Solar data
Description
This dataset contains solar photovoltaic power measurements collected over 21 days, with nine observations recorded per day between morning and late afternoon. The dataset includes time, solar irradiance, temperature, humidity, current, voltage, and generated power. The data was originally collected for an undergraduate research project on artificial neural network-based solar power prediction using MATLAB. It has since been reorganized and used in a Python-based reimplementation that compares two modelling approaches: an original feature set using solar irradiance, current, voltage, temperature, and humidity, and an environmental feature set using solar irradiance, temperature, humidity, and time of day. The dataset can be used for solar power prediction, regression modelling, neural network experiments, feature analysis, model validation, and studies examining the relationship between photovoltaic power output and environmental or electrical measurements.