Chance-constrained maintenance scheduling for interdependent power and natural gas grids considering wind power uncertainty

Abstract

Considering the increased interactions between power grids and natural gas grids, this study presents a chance-constrained maintenance scheduling model for integrated gas-electric grids with wind energy integration. Given the uncertainties of wind power, the loss of wind power probability is modelled as a chance constraint, ensuring the high utilisation of wind power. To overcome the adversities caused by the non-linear and non-convex models of natural gas systems, a piecewise linear approximation method is employed to transform the non-linear models into a group of mixed integer linear models. A big-M formulation method is used to construct inequality constraints for lines/pipelines to be under maintenance. In addition, unit commitment is also coordinated to achieve the best maintenance strategies. The proposed chance-constrained stochastic programming model is converted into an equivalent deterministic programming model via a strong extended formulation for the sample average approximation by leveraging the star-inequalities. Several tests on a four-node natural gas system with a six-bus power system and a 20-node natural gas system with a modified IEEE 118-bus power system demonstrate the effectiveness of the proposed model.