewable generation, energy storage, and mobility-driven demand under realistic variability, addressing key limitations in existing approaches related to the separation between planning and operation, the passive treatment of electric mobility, and the lack of control-compatible peer-to-peer coordination. The proposed model is based on a hybrid energy system integrating photovoltaic and wind generation, district-scale battery energy storage, and aggregated electric mobility with vehicle-to-grid capability. Inter-district coordination is enabled through peer-to-peer energy exchanges, while grid interaction is structured using a binary flexibility variable that distinguishes scheduled operation from incentivized deviations. A transportation sub-model captures mobility-driven vehicle flows and their impact on charging demand, linking traffic dynamics with energy dispatch decisions. The resulting model predictive control framework is applied to the city of Marrakech, achieving a renewable energy fraction of 92.5%, near-zero grid imports, and net renewable exports of 194.5 GWh/yr. Over a 7-day horizon, the system supplies 202.4 MWh of electric vehicle charging and 34.5 MWh for electric buses, while enabling 25.0 MWh of inter-district energy exchanges. These results demonstrate that the proposed framework effectively supports high renewable integration and large-scale urban electrification under realistic operating conditions.