A Data-Driven Robust Unit Commitment Model of Electricity-Natural Gas System Considering Wind Power Uncertainty

摘要

The integrated power and natural gas system (IEGS) provides a new way to increase wind power consumption. This paper proposes a data-driven robust unit commitment (UC) of IEGS considering wind power uncertainty. Firstly, wind power forecast errors are clustered via infinite Gaussian mixture model (IGMM), and a data-driven uncertainty set is derived afterward. Then a two-stage IEGS unit commitment model is established, in which dynamic natural gas flow is considered. Based on the second-order cone (SOC) method, the nonconvex constraints of the dynamic natural gas flow are transformed into convex ones. In order to solve this min-max-max-min UC optimization problem, a Column Constraint Generation (C&CG) based algorithm is further developed. Finally, the effectiveness of the proposed approach is demonstrated with 6-bus-6-node IEGS and 118-bus-10-node IEGS.