A Neural Network Control Approach to Voltage Stability Enhancement

被引:0
|
作者
Rajalakshmi, P. [1 ]
Rathinakumar, M. [1 ]
机构
[1] SCSVMV Univ, Dept Elect & Elect Engn, Kanchipuram, India
来源
2014 IEEE NATIONAL CONFERENCE ON EMERGING TRENDS IN NEW & RENEWABLE ENERGY SOURCES AND ENERGY MANAGEMENT (NCET NRES EM) | 2014年
关键词
IEEE 30 Bus system; Minimum singular value; Participation factor; Voltage collapse; FACTS; MATLAB; Neural network;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper the static voltage stability index has been identified by minimum singular value of the power flow jacobian matrix. The system security in power system models by the scalar magnitude of a voltage stability index may be a very difficult task. When we are taking account of reactive power generation limits it is very difficult to predict stability index at voltage collapse points. Here a quick method is used to calculate the minimum singular value and the corresponding left and right singular vectors are presented. This developed algorithm is very useful in online because it required small amount of computation time. For different patterns of load and generation are increases, to determine voltage collapse point. For solving the maximum loading problem an optimal power flow approach was used with these points the MSV is calculated and used for training and testing the Neural Network.
引用
收藏
页码:27 / 31
页数:5
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