Prediction of the Electricity Demand in the Market: An Application of Optimization and Machine Learning

  • سال انتشار: 1402
  • محل انتشار: مجله مهندسی برق مجلسی، دوره: 17، شماره: 2
  • کد COI اختصاصی: JR_MJEE-17-2_012
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 153
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نویسندگان

Ahmed Majed Althahabi

Al-Manara College for Medical Sciences, Maysan, Iraq.

Hassan Mohammed Abed

Mazaya University College, Iraq

Raed Khalid

Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, Iraq

Abrar Ryadh

Medical Laboratory Techniques Department, Al-Mustaqbal University College, ۵۱۰۰۱ Hillah, Babylon, Iraq

Ali Al Mansor

Department of Optical Techniques, Al-Zahrawi University College, Karbala, Iraq

Kadhum Al-Majdi

Department of Biomedical Engineering, Ashur University College, Baghdad, Iraq.

Adil Abbas Alwan

Mazaya University College, Iraq

چکیده

In this study, the combination of Gray Wolf Optimization and Artificial neural networks (GWO-ANN) algorithm was applied to predict the long-term electricity demand in Iraq, considering the nonlinear trend and uncertainties in the variables affecting it. The results indicate that the population and gross domestic product are significant explanatory variables for long-term energy demand, consistent with previous studies. Compared to other intelligent methods, the GWO-ANN algorithm requires less data for modeling and optimally designs the ANN structure. The modeling and forecasting model outperform the ANN in simulating and predicting the long-term energy demand. Based on the most likely scenario, the predicted electricity demand in Iraq will reach approximately ۴۱۵ GWh. Electricity is a critical factor in the development of societies and is utilized in various economic sectors.

کلیدواژه ها

Electricity demand, Gray Wolf Optimization, Artificial Neural Networks, Predictive modeling

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