Monthly Electricity Consumption with Exogenous Factors Datasets

Published: 20 January 2023| Version 1 | DOI: 10.17632/4b8vjvc7yw.1
Omnia Abu waraga,


This dataset presents the monthly electricity consumption forecasting dataset on the repository level of the city of Dubai from May 2017 – December 2019 that includes exogenous parameters, namely, temperature, population, number of buildings, expatriate ratio, number of connected customers, and building occupancy. This repository consists of two files: 1- "Aggregated Dataset.csv" consists of the aggregated monthly electricity consumption records on the community level and the exogenous parameters. This dataset is generated using the simulation software. 2- "Final Dataset - Processed.csv" contains the final dataset generated after applying the preprocessing and feature importance steps. This dataset is used to model the electricity consumption predictors presented in our manuscript [1]. [1]M. Abdallah, M. Abu Talib, M. Hosny, O. Abu Waraga, Q. Nasir, M.A. Arshad, Forecasting Highly Fluctuating Electricity Load using Machine Learning Models Based on Multimillion Observations, Advanced Engineering Informatics, 53 (2022), 101707.


Steps to reproduce

To produce this dataset, please use the simulation software []


University of Sharjah


Electricity, Energy Consumption