Distributionally Robust Optimization of an Integrated Energy System Cluster Considering the Oxygen Supply Demand and Multi-Energy Sharing

Abstract

Regional integrated energy systems (IESs) have emerged to satisfy the increasing diversified energy demand in Tibet. However, limited resource allocation of a given IES can occur because of the uncertainty in the output and prediction error of distributed renewable energy (DRE). A distributionally robust optimization (DRO) model was proposed for the joint operation of multiple regional IESs, and multi-energy sharing and multi-energy flow coupling of electricity, heat, and oxygen were considered. The probability distribution of the DRE output was described using 1− norm and ∞− norm constraints, and the minimum operating cost under adverse scenarios was determined through DRO. Furthermore, on the premise of ensuring cluster profit, a pricing mechanism of the energy supply within the cluster was proposed. Finally, a typical model involving eight cases was established and analyzed. The results revealed that multi-energy sharing and multi-energy flow coupling improved the economy of IES cluster operation and realized the coordination of robustness and economy. The energy supply price within the cluster enhanced enthusiasm on the demand side.

Keywords

• electricity
• heat and oxygen
• multi-energy sharing
• double-norm constraints
• distributionally robust optimization
• pricing mechanism within the cluster