Optimal Performance Emulation of PSCs using the Elephant Herd Algorithm Associated with Experimental Validation

Abstract

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.