Distributionally Robust Optimization Based Restoration for Integrated Electricity-Gas Systems Incorporating Wind Power and Flexible Reserve Capacity Allocations

The integrated electricity-gas system (IEGS) is the foundation of the Energy Internet. As inevitable risk factors, the widespread blackout and large-scale energy supply disruptions represent serious threats to the IEGS. Improving the load restoration ability of IEGS is an important measure to mitigate the harm caused by blackouts. However, the increasing penetration of wind power has posed some difficulties to IEGS load restoration. In view of this, based on distributionally robust optimization (DRO), a two-stage IEGS restoration model is developed in this paper. Through a detailed mathematical model of an electric power system (EPS) with multiple generating resources and a natural gas system (NGS) with dynamic characteristics, the supporting role of the NGS operation flexibility for IEGS restoration is fully explored and quantitatively analyzed. Through the construction of a Wasserstein metric-based ambiguity set of wind power forecast deviation, the proposed two-stage IEGS restoration model can incorporate operational risks when the uncertainty of wind power output is encountered and also take into account the flexible reserve capacity (FRC) allocation and deployment constraints. The proposed model can realize the reasonable scheduling of wind power, automatically determine the allocation of the required FRC, and optimize the load restoration schemes. Moreover, the proposed model can be converted into a mixed integer linear programming problem which can be directly solved. In the case study, the advantages of the proposed model are compared with three conventional restoration models based on two test systems, and sensitivity analysis is conducted.