Security-Based Active Demand Response Strategy Considering Uncertainties in Power Systems

被引:15
|
作者
Han, Haiteng [1 ]
Gao, Shan [1 ]
Shi, Qingxin [2 ]
Cui, Hantao [2 ]
Li, Fangxing [2 ]
机构
[1] Southeast Univ, Sch Elect Engn, Jiangsu Prov Key Lab Smart Grid Technol & Equipme, Nanjing 210096, Jiangsu, Peoples R China
[2] Univ Tennessee, Dept Elect Engn & Comp Sci, Ctr Ultra Wide Area Resilient Elect Energy Transm, Knoxville, TN 37996 USA
来源
IEEE ACCESS | 2017年 / 5卷
关键词
Active demand response; hyper-box and hyper-ellipse space theory; latin hypercube sampling; power system security; uncertainty; wind power; ARTIFICIAL NEURAL-NETWORKS; CONTINGENCY SELECTION; SIMULATION;
D O I
10.1109/ACCESS.2017.2743076
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:16953 / 16962
页数:10
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