Abstract:
This study depicted maximum power extraction from perovskite solar cells under the
noticeable current density – voltage (J-V) hysteresis. The main objectives of this study
were to analyze the impact of scan rate on the J-V characteristics of PSC, and then to
develop a maximum power point tracking algorithm that could be efficient enough to
predict the most suitable maximum power point, even under the high levels of J-V
hysteresis. IonMonger, a MATLAB-based environment developed by Courtier et.al, was
used to study the impact of scan rate and its direction on the J-V characteristics of a threelayered PSC (Electron transport layer, Perovskite absorber layer, Hole transport layer). It
was observed that by increasing the scan rate from 50mV/s to 200mV/s, the losses in the
current density, at the interfaces, due to interfacial recombination increase, and ultimately
the hysteresis level increases. The hysteresis index is used as a parameter to evaluate the
hysteresis level present in the J-V characteristics of PSC. When the interfacial
recombination rates and effective doping densities of ETL and HTL were tuned, the
hysteresis was reduced to the minimum and the impact of scan rate and direction on the JV characteristics became negligible. A Random Forest Regression model is used to develop
an MPPT that could track the most suitable MPP even under a high level of hysteresis. It
was depicted in this study that even at high values of J-V hysteresis, the RFR – MPPT
predicted the MPP characteristics of PSC efficiently and did not overestimate and
underestimate the performance of PSC. 0.42mW/cm2 or 1.9% of MPP-power difference
was noticed in the prediction of MPP when there was a high level of hysteresis content
present and when there was negligible hysteresis present. The credibility of RFR – MPPT
was also investigated by comparing it with the two highly performed MPPTs in the solar
industry, and the RFR – MPPT performed very accurately and efficiently as compared to
Perturb & Observe and Incremental Conductance algorithms.
