PMU-ANN based Approach for Real Time Voltage Stability Monitoring

被引：0
|
作者：
Shah, Harita [1 ]
Verma, Kusum [1 ]
机构：
[1] Malaviya Natl Inst Technol, Dept Elect Engn, Jaipur, Rajasthan, India
来源：
2016 IEEE 6TH INTERNATIONAL CONFERENCE ON POWER SYSTEMS (ICPS) | 2016年
关键词：
artificial neural network; phasor measurement unit; voltage stability; voltage stability indices; SECURITY ASSESSMENT;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Voltage Stability is one of the major problems to be taken into consideration for secure and reliable operation of modern power systems. This paper presents a Phasor Measurement Unit and Artificial Neural Network (PMU-ANN) based approach for voltage stability monitoring in real time. The proposed approach uses the Feed Forward Neural Network (FFNN). The input to FFNN is voltage magnitude and voltage angle measured from PMU. The optimal placement of PMU is obtained by Integer Linear Programming (ILP). Various voltage stability indices are used as indicator for voltage stability monitoring. The effectiveness of the proposed approach is demonstrated on New England 39 bus test system.
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页数：5
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