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Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region

Year 2025, Volume: 9 Issue: 2, 205 - 215

Sena Çadırcı , İbrahim Gürsu Tekdemir

Abstract

The planning of electrical energy systems can be realized in a more efficient and sustainable way by forecasting energy demand accurately. In this context, short-term load forecasting plays a critical role in optimizing energy production and distribution processes. In this study, short-term load forecasting was conducted using hourly electricity consumption data from a facility located in the Southeastern Anatolia Region between 2019–2022. The data were integrated with meteorological parameters to evaluate the impact of temperature. The performance of Multiple Linear Regression (MLR), Artificial Neural Networks (ANN), and AutoRegressive Integrated Moving Average (ARIMA) methods were compared. According to the results, the ARIMA method was the most successful with an accuracy rate of 92%, followed by the ANN model with 90% accuracy. The MLR method demonstrated relatively lower performance, achieving an accuracy rate of 89%. Moreover, ANN showed a strong capability to model complex relationships, while ARIMA excelled in datasets with seasonality. In conclusion, this study highlights the strengths and weaknesses of different methods, providing valuable contributions to energy planning and emphasizing the importance of analyses conducted using regional datasets.

Keywords

Electric load forecasting Short-term load forecasting Regression analysis Artificial neural networks Autoregressive integrated moving average

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There are 22 citations in total.

Details

Primary Language English
Subjects Electrical Energy Transmission, Networks and Systems, Electrical Engineering (Other)
Journal Section Research Articles
Authors

Sena Çadırcı 0009-0005-7842-9610

İbrahim Gürsu Tekdemir 0000-0003-1381-3513

Early Pub Date September 1, 2025
Publication Date September 2, 2025
Submission Date February 7, 2025
Acceptance Date May 2, 2025
Published in Issue Year 2025 Volume: 9 Issue: 2

Cite

APA Çadırcı, S., & Tekdemir, İ. G. (2025). Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region. Journal of Innovative Science and Engineering, 9(2), 205-215.
AMA Çadırcı S, Tekdemir İG. Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region. JISE. September 2025;9(2):205-215.
Chicago Çadırcı, Sena, and İbrahim Gürsu Tekdemir. “Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region”. Journal of Innovative Science and Engineering 9, no. 2 (September 2025): 205-15.
EndNote Çadırcı S, Tekdemir İG (September 1, 2025) Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region. Journal of Innovative Science and Engineering 9 2 205–215.
IEEE S. Çadırcı and İ. G. Tekdemir, “Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region”, JISE, vol. 9, no. 2, pp. 205–215, 2025.
ISNAD Çadırcı, Sena - Tekdemir, İbrahim Gürsu. “Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region”. Journal of Innovative Science and Engineering 9/2 (September2025), 205-215.
JAMA Çadırcı S, Tekdemir İG. Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region. JISE. 2025;9:205–215.
MLA Çadırcı, Sena and İbrahim Gürsu Tekdemir. “Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region”. Journal of Innovative Science and Engineering, vol. 9, no. 2, 2025, pp. 205-1.
Vancouver Çadırcı S, Tekdemir İG. Short-Term Electricity Load Forecasting and Seasonality Analysis Using Temperature and Artificial Intelligence Methods in the Southeastern Anatolia Region. JISE. 2025;9(2):205-1.
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