Risk-aware day-ahead planning of a zero energy hub integrated with green power-to-hydrogen technology using information gap decision theory and stochastic approach and considering demand side elasticity

Abstract

Environmental issues and rapid load growth have led to increasing renewable resources infiltration toward achieving zero energy infrastructures; however, the uncertainty of such components increases the interactions between the local grid and energy markets for sustainable operation. In this study, day-ahead planning of a zero energy hub composed of wind turbine, photovoltaic, electric heat pump, boiler, chiller and storage units is optimized under the uncertainty of wind and solar units and energy market trading. In the designed structure, the required fuel for the local network is supplied through a power-to-hydrogen system to manage carbon emissions. In order to model the uncertainties and analyze the risk of decisions, a hybrid method consisting of the stochastic approach and information gap decision theory is applied. Furthermore, the impact of demand side elasticity for electrical, heating and cooling loads is evaluated. The results show that 10% of load participation significantly improves energy management actions and decreases operation costs by about 15.6%. The simulations also approve that the hybrid method handles the uncertainties under different conditions, where the risk-based cost functions change according to the operator attitude by about 522.44 $ for the ancillary parameter and scenario deviation equal to 10% and 20%, respectively.

Keywords

• Demand side elasticity
• Renewable resources
• Robust optimization
• Stochastic programming
• Zero energy hub