Utilizing The Time Series Model for Electricity Energy Consumption Prediction In Kirkuk Governorate, Iraq

Ahmed Shamar  Yadgar; Zana Najim  Abdullah; Abdulqader Ahmed  Jasim

Ahmed Shamar Yadgar University Of Kirkuk, Iraq
Zana Najim Abdullah University Of Kirkuk, Iraq
Abdulqader Ahmed Jasim University Of Kirkuk, Iraq

Keywords: Time series analysis (TSA), Vector autoregression (VAR), Electricity energy forecast, Kirkuk Governorate

Abstract

Correctness in the prediction of electrical consumption is essential as it allows for efficient utilization of energy without incurring excess cost or suffering from power outages. Many countries, including Iraq, have faced challenge in precise demand forecasting due to rising population, climate challenges and other factors. Despite several studies studying the energy prediction breake the time series models, but, in Kirkuk the dynamics of temperature, population growth and electricity consumption is not investigated in detail. The goal is to deploy VAR model for electricity consumption forecasting in Kirkuk while controlling for population and temperature influencing demand. The results present by the VAR model confirmed that population growth positively correlated with electricity consumption. This is especially handy because these two variables, energy demand and temperature, are interrelated over time. This study formulates a new forecasting model for Kirkuk, Iraq, using an advanced VAR (Vector Autoregressive) model with optimal lag order to produce the best possible forecast, particularly since large cities have their own special demographic and environmental factors. The results can provide for better management of the power grid which can inform the energy policies and infrastructural development in Kirkuk to better cater to the future electricity demands.

References

M. O. Adenomon and B. A. Oyejola, "Forecasting meteorological time series data with a reduced form Vector Autoregressive (VAR) Model and three univariate time series techniques: A comparative study," Social and Basic Sciences Research Review, vol. 2, no. 3, pp. 139-152, 2013.

S. T. Ahmed and H. A. Tahir, "Comparison between GM (1, 1) and FOGM (1, 1) models for forecasting the rate of precipitation in Sulaimani," Journal of Kirkuk University for Administrative & Economic Sciences, vol. 11, no. 1, pp. 301-314, 2021.

Y. Chang, C. S. Kim, J. I. Miller, J. Y. Park, and S. Park, "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, vol. 60, pp. 206-216, 2016.

I. Fahria and H. Stevanus, "Time series model of forecast electricity energy consumption in Bangka Belitung Governorate," in IOP Conference Series: Earth and Environmental Science, vol. 1108, no. 1, p. 012049, Nov. 2022.

M. Falk, F. Marohn, R. Michel, D. Hofmann, M. Macke, B. Tewes, et al., A first course on time series analysis: examples with SAS, 2011.

S. Hartini, M. P. Hadi, Sudibyakto, and A. Poniman, "Application of Vector Auto Regression model for rainfall-river discharge analysis," Forum Geografi, vol. 29, no. 1, pp. 1-10, 2015.

P. R. Hardani, A. Hoyyi, and S. Sudarno, "Peramalan laju inflasi, suku bunga Indonesia dan indeks harga saham gabungan menggunakan metode Vector Autoregressive (VAR)," Jurnal Gaussian, vol. 6, no. 1, pp. 101-110, 2017.

R. Ibnas, N. Salam, and N. Agustina, "Implementasi metode Vector Autoregressive (VAR) dalam meramalkan jumlah penduduk (studi kasus: Kabupaten Gowa)," Jurnal Matematika dan Statistika serta Aplikasinya, vol. 7, no. 2, pp. 56-61, 2019.

L. T. H. Nguyen, "Impacts of foreign direct investment on economic growth in Vietnam," 2023.

M. Pavlicko, M. Vojteková, and O. Blažeková, "Forecasting of electrical energy consumption in Slovakia," Mathematics, vol. 10, no. 4, p. 577, 2022.

H. A. Taher, S. O. Mohammed, A. S. Yadgar, and O. R. Musa, "Employing the ARDL model to predict the GDP of Iraq through the years (2005 to 2023)," University of Kirkuk Journal For Administrative and Economic Science, vol. 14, no. 4, 2024.

E. Taherifard, "Load and demand forecasting in Iraqi Kurdistan using time series modelling," 2019.

I. Al-Itabi, B. J. Hassan, and Y. K. Al-Timimi, "Time series decomposition and prediction of the monthly temperature at some stations in Iraq," The Iraqi Geological Journal, pp. 180-187, 2025.

J. Delgado, M. Aldarraji, B. Vega-Márquez, and B. Pontes, "Time series analysis of Iraq’s energy sector: Production, consumption, and trends," in International Conference on Soft Computing Models in Industrial and Environmental Applications, pp. 272-281, Cham: Springer Nature Switzerland, Oct. 2024.

M. Aldarraji, B. Vega-Márquez, B. Pontes, B. Mahmood, and J. C. Riquelme, "Addressing energy challenges in Iraq: Forecasting power supply and demand using artificial intelligence models," Heliyon, vol. 10, no. 4, 2024.