Neural Network based stochastic load flow analysis

Amit Jain, S. C. Tripathy, R. Balasubramanian, Kamal Garg, Yoshiyuki Kawazoe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Neural Network based method for the analysis of stochastic load flow is presented in this paper. Stochastic load flow is a method for calculation of the effects of inaccuracies in input data on all output quantities through the load flow calculations. This gives a range of values for each output quantity, which represent the operative condition of the system, to a high degree of probability. It is desirable to know the state of the power system, with consideration of input data accuracies, on instant-to-instant basis and present method of neural network application to stochastic load flow problem is an effort in that direction. The proposed neural network model has been tested on a sample power system and simulation results are presented.

Original languageEnglish
Title of host publication2004 International Conference on Power System Technology, POWERCON 2004
Pages1845-1850
Number of pages6
Publication statusPublished - 2004 Dec 1
Event2004 International Conference on Power System Technology, POWERCON 2004 - , Singapore
Duration: 2004 Nov 212004 Nov 24

Publication series

Name2004 International Conference on Power System Technology, POWERCON 2004
Volume2

Other

Other2004 International Conference on Power System Technology, POWERCON 2004
Country/TerritorySingapore
Period04/11/2104/11/24

Keywords

  • Back propagation
  • Confidence limit
  • Neural network
  • Power System
  • Stochastic load flow

ASJC Scopus subject areas

  • Engineering(all)

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