Monthly Electricity Consumption with Exogenous Factors Datasets

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]. 3- " Aggregated Electricity and Temperature on City Level.csv" consists of the aggregated monthly electricity consumption records on the Dubai City level and the reported temperature. This file helps see the relation between temperature and electricity consumption. [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.