LAPSE:2023.7625
Published Article
LAPSE:2023.7625
A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems
February 24, 2023
Abstract
Maximum power point tracker (MPPT) methods work to maximize the output power of a PV system under changes in meteorological conditions. The performance of these methods depends on the complexity of the algorithm and the number of used variable inputs for obtaining the MPP value. Moreover, they oscillate around the MPP in steady-state operations, causing a waste of power and power loss. Moreover, they do not work perfectly for a PV system running under partial shading conditions. Therefore, this paper proposes modifications to the global maximum power point bald eagle search-based (GMPP BES) method so that it runs as an MPPT as well. The modifications enable the GMPP BES method to detect minor changes in insolation and temperature by observing the changes in the PV array output voltage and, accordingly, trigger the search for the suitable MPP voltage. An experimental setup using a real-time digital simulator (RTDS) was utilized to evaluate the modified GMPP BES-based method under real changes in insolation and ambient temperature. The RTDS simulations confirm the capability of the modified method to accurately and efficiently locate the MPP values. Furthermore, the results demonstrate that the proposed method performs better than the perturb and observe (PO) method concerning its ability to respond to changes in insolation and ambient temperature and its ability to arrive at correct MPP values with nearly zero oscillation around the maximum power point. Thus, with these advantages, the proposed method can be considered a practical solution for solar farms that have to harvest large amounts of energy.
Keywords
bald eagle search technique, global maximum power point tracking, maximum power point tracking, PV systems
Suggested Citation
Abri WA, Abri RA, Yousef H, Al-Hinai A. A Maximum Power Point Tracker Using the Bald Eagle Search Technique for Grid-Connected Photovoltaic Systems. (2023). LAPSE:2023.7625
Author Affiliations
Abri WA: Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman [ORCID]
Abri RA: Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman; Sustainable Energy Research Center (SERC), Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman
Yousef H: Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman [ORCID]
Al-Hinai A: Department of Electrical and Computer Engineering, Sultan Qaboos University, P.O. Box 33, Muscat 123, Oman [ORCID]
Journal Name
Energies
Volume
15
Issue
23
First Page
9185
Year
2022
Publication Date
2022-12-04
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15239185, Publication Type: Journal Article
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LAPSE:2023.7625
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https://doi.org/10.3390/en15239185
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