LAPSE:2023.23836
Published Article

LAPSE:2023.23836
A Novel Module Independent Straight Line-Based Fast Maximum Power Point Tracking Algorithm for Photovoltaic Systems
March 27, 2023
Abstract
The maximum power point tracking (MPPT) algorithm has become an integral part of many charge controllers that are used in photovoltaic (PV) systems. Most of the existing algorithms have a compromise among simplicity, tracking speed, ability to track accurately, and cost. In this work, a novel “straight-line approximation based Maximum Power Point (MPP) finding algorithm” is proposed where the intersections of two linear lines have been utilized to find the MPP, and investigated for its effectiveness in tracking maximum power points in case of rapidly changing weather conditions along with tracking speed using standard irradiance and temperature curves for validation. In comparison with a conventional Perturb and Observe (P&O) method, the Proposed method takes fewer iterations and also, it can precisely track the MPP s even in a rapidly varying weather condition with minimal deviation. The Proposed algorithm is also compared with P&O algorithm in terms of accuracy in duty cycle and efficiency. The results show that the errors in duty cycle and power extraction are much smaller than the conventional P&O algorithm.
The maximum power point tracking (MPPT) algorithm has become an integral part of many charge controllers that are used in photovoltaic (PV) systems. Most of the existing algorithms have a compromise among simplicity, tracking speed, ability to track accurately, and cost. In this work, a novel “straight-line approximation based Maximum Power Point (MPP) finding algorithm” is proposed where the intersections of two linear lines have been utilized to find the MPP, and investigated for its effectiveness in tracking maximum power points in case of rapidly changing weather conditions along with tracking speed using standard irradiance and temperature curves for validation. In comparison with a conventional Perturb and Observe (P&O) method, the Proposed method takes fewer iterations and also, it can precisely track the MPP s even in a rapidly varying weather condition with minimal deviation. The Proposed algorithm is also compared with P&O algorithm in terms of accuracy in duty cycle and efficiency. The results show that the errors in duty cycle and power extraction are much smaller than the conventional P&O algorithm.
Record ID
Keywords
duty cycle, global horizontal irradiance, linear approximation, mathematical modeling, MPPT algorithm
Subject
Suggested Citation
Debnath A, Olowu TO, Parvez I, Dastgir MG, Sarwat A. A Novel Module Independent Straight Line-Based Fast Maximum Power Point Tracking Algorithm for Photovoltaic Systems. (2023). LAPSE:2023.23836
Author Affiliations
Debnath A: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Olowu TO: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Parvez I: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA [ORCID]
Dastgir MG: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Sarwat A: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Olowu TO: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Parvez I: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA [ORCID]
Dastgir MG: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Sarwat A: Electrical and Computer Engineering, Florida International University, 10555 W Flagler St, Miami, FL 33174, USA
Journal Name
Energies
Volume
13
Issue
12
Article Number
E3233
Year
2020
Publication Date
2020-06-22
ISSN
1996-1073
Version Comments
Original Submission
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PII: en13123233, Publication Type: Journal Article
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LAPSE:2023.23836
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https://doi.org/10.3390/en13123233
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Mar 27, 2023
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