Title :
A CPF based neural approach for critical contingency evaluation and weak bus identfication
Author :
Kumar, Ravindra ; Kumar, B.U. ; Chauhan, Shubhika
Author_Institution :
Dept. of Electr. Eng., NIT, Hamirpur, India
Abstract :
In this paper, artificial neural network (ANN) based approach is used to quickly estimate the margin to voltage collapse. A new index “Post Contingency Loading Margin” (PCLM) has been proposed to estimate the loadability margin of the system leading to evaluation of critical contingencies and identification of weak buses under any operating condition. The proposed method has been applied and tested on IEEE 30 bus test system and corresponding results have been presented.
Keywords :
load flow; neural nets; power engineering computing; power system dynamic stability; ANN; CPF based neural approach; IEEE 30 bus test system; PCLM; artificial neural network; continuation power flow; critical contingency evaluation; post contingency loading margin index; voltage collapse; voltage stability; weak bus identfication; Algorithm design and analysis; Artificial neural networks; Loading; Power system stability; Stability analysis; Training; Artificial neural network; CPF; Critical contingency; Post Contingency loadability Margin; Voltage stability;
Conference_Titel :
Energy Efficient Technologies for Sustainability (ICEETS), 2013 International Conference on
Conference_Location :
Nagercoil
Print_ISBN :
978-1-4673-6149-1
DOI :
10.1109/ICEETS.2013.6533549
