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A Fast MPPT Method Based on Improved Water Cycle Optimization Algorithm for Photovoltaic Systems Under Partial Shading Conditions and Load Variations

Authors :
Rafah Ibraheem Jabbar
Saad Mekhilef
Marizan Mubin
Obaid Alshammari
Ahmed Kazaili
Source :
IEEE Open Journal of the Industrial Electronics Society, Vol 5, Pp 1324-1338 (2024)
Publication Year :
2024
Publisher :
IEEE, 2024.

Abstract

Photovoltaic array characteristics with partial shading (PS) have multiple maximum power points (MPPs), and conventional algorithms have difficulties in tracking accurate global maximum power points (GMPPs). This study proposes a MPP tracking (MPPT) method based on improved water cycle optimization for fast-tracking the GMPP under PS conditions, along with a new strategy to enhance the convergence speed of the MPPT method during load variations. The experimental setup included a dc–dc single-ended primary inductance converter (SEPIC) and digital signal processing and control engineering (DSPACE) controller to assess the performance of the proposed method. The proposed method was also compared with the conventional water cycle optimization and six MPPT algorithms. The experimental results showed that the proposed method obtained an average tracking efficiency of 99.92% and a tracking time of 0.475 s for all PS tests. Moreover, it achieved a GMPP in a single perturbation step when the load change occurred, reducing the power loss in the photovoltaic (PV) system. The comparison showed that the proposed method performed better than the other MPPT methods in terms of tracking efficiency, convergence speed, and ease of implementation. This method could be utilized to implement developed PV systems with minimal losses.

Details

Language :
English
ISSN :
26441284
Volume :
5
Database :
Directory of Open Access Journals
Journal :
IEEE Open Journal of the Industrial Electronics Society
Publication Type :
Academic Journal
Accession number :
edsdoj.19b9368b169943ed95ad8c605da61e39
Document Type :
article
Full Text :
https://doi.org/10.1109/OJIES.2024.3510367