Using The Box-Jenkins Method In Time Series To Predict The Monthly Electrical Loads In (Babylon Governorate - Shomali District)

Hayder Kadim  Mohammed; Ali Kazim  Jari; Wissam Sadiq  Khudair

doi:10.24297/jam.v23i.9576

Authors

Hayder Kadim Mohammed Directorate of Education Al-Qadisiyah, Ministry of Education, Iraq
Ali Kazim Jari Directorate of Education Al-Qadisiyah, Ministry of Education, Iraq
Wissam Sadiq Khudair Directorate of Education Babylon, Ministry of Education, Iraq.

DOI:

https://doi.org/10.24297/jam.v23i.9576

Keywords:

Period Sequence, Appropriate Model For The Data Is (3-1-2) ARMA, Time Series Analysis, Box-Jenkins Method

Abstract

The topic of time series analysis is considered one of the important statistical topics to explain the phenomena that occur during a specific period of time. Time sequence examination objects to find an accurate account of the sequence, build a suitable perfect to interpret its behavior, and use the effects to predict the future time series . We using the Box-Jenkins method in the period sequence to predict the monthly electrical loads in (Babylon Governorate - Shomali district), and we have found that the studied time series is unstable in the mean and variance, we note that the time series is stable in the nasty and alteration. Autocorrelation and incomplete autocorrelation coefficients are used for the original data. Through these coefficients, we conclude that the appropriate model for the data is (3-1-2) ARMA. This model was chosen as it obtained the least (ARAM), and thus the model is appropriate for the data and the use of predictive values until the year (2022).

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