1/2012 - 13 |
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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Author keywords
electric power quality, D-STATCOM, three-level H-bridge inverter, neuro-fuzzy controller, MATLAB
References keywords
power(18), statcom(15), control(15), electronics(10), system(6), static(6), fuzzy(6), controller(6), voltage(5), iecon(5)
Blue keywords are present in both the references section and the paper title.
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
Abstract
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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[1] 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]
[2] 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]
[3] Performance analysis of SRFT based D-STATCOM for power quality improvement in distribution system under different loading conditions, Sirohi, Vijay, Saggu, Tejinder Singh, Singh, Mandeep, International Journal of Emerging Electric Power Systems, ISSN 2194-5756, 2023.
Digital Object Identifier: 10.1515/ijeeps-2023-0107 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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