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FPA Tuned Fuzzy Logic Controlled Synchronous Buck Converter for a Wave/SC Energy SystemSAHIN, E. , ALTAS, I. H.
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fuzzy control, heuristic algorithms, renewable energy sources, supercapacitors, DC-DC power converters
energy(30), power(20), fuzzy(17), systems(16), control(16), wave(15), system(11), logic(10), applications(10), conversion(9)
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About this article
Date of Publication: 2017-02-28
Volume 17, Issue 1, Year 2017, On page(s): 39 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.01006
Web of Science Accession Number: 000396335900006
SCOPUS ID: 85014151061
This paper presents a flower pollination algorithm (FPA) tuned fuzzy logic controlled (FLC) synchronous buck converter (SBC) for an integrated wave/ supercapacitor (SC) hybrid energy system. In order to compensate the irregular wave effects on electrical side of the wave energy converter (WEC), a SC unit charged by solar panels is connected in parallel to the WEC system and a SBC is controlled to provide more reliable and stable voltage to the DC load. In order to test the performance of the designed FLC, a classical proportional-integral-derivative (PID) controller is also employed. Both of the controllers are optimized by FPA which is a pretty new optimization algorithm and a well-known optimization algorithm of which particle swarm optimization (PSO) to minimize the integral of time weighted absolute error (ITAE) performance index. Also, the other error-based objective functions are considered. The entire energy system and controllers are developed in Matlab/Simulink and realized experimentally. Real time applications are done through DS1104 Controller Board. The simulation and experimental results show that FPA tuned fuzzy logic controller provides lower value performance indices than conventional PID controller by reducing output voltage sags and swells of the wave/SC energy system.
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 Five Level Cascaded H-Bridge D-STATCOM using a new Fuzzy and PI Controllers model for Wind Energy Systems, YANMAZ, K., ALTAS, I. H., MENGI, O. O., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.04007 [CrossRef] [Full text]
 Genetically Optimization of an Asymmetrical Fuzzy Logic Based Photovoltaic Maximum Power Point Tracking Controller, AL-GIZI, A., AL-CHLAIHAWI, S., LOUZAZNI, M., CRACIUNESCU, A., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 4, Volume 17, 2017.
Digital Object Identifier: 10.4316/AECE.2017.04009 [CrossRef] [Full text]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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