Robust optimal operation of energy hub incorporating integrated thermal and electrical demand response programs under various electric vehicle charging modes

Although the energy hub (EH) concept results in different benefits, the system uncertainties might affect the optimized decisions. Several studies have studied EH's optimal operation, considering the system uncertainties. However, there is a research gap in proposing a novel EH's robust optimal operation under various charging modes of electric vehicles (EVs), besides integrated electrical and thermal demand response programs (DRPs). The main purpose of this research is to fill such a knowledge gap. In this paper, the uncertainties of renewable energy distributed resources and electricity price have been concerned using the robust optimization method. The integrated charging load of EVs under coordinated and uncoordinated charging modes has been distinguished using the Monte Carlo simulation (MCS). Another contribution is to study different schemes of hybrid electrical, heat, and cooling energy storage systems in the introduced robust framework. Simulation results infer that a 15.87% decrement in EH's operation cost is achievable by applying the integrated thermal and electrical DRPs, using the electric heat pump (EHP) and hybrid storage system consisting of the ice storage system. The comparative test results show that the advantages of integrated thermal and electricity DRPs and charging management of EVs are highlighted by using EHPs. The sensitivity analyses of the EH's operation cost against the robustness efficiency parameters corresponding to the uncertainty level show that the advantages of the proposed method are highlighted while the EH's uncertainties increase.

Automated summary

While the energy hub concept has various benefits, uncertainties within the system can impact decision making. Studies have focused on optimizing the operation of energy hubs while considering uncertainties, but there is a gap in research regarding robust optimal operation under different EV charging modes and integrated demand response programs. This research aims to address this gap by using robust optimization methods to account for uncertainties in renewable energy resources and electricity prices, as well as studying hybrid storage systems in the robust framework. Simulation results demonstrate cost savings by implementing integrated thermal and electrical demand response programs and utilizing electric heat pumps and hybrid storage systems. Sensitivity analyses show the advantages of the proposed method when uncertainties within the energy hub increase.