Flexibility-Oriented Scheduling of Smart Energy Hubs Considering Integrated Demand Response Programs

The transition towards a sustainable energy system requires the integration of renewable energy sources (RESs) and the adoption of innovative energy management frameworks to handle RES variability and uncertainty. The evolution of novel energy management technologies has made it possible to design and operate integrated energy systems (IESs) that couple various energy carriers such as electricity, heat, and gas. The emergence of energy hubs (EHs) presents opportunities for enhanced efficiency, reliability, and flexibility in energy supply and demand. However, optimizing operation schedules in EHs incorporates non-renewables, renewable sources, and energy storage devices becomes increasingly complex as they strive to meet diverse customer demands. This paper introduces a stochastic model for EH operation integrating electrical, thermal, and cooling storage with an electric vehicle parking lot (EVPL). In addition to uncertainty modeling of demands, PV, and EVPL outputs, the model incorporates an integrated demand response program (IDRP) and seasonal load patterns. It's formulated as a linear model solved using the CPLEX solver in GAMS. Results show integrating a shiftable IDRP reduces operational costs by 6% and validates that ESS discharges during peak hours enhance system flexibility.