ArticleScientific reports2025
Parameter identification of the PV systems based on an adapted version of human evolutionary optimizer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Optimized parameter estimation of solar PV models using an improved red-tailed hawk algorithm.Scientific reports · 2026Article
- A novel kangaroo escape optimizer for parameter estimation of solar photovoltaic cells/modules via one, two and three-diode equivalent circuit modeling.Scientific reports · 2025Article
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3 authors.
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Abstract
Modelling the circuit model parameters of photovoltaic (PV) cells and modules is one of the significant encounters in the field of solar energy. Lately, with the advance of the application of optimization algorithms, approximating the PV module parameters can be changed into an optimization problem. This research offers an optimization pipeline for the optimal collection of the parameters in the PV systems. The method is founded on a novel combination of a metaheuristic algorithm, termed AHEO (Adapted Human Evolutionary Optimizer) for the current goal. The key purpose of employing the AHEO in the paper is to minimalize the root mean square error (RMSE) between the forecast and the measured I-V curves of the PV system. The method has been confirmed on a commercial PV module and the results show its high accuracy with a RMSE decrease of 34.6% related to the conventional optimization methods.
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