Abstract
The Korea Institute of Energy Research builds Korean solar irradiance datasets, using gridded solar insolation estimates derived using the University of Arizona solar irradiance based on Satellite–Korea Institute of Energy Research (UASIBS–KIER) model, with the incorporation of geostationary satellites over the Korean Peninsula, from 1996 to 2019. During the investigation period, the monthly mean of daily total irradiance was in a good agreement with the in situ measurements at 18 ground stations; the mean absolute error is also normalized to 9.4%. It is observed that the irradiance estimates in the datasets have been gradually increasing at a rate of 0.019 kWh m−2 d−1 per year. The monthly variation in solar irradiance indicates that the meteorological conditions in the spring season dominate the annual solar insolation. In addition, the local distribution of solar irradiance is primarily affected by the geographical environment; higher solar insolation is observed in the southern part of Korea, but lower solar insolation is observed in the mountainous range in Korea. The annual capacity factor is the secondary output from the Korean solar irradiance datasets. The reliability of the estimate of this factor is proven by the high correlation coefficient of 0.912. Thus, in accordance with the results from the spatial distribution of solar irradiance, the southern part of Korea is an appropriate region for establishing solar power plants exhibiting a higher annual capacity factor than the other regions.
Highlights
The long-term variability in solar resources in space and time has been considered as a crucial factor in the life cycle of solar power systems, including installation, deployment, and operation (e.g., [1,2,3,4,5,6])
Ground observations are still limited in their ability to retrieve the spatial distribution of solar insolation and further investigate solar energy potentials at a regional or national scale
The monthly average of the daily total irradiance that is derived by the UASIBS–Korea Institute of Energy Research (KIER)
Summary
The long-term variability in solar resources in space and time has been considered as a crucial factor in the life cycle of solar power systems, including installation, deployment, and operation (e.g., [1,2,3,4,5,6]). The analysis of long-term in situ measurements by a pyranometer can help to understand the climatological variability in solar irradiance, due to the higher accuracy and reliability of the observations compared to remote sensing techniques [7,8]. Remote sensing techniques have been considered as an alternative approach for understanding the climatological characteristics of solar insolation (e.g., [9,10,11,12,13]).
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