Machine Learning-Based Power Forecasting for Outdoor Sun-Tracking PV Systems Under Variable Sky Conditions in Semi-Arid Regions

This dataset contains raw and processed data used for photovoltaic (PV) power forecasting using machine learning models (Linear Regression, Random Forest, and Support Vector Machine). Location:URAER, Ghardaïa, Algeria (Semi-arid climate) Contents:1. Raw meteorological and PV system data2. Processed datasets used for model training3. Input/output data for machine learning models4. Forecast results for LR, RF, and SVM models5. Data used to generate all figures and statistical results Variables:- GHI: Global Horizontal Irradiance (W/m²)- Temperature: Ambient temperature (°C)- PV Power: Output power (W) Usage:The dataset allows full replication of the results presented in the associated research article. Author:Zaghba Layachi et al.