Optimizing PV Array Performance: Comparative Study of Shading Mitigation Techniques and Row-Constrained Swapping
Partial shading presents a recurring problem for PV modules, leading to uneven exposure and reduced power generation. Various setups have been proposed to mitigate shading effects by creating alternative paths for current flow. This comprehensive review examines different photovoltaic (PV) configura...
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Main Authors: | , , , |
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Format: | Proceeding |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/44464/1/Optimizing_PV_Array_Performance_Comparative_Study_of_Shading_Mitigation_Techniques_and_Row-Constrained_Swapping.pdf http://ir.unimas.my/id/eprint/44464/ https://ieeexplore.ieee.org/document/10370531 |
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Institution: | Universiti Malaysia Sarawak |
Language: | English |
Summary: | Partial shading presents a recurring problem for PV modules, leading to uneven exposure and reduced power generation. Various setups have been proposed to mitigate shading effects by creating alternative paths for current flow. This comprehensive review examines different photovoltaic (PV) configurations like total-cross-tied (TCT), Sudoku puzzle pattern, and Futoshiki puzzle pattern, assessing their advantages and limitations. To overcome existing limitations, a new configuration pattern called Row-Constrained Swapping (RCS) is proposed. The performance of the RCS pattern is evaluated in five partial shading scenarios through MATLAB Simulink simulations, and the resulting power output characteristics are analyzed. The findings demonstrate the superiority of the proposed RCS configuration, surpassing other PV setups and establishing it as an optimal choice for large-scale PV applications. By optimizing PV array performance, this study contributes to maximizing power generation and addressing the negative impacts of partial shading. The RCS configuration decreases the number of shaded panels required for relocation by 30%, resulting in a corresponding increase in power generation. |
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