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The framework developed on this research begins with knowledge preparation and mapping of assorted geospatial metrics to each High-down and Bottom-up pathways. Further, the machine learning mannequin is skilled and used to estimate BFEFN values from BAFN, PPLNFN, and RLFN values. Next, the BFEFN values are used to calculate the technical potential (SP) with the help of the conversion components (CF). Finally, the calculated potential dataset is used to map the Levelised Cost of Electricity (LCOE) values using IRENA’s renewable power generation price knowledge. The detailed framework is described in the “Results” and “Methods” sections. Mannequin parameters and regional mappings are supplied in Supplementary Tables 6, 8-10 and Supplementary Fig. 3a-d.
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