Optimal Shade Dispersion Strategy for Enhanced PV Power Extraction Under PSCs
Ranjeet Singh, Vinod Kumar Yadav, Madhusudan Singh
Abstract
This article proposes a static optimal shade dispersion (SD) strategy to alleviate the mismatch loss (ML) by uniformly dispersing the shade over the entire photovoltaic (PV) array. The proposed generalized module repositioning approach (GMRA) is valid for any <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i \times j$</tex-math></inline-formula> array dimensions, for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i = j$</tex-math></inline-formula> or <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i \neq j$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$i$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$j$</tex-math></inline-formula> being the number of rows and columns, respectively, and can assume even, odd, or both values. To extract optimal power from a series-parallel (SP) PV configuration under mismatch conditions, a variant of the proposed GMRA (SP-GMRA) is also presented. The module locations of the total-cross-tied (TCT) and SP-configured PV array are changed using GMRA and SP-GMRA respectively without altering the terminal electrical connections. Simulations are performed on a 9×9 PV array under four common shade occurrences, followed by experimental validation on symmetrical 5×5 and unsymmetrical 6×4 configurations to demonstrate the applicability and generalization of the proposed approach to varied array sizes. The proposed scheme is compared to a wide range of recently published state-of-the-art reconfiguration methods for performance evaluation both on simulation and hardware platforms. The proposed technique outperforms all other reconfiguration schemes and yields up to 76.3% and 27% lower ML compared to TCT and SP configurations, respectively.