Title :
Multicontingency voltage stability monitoring of power systems using radial basis function network
Author :
Chakrabarti, Saikat ; Jeyasurya, B.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ., St. John, Nfld.
Abstract :
This paper proposes a scheme for online voltage stability monitoring using radial basis function network (RBFN). A single RBFN is used to predict MW margins for different contingencies. A self-organizing learning algorithm and a sequential learning strategy are used to design the hidden layer of the RBFN and the weights in the output layer are determined by using linear optimization technique. The proposed scheme is applied on the New England 39-bus power system model
Keywords :
optimisation; power system control; power system dynamic stability; radial basis function networks; unsupervised learning; voltage control; linear optimization; multicontingency voltage stability monitoring; power system; radial basis function network; self-organizing learning algorithm; sequential learning; Artificial neural networks; Monitoring; Power system measurements; Power system modeling; Power system planning; Power system security; Power system stability; Radial basis function networks; Topology; Voltage;
Conference_Titel :
Intelligent Systems Application to Power Systems, 2005. Proceedings of the 13th International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
1-59975-174-7
DOI :
10.1109/ISAP.2005.1599282
