Robust scheduling of thermal, cooling and electrical hub energy system under market price uncertainty

Multi-carrier hub energy system (MCHES) satisfies different energy demands such as heating, cooling, and energy demand by using different energy sources simultaneously. In this paper, a robust optimization approach (ROA) is provided for robust scheduling of MCHES considering economic and environmental constraints in the presence of market price uncertainty and multi-demand response programs (DRPs). In ROA, lower and upper levels of market price are considered instead of forecasted market price which guarantees the robust scheduling of the MCHES. The time-of-use (TOU) and real-time-pricing (RTP) rates of DRPs play a vital role in flattening the load curve with the aim of reducing the total operation cost and CO2 emission. The proposed model is formulated as robust mixed integer linear programming (RMILP) and solved by General Algebraic Modeling System (GAMS) platform which has a great advantage in solving the linear programming models. Finally, to assess the effects of assumed DRPs on robust scheduling of MCHES, three case studies are utilized, and significant results were obtained.