Bi-level model for congestion management with large-scale wind power integration considering realtime operational risks
- Resource Type
- Conference
- Authors
- Fan, Zhen; Wang, Xiran; Lou, Suhua; Li, Hui; Wang, Zhidong; Lv, Mengxuan; Wu, Zhiming
- Source
- 2017 International Conference on Electrical Engineering and Informatics (ICELTICs) Electrical Engineering and Informatics (ICELTICs), 2017 International Conference on. :141-146 Oct, 2017
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Wind power generation
Real-time systems
Load modeling
Production
Liquid crystal displays
Uncertainty
Spinning
Congestion management
bi-level programming
real-time operatioal risk
wind power integration
MILP
- Language
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.