UniEload: University Electrical Load Dataset
Published: 8 December 2025| Version 2 | DOI: 10.17632/d8r95wmzms.2
Contributors:
, Priyankar Biswas, Sumon HossainDescription
This paper presents a dataset on electrical power collected from a university campus in Bangladesh. It is meant to help research on energy forecasting in university settings. The dataset has hourly measurements of system voltage, three-phase currents (R, Y, B), and power factor (pf). It was also combined with weather data to aid research on load forecasting that takes weather into account. The weather parameters include temperature, humidity, precipitation, wind speed, and solar radiation.
Files
Steps to reproduce
CSV files are the RAW dataset files.
Categories
Electrical Engineering, Machine Learning, Time Series Analysis, Energy Consumption, Time Series Forecasting, Energy Forecasting, Forecasting of Consumption