article · ECS Journal of Solid State Science and Technology
Perovskite solar cells offer an attractive alternative to traditional silicon photovoltaics due to solution processing and power conversion efficiencies surpassing 25 percent. However, environmental factors such as oxygen and humidity induce operational nonlinearities, hysteresis, and stability concerns. To improve performance assessment, single-, double-, and triple-diode electrical models were developed for two cell types, using the elephant herd optimization algorithm to determine optimal parameters. The optimization approach demonstrated clear superiority over competing algorithms, yielding parameter values with high similarity to experimental results. In particular, the triple-diode model successfully simulated cell electrical behavior. The analysis confirmed that incorporating dye sensitization on the titania compact layer significantly improves cell performance, lowering series resistance, diode ideality factors, and saturation currents while increasing shunt resistance and open circuit voltage.
Perovskite solar cells are prone to nonlinear performance drops caused by moisture and oxygen exposure. Accurate electrical models allow researchers and developers to understand these operational challenges and test cell designs rapidly. By providing a reliable simulation framework, this work supports more precise device analysis and guides material modifications, such as dye sensitization, to improve overall energy conversion efficiency.
This modeling and parameter extraction framework could be utilized by photovoltaic engineers and solar device manufacturers to evaluate cell designs before prototyping. Because the work focuses on algorithm development and experimental validation in a laboratory context, it represents applied research. Moving toward commercialisation would require integrating the algorithm into accessible design software for industrial solar cell developers.
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Photovoltaics (PVs) are among the most promising low-cost energy sources with high possibility of large-scale solar cell manufacturing and production. Perovskite solar cells (PSCs) are considered as the fore front of third generation of PVs. They are fabricated using solution processes and their power conversion efficiency now exceeds 25%, making them a very attractive alternative to the silicon based devices (amorphous and crystalline). The presence of humidity and oxygen in these cells leads to large degree of nonlinearity that affects their operation mechanisms, hysteresis phenomena, photovoltaic performance and stability. To face these issues, it is important to find the accurate PSCs models and their optimum parameters for assessing their performance. In this paper, three electrical models, single-, double- and triple-diode models, are developed for two types of PSCs and their parameters are optimally extracted using elephant herd optimization (EHO) paradigm. The simulation results have proved the EHO superiority compared with the competitive algorithms and confirmed a high similarity between the estimated parameters with the experimental ones. The proposed three diode model was able to effectively simulate via the EHO algorithm the electrical behavior of perovskite solar cells and confirmed that dye sensitization of the titania compact layer leads to higher performance expressed in terms of low series resistance, high shunt resistance, low diode ideality factor, low diode saturation current, and high open circuit voltage values.
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DOI: 10.1149/2.0271912jss
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