Title :
Adequacy assessment of composite system based on static voltage stability limit using ANN
Author :
Titare, L.S. ; Arya, L.D. ; Shrivastava, M.
Author_Institution :
Electr. Eng. Dept., Gov. Eng. Coll., Ujjain, India
Abstract :
A new methodology has been developed for determining probability of failure accounting static voltage stability limits under various network and generation capacity states. These failure probabilities have been obtained for various total systems loading condition. Corrective capabilities under various system states have been accounted via an optimization formulation. Results so obtained have been used to train a multilayer feed forward network. Hence probability of failure can be calculated on-line. The algorithm has been implemented on 6-bus, 7-line test system.
Keywords :
feedforward neural nets; large-scale systems; learning (artificial intelligence); load flow; multilayer perceptrons; optimisation; power system analysis computing; power system reliability; power system stability; probability; voltage regulators; 6-bus-7-line test system; ANN; adequacy assessment; artificial neural network; composite system; continuation power flow; failure probability; multilayer feed forward network; optimization; power system reliability; static voltage stability limit; system loading condition; Interconnected systems; Load flow; Power system analysis computing; Power system dynamics; Power system modeling; Power system planning; Power system reliability; Power system security; Power system stability; Voltage;
Conference_Titel :
India Annual Conference, 2004. Proceedings of the IEEE INDICON 2004. First
Print_ISBN :
0-7803-8909-3
DOI :
10.1109/INDICO.2004.1497789
