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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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