SaurKshetra: A Dataset for Solar Farms Potential Site Mapping using Suitability parameters in India

Description

This dataset tests the hypothesis that long-term reanalysis of environmental and solar irradiance variables can reliably indicate relative solar energy potential across India in the absence of dense ground measurements. Final Dataset.xlsx (Jan 2013–Dec 2022) contains sitewise time series of solar irradiance, air temperature, cloud cover, albedo, precipitation, latitude, longitude and timestamp, all extracted from NASA POWER, temporally aligned, unit-standardized, and cleaned for missing values. Exploratory analysis shows clear seasonal and regional patterns (monsoon-driven drops in irradiance, latitudinal gradients) useful for comparing sites and assessing inter-annual variability. Use the data for geospatial site screening, clustering, ML-based suitability or predictive models — treat values as indicative (regional/relative) and validate site-level conclusions with in-situ measurements where possible.

Steps to reproduce

Steps to Reproduce 1. Download the Final Dataset.xlsx file from this repository. 2.Load the file into any data analysis environment (e.g., Python, R, MATLAB, Excel). 3.Parse the timestamp column to a datetime format and verify latitude–longitude coordinates. 4.Use the provided variables (solar irradiance, temperature, cloud cover, albedo, precipitation) for analysis such as visualization, clustering, or model training. 5.Apply your chosen geospatial or machine-learning methods to reproduce solar potential assessment results.

Institutions

• Vishwakarma Institute of Information Technology

  Maharashtra, Pune

Categories

Licence