Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia

Joint Authors

Harsarapama, Anindio P.
Aryani, Dwi Riana
Rachmansyah, Dedy

Source

Journal of Renewable Energy

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-09-22

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Mechanical Engineering

Abstract EN

Solar resource data derived from satellite imagery are widely available nowadays, either as an open-source or paid database.

This article is intended to assess open-source databases, which cover the region of Indonesia.

Here, four known solar resource databases, which spatially cover the Indonesian archipelago, have been used, namely, Prediction of Worldwide Energy Resource (POWER), Surface Solar Radiation–Heliosat-East (SARAH-E), CM SAF Cloud, Albedo, Radiation edition 2 (CLARA-A2), and SolarGIS.

In addition, a minor portion of the Meteonorm database by Meteotest, around five sample points across Indonesia, has been assessed in terms of coherency to the four mentioned databases.

Correlation coefficient and relative bias of the multiyear monthly mean annual cycle global horizontal irradiation (GHI) between pairs of databases are inspected.

Three out of four databases are then validated through the available irradiation ground measurement data provided by the World Radiation Data Centre (WRDC).

The correlation between each pair varies mostly between 0.7 and 1, which shows that the four databases to a certain extent agree on how the intermonthly variation would behave throughout the year.

On the other hand, the validation result reveals that the three databases, i.e., POWER, CLARA-A2, and SARAH-E, are suffering from positive bias error ranging from 3% to 7%.

Despite that fact, the correlation between measured and estimated values is still acceptable with SARAH-E showing the best performance among the three.

Careful selections and adjustment enable the possibility of these databases to be utilized as a tool for depicting interannual and intermonthly variations of solar irradiation throughout the Indonesian archipelago.

American Psychological Association (APA)

Harsarapama, Anindio P.& Aryani, Dwi Riana& Rachmansyah, Dedy. 2020. Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia. Journal of Renewable Energy،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1190293

Modern Language Association (MLA)

Harsarapama, Anindio P.…[et al.]. Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia. Journal of Renewable Energy No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1190293

American Medical Association (AMA)

Harsarapama, Anindio P.& Aryani, Dwi Riana& Rachmansyah, Dedy. Open-Source Satellite-Derived Solar Resource Databases Comparison and Validation for Indonesia. Journal of Renewable Energy. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1190293

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1190293