Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique

Po-Chen Cheng, Bo-Rei Peng, Yi-Hua Liu, Yu-Shan Cheng and Jia-Wei Huang
Additional contact information
Po-Chen Cheng: Department of Electrical Engineering, National Taiwan University of Science and Technology, EE-105-1 #No.43, Sec. 4, Keelung Rd., Da'an Dist., Taipei 10600, Taiwan
Bo-Rei Peng: Department of Electrical Engineering, National Taiwan University of Science and Technology, EE-105-1 #No.43, Sec. 4, Keelung Rd., Da'an Dist., Taipei 10600, Taiwan
Yi-Hua Liu: Department of Electrical Engineering, National Taiwan University of Science and Technology, EE-105-1 #No.43, Sec. 4, Keelung Rd., Da'an Dist., Taipei 10600, Taiwan
Yu-Shan Cheng: Department of Electrical Engineering, National Taiwan University of Science and Technology, EE-105-1 #No.43, Sec. 4, Keelung Rd., Da'an Dist., Taipei 10600, Taiwan
Jia-Wei Huang: Electric Energy Technology Division Power Electronics Department, Industrial Technology Research Institute, Rm#839, Bldg. 51, No. 195, Sec. 4, Chung Hsing Rd., Chutung, Hsinchu 31040, Taiwan

Energies, 2015, vol. 8, issue 6, 1-23

Abstract: In this paper, an asymmetrical fuzzy-logic-control (FLC)-based maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems is presented. Two membership function (MF) design methodologies that can improve the effectiveness of the proposed asymmetrical FLC-based MPPT methods are then proposed. The first method can quickly determine the input MF setting values via the power–voltage (P–V) curve of solar cells under standard test conditions (STC). The second method uses the particle swarm optimization (PSO) technique to optimize the input MF setting values. Because the PSO approach must target and optimize a cost function, a cost function design methodology that meets the performance requirements of practical photovoltaic generation systems (PGSs) is also proposed. According to the simulated and experimental results, the proposed asymmetrical FLC-based MPPT method has the highest fitness value, therefore, it can successfully address the tracking speed/tracking accuracy dilemma compared with the traditional perturb and observe (P&O) and symmetrical FLC-based MPPT algorithms. Compared to the conventional FLC-based MPPT method, the obtained optimal asymmetrical FLC-based MPPT can improve the transient time and the MPPT tracking accuracy by 25.8% and 0.98% under STC, respectively.

Keywords: fuzzy logic control; maximum power point tracking; particle swarm optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Downloads: (external link)
https://www.mdpi.com/1996-1073/8/6/5338/pdf (application/pdf)
https://www.mdpi.com/1996-1073/8/6/5338/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:8:y:2015:i:6:p:5338-5360:d:50686

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().