Comparative analysis reveals meteorological database choice alters solar photovoltaic payback periods by up to 4.7 years, highlighting the financial risk of inaccurate weather data.
The selection of georeferenced meteorological databases is a critical technical and financial factor in photovoltaic (PV) system sizing. This study evaluates how database choice affects PV generation estimates and economic feasibility by combining bibliometric screening, technical validation, financial indicators, and multicriteria analysis. A bibliometric review of 5658 documents indexed in Scopus and Web of Science supports the selection of seven databases, compared across ten Brazilian locations. PV generation is estimated using both a simplified sizing approach and a higher-temporal-resolution model based on hourly irradiance, ambient temperature, and module thermal coefficients, enabling comparison with measured generation in a three-year case study in João Pessoa. Performance is assessed using MAE, MAPE, RMSE, R2, NPV, payback and the Analytic Hierarchy Process. Under the adopted PV model and AHP weighting structure, NASA POWER shows the strongest overall multicriteria performance in the analyzed Brazilian sample, ranking first in seven locations. Database choice causes variations of up to 4.70 years in payback and BRL 105,709.36 in NPV, equivalent to USD 21,082.84 at the 22 May 2026 exchange rate. The simplified CRESESB-based method overestimates annual generation by 6.79–12.64%, whereas NASA POWER reaches a best annual deviation of −1.66% in 2024.
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Neto et al. (2026) studied this question.
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