Alessandro Nocente

Evaluating how the sources of uncertainty in solar modelling (e.g., input parameters, developed model chain) can influence the results’ accuracy is one of the main challenges when applied at high latitudes. In this study, a multi-stage validation workflow is implemented around five main stages: data acquisition, data quality check, solar radiation modelling, photovoltaic energy modelling, and experimental validation. Different data sources such as satellite observations, numerical reanalysis, and on-site ground measurements are considered as inputs, while the outcomes from each step of the model chain (e.g., decomposition modelling, transposition modelling, photovoltaic energy modelling) are compared against observations recorded from the solar radiation network at the Norwegian University of Science and Technology (NTNU-Solarnet) in Trondheim (Norway). In the first and second validation stages, the decomposition and transposition models with measured input parameters show the best accuracy indicators, but they do not fulfill the validation criteria. Conversely, in the third validation stage, the photovoltaic energy models with on-site ground measurements as inputs are experimentally validated. In conclusion, at high latitudes, the most accurate results are obtained when monitored solar irradiation data are used instead of satellite observations and numerical reanalysis. Furthermore, the shortest model chain is preferred, with equal data sources.