Bi-level model for congestion management with large-scale wind power integration considering realtime operational risks

The large-scale integration of wind power is expected to lead to increase of transmission congestion probability due to the uncertain nature of wind power. This paper presents a novel bi-level congestion management model considering real-time operational risk under uncertainty. The upper level model represents the congestion re-dispatching problem, and the lower level model represents real-time operation problem whose objective is to minimize the operational risks. Wind power production uncertainty is modeled through a suitable set of scenarios, and the risks considered in this paper contain the loss of load and wind curtailment. The bi-level model is transformed into a mixed integer linear programming(MILP) problem using Karush-Kuhn-Tucker(KKT) optimality conditions and Fortuny-Amat and McCarl linearization approach. Numerical results indicate the efficiency of the proposed approach.