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This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.


In the study, the solar energy resource in the Central Luzon Region (Region 3), Philippines was determined using r.sun – a topography-based solar radiation model implemented in GRASS GIS – and suitable sites for the installation of ground-mounted solar photovoltaic (PV) farms were identified using the Analytic Hierarchy Process (AHP) to determine the weights of different physical, environmental, socio-economic, risk, and constraint criteria. For the resource assessment, the inputs to r.sun used in the study consisted of freely available data that include: an SRTM (90m resolution) Digital Elevation Model (DEM) and monthly average Linke turbidity coefficients available from the SoDA (Solar Radiation Database) webservice (www.soda-is.com). Daily solar radiation data from eight (8) measuring stations throughout the region were gathered. Readings from six (6) stations were used to interpolate monthly clear-sky index rasters while the readings from the remaining two (2) stations were used to validate the modelled monthly average Global Horizontal Irradiation (GHI) computed by r.sun. For the site suitability analysis, different criteria rasters were created and combined using weighted overlay to generate a suitability map for ground-mounted solar PV farms in the region. From the results, the monthly average GHI in the region computed by r.sun ranged from 3706.8 Wh/m2 - day in December to 6021.0 Wh/m2 -day in May with an annual average GHI of 4727.12 Wh/m2 -day indicating a good amount of resource potential. High GHI values were observed for the summer months of March to May (Mean: 5640.26 Wh/m2 -day) while the cold and rainy season ranging from July to December showed relatively lower values (Mean: 4298.98 Wh/m2 -day). The Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) between the measured and modelled GHI were 352.88 Wh/m2 -day and 8.53%, respectively, with the lowest error in March (73.94 Wh/m2 -day, 1.44%) and the highest in August (844.01 Wh/m2 -day, 21.65%). In fact, the model performed well for the months of January to June (MAE: 192.18 Wh/m2 -day, MAPE: 3.83%) and slightly poorer for July to December (MAE: 512.824 Wh/m2 -day, MAPE: 13.22%). For further study, other data sources and inputs can be looked into to improve the accuracy of the resource assessment and site suitability analysis. Aside from this, the use of more solar radiation recording stations for validation is preferred in order to better validate the results of r.sun and its applicability for solar energy resource assessment in the Philippines.



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