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Phase Angle Control of Three Level Inverter Based D-STATCOM Using Neuro-Fuzzy ControllerCOTELI, R. , DENIZ, E. , DANDIL, B. , TUNCER, S. , ATA, F.
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electric power quality, D-STATCOM, three-level H-bridge inverter, neuro-fuzzy controller, MATLAB
power(18), statcom(15), control(15), electronics(10), system(6), static(6), fuzzy(6), controller(6), voltage(5), iecon(5)
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About this article
Date of Publication: 2012-02-28
Volume 12, Issue 1, Year 2012, On page(s): 77 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.01013
Web of Science Accession Number: 000301075000013
SCOPUS ID: 84860724702
Distribution Static Compensator (D-STATCOM) is a shunt compensation device used to improve electric power quality in distribution systems. It is well-known that D-STATCOM is a nonlinear, semi-defined and time-varying system. Therefore, control of D-STATCOM by the conventional control techniques is very difficult task. In this paper, the control of D-STATCOM is carried out by the neuro-fuzzy controller (NFC) which has non-linear and robust structure. For this aim, an experimental setup based on three-level H-bridge inverter is constructed. Phase angle control method is used for control of D-STATCOM's output reactive power. Control algorithm for this experimental setup is prepared in MATLAB/Simulink and downloaded to DS1103 controller card. A Mamdani type NFC is designed for control of D-STATCOM's reactive current. Output of NFC is integrated to increase tracking performance of controller in steady state. The performance of D-STATCOM is experimentally evaluated by changing reference reactive current as on-line. The experimental results show that the proposed controller gives very satisfactory performance under different loading conditions.
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 Applications of neuro fuzzy systems: A brief review and future outline, Kar, Samarjit, Das, Sujit, Ghosh, Pijush Kanti, Applied Soft Computing, ISSN 1568-4946, Issue , 2014.
Digital Object Identifier: 10.1016/j.asoc.2013.10.014 [CrossRef]
 INFGMN – Incremental Neuro-Fuzzy Gaussian mixture network, Mazzutti, Tiago, Roisenberg, Mauro, de Freitas Filho, Paulo José, Expert Systems with Applications, ISSN 0957-4174, Issue , 2017.
Digital Object Identifier: 10.1016/j.eswa.2017.07.032 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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