DocumentCode
3363077
Title
Voltage Stability Assessment Based on BP Neural Network
Author
Han, Xiaoqing ; Zheng, Zhijing ; Tian, Nannan ; Hou, Yuanyuan
Author_Institution
Coll. of Electr. & Power Eng., Taiyuan Univ. of Technol., Taiyuan
fYear
2009
fDate
27-31 March 2009
Firstpage
1
Lastpage
4
Abstract
An assessment approach on power system voltage stability is provided using Back Propagation (BP) Neural Network, which takes the Voltage Collapse Proximity Indicator (VCPI) as assessment index. The key feature of the method is to establish static and dynamic assessment models on voltage stability. The training results of the static models based on load flow calculation can reflect the nonlinear mapping relationship correctly between power flows and voltages on load bus with given load increasing mode; Based on integrated load model, the dynamic model uses two three-layer BP networks to make classification and prediction on system, respectively. With two instances of WSCC-9 and 3 generator-12 bus power system, it is verified that the method is effective to voltage stability assessment on power system.
Keywords
backpropagation; neural nets; power system stability; assessment index; back propagation neural network; load flow calculation; nonlinear mapping; power system voltage stability; voltage collapse proximity indicator; Load flow; Load modeling; Neural networks; Nonlinear dynamical systems; Power generation; Power system dynamics; Power system modeling; Power system stability; Predictive models; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location
Wuhan
Print_ISBN
978-1-4244-2486-3
Electronic_ISBN
978-1-4244-2487-0
Type
conf
DOI
10.1109/APPEEC.2009.4918962
Filename
4918962
Link To Document