On-line voltage stability monitoring using artificial neural network

被引：17
|
作者：
Chakrabarti, S [1 ]
Jeyasurya, B [1 ]
机构：
[1] Mem Univ Newfoundland, Fac Engn & Appl Sci, St Johns, NF A1B 3X5, Canada
来源：
2004 LARGE ENGINEERING SYSTEMS CONFERENCE ON POWER ENGINEERING, CONFERENCE PROCEEDINGS: ENERGY FOR THE DAY AFTER TOMORROW | 2004年
关键词：
feature selection; NIW margin; neural networks; voltage stability;
D O I：
10.1109/LESCPE.2004.1356271
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：
This paper proposes a scheme for on-line voltage stability monitoring using artificial neural network (ANN) and a systematic way for training the ANN. Separate ANNs are used for different contingencies and for different load levels under the same contingency. Results of contingency analysis are used along with Principal Component Analysis (PCA) to choose important input features to train the ANN. Implementation of the feature selection scheme enhances the overall usefulness of the neural network. The proposed scheme is applied on the New England 39-bus power system model.
引用
收藏
页码：71 / 75
页数：5
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