Hourly Energy consumption in industrial site

Citation Author(s):
Green Tech Institute (GTI), Mohammed VI Polytechnic University (UM6P)
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Last updated:
Sun, 02/20/2022 - 14:54
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The dataset contains an example of energy consumption, Functioning hours and Production KPI of different stages of the experimental open pit mine, mainly the destoning, the screening, and the train loading station. The Code is an example of the prediction algorithm, and the API can be used to apply the same algorithm used in this article.

In the proposed Dataset the energy consumption data for each station are collected from power meters and stored into a database that contains functioning hours and production.

In the data pre-processing stage, the gathered data are cleaned removing unwanted observations, such as energy consumed without equivalent timestamped production or functioning hours, dropping missing data. In the k-fold cross validation stage, the dataset is shuffled randomly, then split into groups, considering the group to be test data set or a holdout to compare. The remaining groups are considered training data set. Then comes fitting the model to the training data and testing it on the test data, keeping the evaluation score and discarding the model.


Dataset contains hourly energy consumption data of the experimental open pit mine of benguerir of different station, 

CSV file contains (Time, Functionning hour, Energy, and production kpi) 

it contains also an example of the FFQR algorithm to predict the data and the result as an API to test



Please cite as Laayati, Oussama, Mostafa Bouzi, and Ahmed Chebak. 2022. "Smart Energy Management System: Design of a Monitoring and Peak Load Forecasting System for an Experimental Open-Pit Mine" Applied System Innovation 5, no. 1: 18. https://doi.org/10.3390/asi5010018


Thank you!

Submitted by Seong Min on Tue, 04/05/2022 - 02:11

Thank you!

Submitted by Seong Min on Tue, 04/05/2022 - 02:11