Skip to main content

2015 | OriginalPaper | Buchkapitel

7. Classification of Voltage Security States Using Unsupervised ANNs

verfasst von : Kabir Chakraborty, Abhijit Chakrabarti

Erschienen in: Soft Computing Techniques in Voltage Security Analysis

Verlag: Springer India

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter focuses on the application of self-organizing neural networks that are capable of extracting valuable data from their working surroundings. The basic role of self-organization lies in the invention of significant patterns without the intervention of a teaching input. An important aspect of the implementation of such a system is that all adaptations must be based on the data that are accessible locally to the neural connection from the pre- and postsynaptic neuron signals and activations. Self-organization must lead eventually to a state of knowledge that provides useful information concerning the environment from which patterns are drawn. As an alternative to the multilayer perceptron, Kohonen’s self-organizing neural network offers some advantages, particularly in clustering-type applications. Faster learning rate and straightforward interpretation of the classification results make self-organizing map (SOM) an ideal choice for the classification of voltage security states in multi-bus power networks. This chapter describes an artificial neural network-based approach, in which Kohonen’s self-organizing feature map technique has been applied to classify the power system operating states based on their degree of static voltage stability.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat De A, Chakraborty K, Chakrabarti A (2012) Classification of power systems voltage stability conditions using Kohonen’s SOFM and LVQ. Eur Trans Electr Power 22(3):412–420 De A, Chakraborty K, Chakrabarti A (2012) Classification of power systems voltage stability conditions using Kohonen’s SOFM and LVQ. Eur Trans Electr Power 22(3):412–420
2.
Zurück zum Zitat Kohonen T (1984) Self-organization and associate memory. Springer, London Kohonen T (1984) Self-organization and associate memory. Springer, London
3.
Zurück zum Zitat De A, Chatterjee N (2001) Impulse fault diagnosis in power transformers using self organizing map and learning vector quantization. IEEE Proc Gener Transm Distrib 148(5):398–406 De A, Chatterjee N (2001) Impulse fault diagnosis in power transformers using self organizing map and learning vector quantization. IEEE Proc Gener Transm Distrib 148(5):398–406
4.
Zurück zum Zitat De A, Chatterjee N (2002) Recognition of impulse fault patterns in transformer using Kohonen’s self organizing feature map. IEEE Trans Power Delivery 17(2):489–494 De A, Chatterjee N (2002) Recognition of impulse fault patterns in transformer using Kohonen’s self organizing feature map. IEEE Trans Power Delivery 17(2):489–494
5.
Zurück zum Zitat Midya BL (2005) 3-D object recognition system using ultrasound. In: 3rd international conference on intelligent sensing and information processing, pp 99–104 Midya BL (2005) 3-D object recognition system using ultrasound. In: 3rd international conference on intelligent sensing and information processing, pp 99–104
6.
Zurück zum Zitat Mori H, Tamaru Y, Tsuzuki S (1992) An artificial neural-net based technique for power system dynamic stability with the Kohonen model. IEEE Trans Power Syst 7(2):856–864CrossRef Mori H, Tamaru Y, Tsuzuki S (1992) An artificial neural-net based technique for power system dynamic stability with the Kohonen model. IEEE Trans Power Syst 7(2):856–864CrossRef
7.
Zurück zum Zitat NeuralWare (1993) Neural computing: a technology handbook for professional IV plus and neuralworks explorer. NeuralWare, Inc., USA NeuralWare (1993) Neural computing: a technology handbook for professional IV plus and neuralworks explorer. NeuralWare, Inc., USA
8.
Zurück zum Zitat Song YH, Wan HB, Johns AT (1997) Kohonen neural network based approach to voltage weak buses/areas identification. IEEE Gener Transm Distrib 144(3):340–344 Song YH, Wan HB, Johns AT (1997) Kohonen neural network based approach to voltage weak buses/areas identification. IEEE Gener Transm Distrib 144(3):340–344
9.
Zurück zum Zitat Chakraborty K, De A, Chakrabarti A (2012) Voltage stability assessment in power network using self organizing feature map and radial basis function. Comput Electr Eng 38(4):819–826 Chakraborty K, De A, Chakrabarti A (2012) Voltage stability assessment in power network using self organizing feature map and radial basis function. Comput Electr Eng 38(4):819–826
10.
Zurück zum Zitat Chakraborty K, De A, Chakrabarti A (2013) Self organizing feature map and radial basis function based voltage stability state classification of power system. Eur J Electr Eng 16(1):7–25 Chakraborty K, De A, Chakrabarti A (2013) Self organizing feature map and radial basis function based voltage stability state classification of power system. Eur J Electr Eng 16(1):7–25
11.
Zurück zum Zitat El-Kateb MM, Abdelkader S, Kandil MS (1997) Linear indicator for voltage collapse in power system. IEEE Proc Gener Transm. Distrib 144(2):139–146 El-Kateb MM, Abdelkader S, Kandil MS (1997) Linear indicator for voltage collapse in power system. IEEE Proc Gener Transm. Distrib 144(2):139–146
Metadaten
Titel
Classification of Voltage Security States Using Unsupervised ANNs
verfasst von
Kabir Chakraborty
Abhijit Chakrabarti
Copyright-Jahr
2015
Verlag
Springer India
DOI
https://doi.org/10.1007/978-81-322-2307-8_7