A Two-Stage Robust Scheduling Optimization of an Energy Hub with Multiple Chance Constraints

Global environmental degradation and energy crisis have become more serious in recent years. The development and utilization of renewable energy (RE) have become a research hotspot. The multi-energy system, as an efficient and flexible energy supply method, is an effective way to improve the utilization of RE energy and achieve emission reduction. Due to the increased coupling between various energy sources, the dispatch of multi-energy systems becomes very complex. Energy hubs (EH) are introduced to describe the coupling relationship between different energy sources in the multi-energy system. The existing researches on EH mainly focus on the modeling and the capacity optimization of internal components, lacking the study of energy scheduling problems that consider the uncertainty of RE generation. Thus, a two-stage stochastic program for energy dispatch is developed in this paper for EH systems with RE penetration. Combining Bonferroni's inequality with the conditional value-at-risk (CVaR) allows an easily tractable conservative approximation. In the simulation part, the optimization results of the energy dispatch at the input side and individual components are obtained. The results can provide important basic information for future operation optimization of EH systems under a high percentage of renewable energy penetration.