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Modeling of hybrid wind‐gas power generation system and adaptive neuro‐fuzzy controller to improve the system performance
Author(s) -
Oğuz Yüksel,
Guney Irfan,
Erdal Hasan
Publication year - 2010
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20271
Subject(s) - adaptive neuro fuzzy inference system , computer science , controller (irrigation) , hybrid system , hybrid power , electricity generation , matlab , electric power system , power (physics) , neuro fuzzy , inference system , control engineering , fuzzy logic , control theory (sociology) , fuzzy control system , engineering , control (management) , artificial intelligence , physics , quantum mechanics , machine learning , agronomy , biology , operating system
In this study, dynamic modeling of the hybrid wind‐gas power generation system (HWGPGS) is realized by using the MATLAB/Simulink program for purpose of meeting the electric energy needs of small settlement units far from city centers or energy distribution networks. Besides, Adaptive Neuro‐Fuzzy Inference System (ANFIS) is used to ensure electrical output magnitudes of the hybrid power generation system at a desired operating performance. The components that build up the hybrid power generation system and its functions in the system are explained. In case the HWGPGS is loaded with different consumer loads, analysis of electrical magnitudes of the system is made through simulation results. As it can be seen from the results of simulation study realized for the hybrid power generation system, output electrical magnitudes of the ANFIS controlled system reach to desired operating values in a short time. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 669–683, 2010; View this article online at wileyonlinelibrary.com ; DOI 10.1002/cae.20271