UniEload: University Electrical Load Dataset

Published: 25 December 2025| Version 3 | DOI: 10.17632/d8r95wmzms.3
Contributors:
,
, Sumon Hossain

Description

This repository 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. The dataset spans from 1 August 2023 to 30 September 2025, covering all 24-hour periods from 9:00 AM to 8:00 AM daily.

Files

Steps to reproduce

CSV files are the RAW dataset files. The README file contains the concise information about the dataset and how to use it.

Categories

Electrical Engineering, Machine Learning, Time Series Analysis, Energy Consumption, Time Series Forecasting, Energy Forecasting, Forecasting of Consumption

Licence