Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/7175
Title: Determination of optimal hierarchical fuzzy controller parameters according to loading condition with ANN
Authors: Caner, M.
Umurkan, N.
Tokat, Sezai
Üstün, S.V.
Keywords: Excitation control
Hierarchical fuzzy control
Power system stabilizer
Backpropagation algorithms
Computer simulation
Fuzzy control
Neural networks
Parameter estimation
Power system stabilizers
Quantitative criterias
Electric loads
Abstract: This paper represents an artificial neural network (ANN) backpropagation algorithm is used to choose best coefficients of hierarchical fuzzy power system stabilizer (HFPSS). PSS is used for stability enhancement of a single machine infinite bus (SMIB) power system. ANN algorithm is used to predict load condition of the power system. And according to the predicted load condition ANN determinates choosing optimal parameters of the hierarchical fuzzy controller (HFC) to achieve better performance. Simulation results are compared with conventional PSS (CPSS) to show the effectiveness of the proposed controller. Also quantitative criterias of measuring performance is computed for 16 loading conditions. © 2007 Elsevier Ltd. All rights reserved.
URI: https://hdl.handle.net/11499/7175
https://doi.org/10.1016/j.eswa.2007.05.038
ISSN: 0957-4174
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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