Gene Evaluation Algorithm for Reconfiguration of Medium and Large Size Photovoltaic Arrays Exhibiting Non-Uniform Aging



Alkahtani, Mohammed ORCID: 0000-0003-2801-698X, Hu, Yihua, Wu, Zuyu, Kuka, Colin Sokol, Alhammad, Muflih S and Zhang, Chen
(2020) Gene Evaluation Algorithm for Reconfiguration of Medium and Large Size Photovoltaic Arrays Exhibiting Non-Uniform Aging. Energies, 13 (8). p. 1921.

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Abstract

<jats:p>Aging is known to exert various non-uniform effects on photovoltaic (PV) modules within a PV array that consequently can result in non-uniform operational parameters affecting the individual PV modules, leading to a variable power output of the overall PV array. This study presents an algorithm for optimising the configuration of a PV array within which different PV modules are subject to non-uniform aging processes. The PV array reconfiguration approach suggests maximising power generation across non-uniformly aged PV arrays by merely repositioning, rather than replacing, the PV modules, thereby keeping maintenance costs to a minimum. Such a reconfiguration strategy demands data input on the PV module electrical parameters so that optimal reconfiguration arrangements can be selected. The algorithm repetitively sorts the PV modules according to a hierarchical pattern to minimise the impact of module mismatch arising due to non-uniform aging of panels across the array. Computer modelling and analysis have been performed to assess the efficacy of the suggested approach for a variety of dimensions of randomly non-uniformly aged PV arrays (e.g., 5 × 5 and 7 × 20 PV arrays) using MATLAB. The results demonstrate that enhanced power output is possible from a non-uniformly aged PV array and that this can be applied to a PV array of any size.</jats:p>

Item Type: Article
Uncontrolled Keywords: solar photovoltaic, rearrangement, non-uniform aging, reconfiguration, gene evaluation algorithm
Depositing User: Symplectic Admin
Date Deposited: 05 May 2020 10:12
Last Modified: 17 Mar 2024 08:08
DOI: 10.3390/en13081921
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3085986