Performance Analysis and Predictive Modeling of Microinverters Under Varying Environmental Conditions

This study conducts both experimental and statistical analyses of microinverter performance within a compact AC-PV module that integrates a PV panel and a microinverter without battery integration. Using measurement data in combination with correlation analysis, derived thermal indicators, and quadratic regression modeling, the research provides a comprehensive quantitative assessment of microinverter behavior under practical operating conditions. A central finding is that the PV module’s temperature rise above ambient, ΔTmodule, serves as the most reliable single predictor of output power with a coefficient of determination of R2 = 0.85. The coefficient determination of ΔTmodule surpasses even solar irradiance and the microinverter temperature rise, ΔTmicro, with R2 = 0.80 and R2 = 0.75, respectively. This underscores the excess thermal loading of the module, rather than the absolute temperature alone. In contrast, ambient temperature (R2 = 0.04) proves to be a negligible variable for output power prediction. Also, comparing experimental temperatures with semi-empirical models showed that the PV temperature formula captures key thermal behavior, and the difference between theoretical and measured values is around 12%. From a design standpoint, these results highlight that enhancing thermal management at the module–inverter interface can directly improve output stability and ensure battery integration in the long-term reliability of an AC-PV module in future studies.