SARIMA(X) AND DECISION TREE MODELS COMPARISON FOR LOAD FORECASTING IN ELECTRICAL GRIDS

Authors

DOI:

https://doi.org/10.30890/2567-5273.2024-33-00-008

Keywords:

STLF, SARIMA, SARIMAX, Decision Trees, load forecasting, electrical grid

Abstract

This work compares load forecasting models in the electrical network based on SARIMA(X) and Decision Tree. Various versions of the above models were trained on load data for 2021 for one of the substations in the Kyiv region. The day 01/01/2022 was select

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References

Hagan, M. T., & Behr, S. M. (1987). The Time Series Approach to Short Term Load Forecasting. IEEE Transactions on Power Systems, 2(3), 785–791. https://doi.org/10.1109/tpwrs.1987.4335210

G. Gross and F. D. Galiana, “Short-term load forecasting,” Proceedings of the IEEE, vol. 75, no. 12, pp. 1558–1573, 1987, doi: https://doi.org/10.1109/proc.1987.13927.

J. W. Taylor and P. E. McSharry, “Short-Term Load Forecasting Methods: An Evaluation Based on European Data,” IEEE Transactions on Power Systems, vol. 22, no. 4, pp. 2213–2219, Nov. 2007, doi: https://doi.org/10.1109/tpwrs.2007.907583.

Statsmodels.org, 2023. https://www.statsmodels.org

S. Nallathambi and K. Ramasamy, “Prediction of electricity consumption based on DT and RF: An application on USA country power consumption,” IEEE Xplore, Apr. 01, 2017. https://ieeexplore.ieee.org/document/8191939

“scikit-learn: machine learning in Python — scikit-learn 0.22.2 documentation,” scikit-learn.org. https://scikit-learn.org

Published

2024-06-30

How to Cite

Кирик, В., & Шаталов, Є. (2024). SARIMA(X) AND DECISION TREE MODELS COMPARISON FOR LOAD FORECASTING IN ELECTRICAL GRIDS. Modern Engineering and Innovative Technologies, 1(33-01), 12–17. https://doi.org/10.30890/2567-5273.2024-33-00-008

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Articles