NDLI: Steady state security assessment of power system using neural networks

Content Provider	IEEE Xplore Digital Library
Author	Emmanuel, P. Kejariwal, M.
Copyright Year	1989
Description	Author affiliation: Dept. of Electr. Eng., Montana State Univ., Bozeman, MT, USA (Emmanuel, P.; Kejariwal, M.)
Abstract	An adaptive pattern recognition approach based on an artificial neural network for calculation of steady state security is outlined. A Rumelhart feedforward net with error back-propagation learning scheme is described and implemented on a CIGRE 225 kV, 10 bus 13 lines system. The steady state security index obtained for a test case shows the capability and adaptability of this network. By backward propagation it is possible to obtain the combination of inputs (features) which give rise to the particular class membership. This information can be of great use in determining the necessary preventive and emergency actions to be taken when the system is in an insecure state. Though the results are very encouraging further efforts are required to make it an efficient and viable tool for steady state security analysis.
Starting Page	742
Ending Page	745
File Size	480261
Page Count	4
File Format	PDF
DOI	10.1109/TENCON.1989.177045
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-11-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power system security Steady-state Neural networks Control systems Voltage control Power system restoration Probability Load forecasting IEEE members Information security
Content Type	Text
Resource Type	Article

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