NDLI: A methodology for training artificial neural networks for islanding detection of distributed generators

Content Provider	IEEE Xplore Digital Library
Author	Merlin, V.L. Santos, R.C. Pavani, A.P.G. Coury, D.V. Oleskovicz, M. Vieira, J.C.M.
Copyright Year	2013
Description	Author affiliation: Escola de Eng. de Sao Carlos, São Carlos, Brazil (Coury, D.V.; Oleskovicz, M.; Vieira, J.C.M.) \|\| Univ. Fed. do ABC, Santo Andre, Brazil (Merlin, V.L.; Santos, R.C.; Pavani, A.P.G.)
Abstract	The anti-islanding protection of synchronous generators is typically performed by voltage and frequency relays. However, one of the main issues related to setting these relays is to identify and differentiate the magnitude and frequency variations of an islanding event from other disturbances that may occur along the system, such as severe load switching. By using an Artificial Neural Network (ANN) based algorithm, it is possible to recognize existent patterns on the distributed generator voltage waveform, which makes possible to obtain an accurate response about islanding events. However, the ANN training process is not so easy, because it involves important issues such as the definition of the ANN architecture, the size of data window, sampling rate and selection of a representative training set for the studied problem. In this context, this paper discusses the fundamental aspects for training an ANN used for islanding detection of synchronous distributed generators.
Sponsorship	IEEE Power Energy Soc.
Starting Page	1
Ending Page	6
File Size	431046
Page Count	6
File Format	PDF
ISBN	9781467352727
e-ISBN	9781467352741
DOI	10.1109/ISGT-LA.2013.6554400
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-15
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training RNA Bills of materials Anti-islanding protection Artificial neural networks Generators Distributed generation Artificial neural network MATLAB Relays
Content Type	Text
Resource Type	Article

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