Jiangsu Provincial Key Laboratory of Smart Grid Technology & Equipment, School of Electrical Engineering, Southeast University, Nanjing, China
Shan Gao
Jiangsu Provincial Key Laboratory of Smart Grid Technology & Equipment, School of Electrical Engineering, Southeast University, Nanjing, China
Qingxin Shi
Department of Electrical Engineering and Computer Science, Center for Ultra-wide-area Resilient Electric Energy Transmission Networks, The University of Tennessee, Knoxville, TN, USA
Hantao Cui
Department of Electrical Engineering and Computer Science, Center for Ultra-wide-area Resilient Electric Energy Transmission Networks, The University of Tennessee, Knoxville, TN, USA
Fangxing Li
Department of Electrical Engineering and Computer Science, Center for Ultra-wide-area Resilient Electric Energy Transmission Networks, The University of Tennessee, Knoxville, TN, USA
In modern power systems, the stochastic and interactive characteristics of mixed generations have gained increasing interest, especially when more renewable energy sources are connected to the grid. The uncertainty of renewable energy has notable effects on power system security. In this paper, a set of composite security indices, which are derived from the Hyper-box and Hyper-ellipse Space theory, are extended by a Latin hypercube sampling method to model multiple probabilistic scenarios under uncertainty. Thus, the proposed approach is suitable for power system security assessment with wind power integrated. According to the indices, a security-based active demand response (DR) strategy is proposed. This strategy is able to provide expected active DR capacity based on the forecast wind power fluctuations. Therefore, it can be applied to day-ahead power system dispatches.
