Statistical Model of Outdoor Perovskite Performance

Perovskite outdoor reliability is at the moment insufficient to allow for commercial use. The first step in improving the reliability is correctly assessing the outdoor performance, which is complicated by varying irradiance, module temperature and spectrum. In this contribution we propose a statistical model for outdoor performance of perovskites: a multiple linear regression model which can be trained on first month’s data. We show that with this model, we can accurately predict the performance of the perovskites under any occurring weather conditions, which can then be compared to the measured outdoor performance. With respect to alternative analysis methods, this offers an improved accuracy both in time and in the offered variable.