Models for correcting hourly solar radiation data from the Meteonorm database for the Kyrgyz Republic

The study aims to improve the accuracy of modeling hourly solar radiation data in the Kyrgyz Republic, a region characterized by complex terrain, climate variability, and a lack of reliable climate data—factors critical for solar energy development amid a persistent energy shortage. The research involved comparing the long-term mean hourly global and diffuse solar radiation from the Meteonorm database with actinometric data from the Handbook on Climate of the USSR (Part 1) for four actinometric weather stations: Bishkek, Cholpon-Ata, Suusamyr, and Tian Shan. Regression analysis was employed to process the data. Based on its results, a procedure was developed to determine correction factors for adjusting monthly mean hourly solar radiation data depending on geographical latitude and elevation. The data points were divided into two groups: elevations below and above 2000 m above sea  level. Linear regression equations with a high coefficient of determination (0.93–0.99) were obtained, significantly reducing discrepancies between modeled and observed solar radiation data. The developed procedure was implemented as a web application using the Laravel PHP framework, which enables the automatic calculation, storage, and visualization of solar radiation data. Testing at the 80-kW solar power plant of the Kyrgyz State Technical University (Bishkek) showed a 20 % reduction in the normalized root mean square error (to 10–15 %) and a decrease in prediction error to below 5 %. The proposed Meteonorm data correction system improves the reliability of solar resource assessments, making it a valuable tool for the design and verification of photovoltaic power plants, as well as for refining the calculations of solar energy potential in the mountainous regions of Central Asia. 

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