A Novel PV Array Reconfiguration-Technique to Maximize Power Generation under Shading Conditions

Partial shading conditions (PSCs) pose a great challenge to photovoltaic (PV) arrays and result in high power losses as well as reducing the lifetime of PV modules. Traditional PV arrangements are incapable of reducing such losses. A new Jigsaw Sudoku Puzzle-based reconfiguration method for improving PV arrays' power output under shading is presented in this research. The technique is designed to redistribute the effects of shading uniformly throughout the array, reducing mismatch losses and enhancing overall efficiency. A 6×6 PV array is simulated and modeled in MATLAB/Simulink, comparing the performance of the proposed method with conventional configurations, such as String-Parallel (SP), Fully-Cross-Tied (FCT), and Novel Shade Distribution (NSD). Performance metrics like global peak power points, conversion efficiency, form factor, power dissipation losses, open-circuit voltage, short-circuit current, Output Power Improvement, and number of peaks are evaluated. The findings prove that Jigsaw Sudoku Puzzle-based reconfiguration improves power output considerably, increases efficiency, and minimizes power dissipation losses when compared to traditional configurations and is thus a practical solution for reducing the negative impacts of partial shading in PV systems.

Authors

Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1109/ictmim65579.2025.10988016
Citations
1
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel PV Array Reconfiguration-Technique to Maximize Power Generation under Shading Conditions

Aluri Manoj, Kumar Laxman, G. Meerimatha, S. Saniya et al.
1 citations
Photovoltaic System Optimization Techniques
0.36
article

A Novel PV Array Reconfiguration-Technique to Maximize Power Generation under Shading Conditions

Aluri Manoj, Kumar Laxman, G. Meerimatha, S. Saniya, B. Nageswari, D. Towseef
article en
1 citations

Abstract

Partial shading conditions (PSCs) pose a great challenge to photovoltaic (PV) arrays and result in high power losses as well as reducing the lifetime of PV modules. Traditional PV arrangements are incapable of reducing such losses. A new Jigsaw Sudoku Puzzle-based reconfiguration method for improving PV arrays' power output under shading is presented in this research. The technique is designed to redistribute the effects of shading uniformly throughout the array, reducing mismatch losses and enhancing overall efficiency. A 6×6 PV array is simulated and modeled in MATLAB/Simulink, comparing the performance of the proposed method with conventional configurations, such as String-Parallel (SP), Fully-Cross-Tied (FCT), and Novel Shade Distribution (NSD). Performance metrics like global peak power points, conversion efficiency, form factor, power dissipation losses, open-circuit voltage, short-circuit current, Output Power Improvement, and number of peaks are evaluated. The findings prove that Jigsaw Sudoku Puzzle-based reconfiguration improves power output considerably, increases efficiency, and minimizes power dissipation losses when compared to traditional configurations and is thus a practical solution for reducing the negative impacts of partial shading in PV systems.

Affordable and clean energy
Openalex Percentile: Top 44%
Photovoltaic System Optimization Techniques
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Novel PV Array Reconfiguration-Technique to Maximize Power Generation under Shading Conditions — Aluri Manoj, Kumar Laxman, et al. · (2025) | TGRS Research Map | TGRS