Key advances on triple-junction perovskite–perovskite–Si solar cells with an unprecedented efficiency of 24.4% and enhanced long-term thermal stability are reported via the development of high-performance middle perovskite solar cell.

This study investigates the impact of degradation in perovskite‐silicon tandem solar cells by means of energy yield (EY) modelling over the entire lifetime. First, we assess the impact on EY of degradation in the individual solar cell parameters of the perovskite top cell. Our analysis reveals that degradation in fill factor, due to a decline in perovskite top cell shunt resistance (RSh), has the most severe impact on the EY, emphasizing the imperative to rectify perovskite imperfections in thin film processing causing RSh decline. Second, we investigate implications of degradation in the perovskite top cell on the EY of current mismatched tandem solar cells. Third, we examine critical thresholds for the “acceptable degradation levels” in the perovskite top cell with regard to degradation in each solar cell parameter, assuming that the total loss in EY must be comparable to the degradation in state‐of‐the‐art silicon. Overall, our study highlights that degradation of the perovskite top cell needs to be assessed with care when extrapolating the impact on the lifetime EY of perovskite‐silicon tandem solar cells. The severity of degradation for different degradation mechanisms in a single junction perovskite solar cell cannot be translated one‐to‐one to tandem devices.

This work proposes and evaluates a method for the nowcasting of solar irradiance variability in multiple time horizons, namely 5, 10, and 15 min ahead. The method is based on a Convolutional Neural Network structure that exploits infrared sky images acquired through an All-Sky Imager to estimate the range of possible values that the Clear-Sky Index will possibly assume over a selected forecast horizon. All data available, from the infrared images to the measurements of Global Horizontal Irradiance (necessary in order to compute Clear-Sky Index), are acquired at SolarTech^LAB in Politecnico di Milano. The proposed method demonstrated a discrete performance level, with an accuracy peak for the 5 min time horizon, where about 65% of the available samples are attributed to the correct range of Clear-Sky Index values.

Long-term stability of the perovskite top cell remains a hurdle to commercializing perovskite–silicon tandem (PST) solar cells. While accelerated tests provide valuable insights into degradation kinetics, they fail in predicting real-world degradation behavior. Keeping stressors constant, accelerated tests neglect dynamic conditions in actual operational environments, like diurnal and seasonal temperature and irradiance variability. We address this challenge by integrating a degradation function into our energy yield (EY) modelling software which integrates degradation in collection efficiency (and thus photocurrent) over time due to light and heat exposure, bridging the gap between accelerated testing and in real-world stability assessment. By linking the EY model to measurable material parameters like activation energy governing degradation pathways, this approach enables physically grounded degradation modelling. Based on degradation observed under accelerated tests, the model predicts PST operational lifetimes in diverse climates, highlighting the substantial discrepancy between lifetimes measured under accelerated testing and real-world locations. Applied to a PST solar cell, we show that an operational lifetime (T_90,Agg) of about 1400 h under ISOS-L2 (1 Sun, 85 °C), translates to several months in-field (about 26 months in arid Phoenix and 42 months in temperate Seattle), demonstrating strong climate dependence. We also provide a practical mapping from ISOS-L2 to real-world lifetimes and estimate the minimum stability threshold needed for deployment as around 4000 h T_90,Agg under ISOS-L2, translating to more than 5 years of operation across the investigated locations. After device-specific parameterization from appropriate aging tests, this device-agnostic framework allows stability-aware EY modelling to predict real-world degradation.