Energy Demand Forecasting and Policy Development in Turkey

Ercan Köse () and Sevil Kutlu Kaynar
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Ercan Köse: Electrical-Electronics Engineering Department, Tarsus University, Tarsus, 33400 Mersin, Turkey
Sevil Kutlu Kaynar: Energy Systems Engineering ABD, Graduate Education Institute, Tarsus University, Tarsus, 33400 Mersin, Turkey

Energies, 2025, vol. 18, issue 13, 1-31

Abstract: As Turkey’s energy demand surges due to industrialization, population growth, and economic development, precise forecasting of electricity demand has become crucial for ensuring energy security and facilitating sustainable planning. This study undertakes an analysis of Turkey’s current energy landscape and develops long-term electricity demand forecasts utilizing a diverse array of statistical and machine learning models, including linear regression, polynomial regression, and artificial neural networks (ANNs). By incorporating economic indicators, demographic trends, and historical consumption data, this research projects Turkey’s electricity demand up to 2045. Among the various influencing factors, industrial production stands out as the most significant driver. The findings offer strategic insights into infrastructure investments, the integration of renewable energy, and policies aimed at enhancing efficiency. This research presents a data-driven, policy-oriented framework to assist decision-makers in reducing import dependence while steering Turkey towards a sustainable energy transition.

Keywords: electricity demand forecasting; regression models; artificial neural networks; renewable energy; energy policy; time series; Turkey (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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