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Energy Conversion and Management
Elsevier
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Abstract: |
Harvesting maximum power from a partially shaded photovoltaic array is a critical issue that attracts the
attention of several researchers. As per the literature, it is found that providing an optimal reconfigured
pattern of the shaded photovoltaic array is an optimal solution for this issue. Therefore, in this paper,
an innovative fitness function has been considered with the artificial ecosystem-based optimization for an
electrical photovoltaic array reconfiguration approach. The proposed approach has been applied for the large
scale photovoltaic arrays including 9 ×9, 6 × 20, 16×16, and 25 × 25 photovoltaic array with different shade
patterns. The new fitness function has been validated via a comparison with the regular used weighted
function in literature. The quality of the solutions of the proposed artificial ecosystem-based optimization–
reconfiguration approach has been assessed and demonstrated via performing several measures namely fill
factor, percentage of power loss, mismatch power loss, and power enhancement in comparison with a total
cross-tied, particle swarm optimizer approaches, and harris hawks optimizer. Furthermore, the Wilcoxon
signed-rank test has been performed to illustrate the applicability, robustness, and consistency of the proposed
algorithm results across several independent runs. The analysis reveals the quality of the innovative fitness
function while integrating with the optimization algorithms in comparison to the weighted fitness function in
producing higher power values via attaining a more efficient photovoltaic array design. Furthermore, the results
confirmed the efficiency of the artificial ecosystem-based optimization–photovoltaic reconfiguration approach
in boosting the generated photovoltaic power by a percentage of 28.688%, 7.0197 %, 29.2565%, 8.3811%
and 5.3884 % across the considered systems with an uniform dispersion of the shadow on the photovoltaic
surface and providing highest consistent in the maximum power values across the independent runs.
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