Time-Series vs Typical Meteorological Year Data: Verification of PV String Sizing and Design

High-resolution weather data is needed for accurate photovoltaic (PV) system design. This study utilizes two commonly used datasets, Typical Meteorological Year (TMY) and Time Series (TS), both provided by the satellite-based solar model of Solargis. TMY datasets, derived from long-term historical time-series, simplify climate representation but do not necessarily account for short-term variability and uncommon weather events, which can result in inaccuracies in system design and performance predictions. In contrast, TS datasets include actual fluctuations and extreme conditions which are critical for precise system sizing and operational safety. Using Solargis Evaluate for PV design and simulation, case studies illustrate the significance of TS data in addressing extreme weather scenarios. For instance, during Storm Uri in Texas, TS data recorded an unprecedented low daytime temperature of-17.1 °C, which was not represented in the TMY dataset. This can lead to differences in the verification of design (string sizing) necessary for ensuring system operation during extremes. In addition, summer conditions in the same region showed TS data capturing higher temperatures compared to TMY.