Forecasting electricity demand in Türkiye: A comprehensive review of methods, determinants, and policy implications

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dc.contributor.authorElbaş, Hakan
dc.contributor.authorBilgin, Turgay Tugay
dc.date.accessioned2026-02-08T15:11:14Z
dc.date.available2026-02-08T15:11:14Z
dc.date.issued2025
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThis review examines the methods, determinants, and forecasting horizons used in electricity demand forecasting in Türkiye. The study investigates how Türkiye's electricity demand is influenced by economic, climatic, socio-demographic, and technological factors, and explores the evolving landscape of forecasting techniques, from traditional statistical models to advanced machine learning and hybrid approaches. The research addresses three key questions: The significant determinants of electricity demand in Türkiye, the most effective forecasting methods, and the application of these insights to improve energy planning and policy development. Through a systematic analysis of peer-reviewed literature, official reports, and case studies, the study reveals the complex interplay of factors affecting electricity demand and the increasing sophistication of forecasting methodologies. Economic growth, industrial production, climate change, urbanization, and technological advancements emerge as primary drivers of demand, while artificial neural networks and hybrid models demonstrate superior forecasting capabilities. The study highlights the importance of integrated modeling approaches, sector-specific strategies, and the incorporation of climate projections in long-term planning. It also emphasizes the need for aligning energy policies with broader economic and environmental objectives. This review provides valuable insights for researchers, policymakers, and industry stakeholders, offering a comprehensive framework for understanding and improving electricity demand forecasting. © 2025 Erol Kurt. All rights reserved.
dc.identifier.doi10.30521/jes.1549293
dc.identifier.endpage158
dc.identifier.issue1
dc.identifier.scopus2-s2.0-105001663137
dc.identifier.scopusqualityQ3
dc.identifier.startpage132
dc.identifier.urihttps://doi.org/10.30521/jes.1549293
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5336
dc.identifier.volume9
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherErol Kurt
dc.relation.ispartofJournal of Energy Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzScopus_KA_20260207
dc.subjectAI
dc.subjectDemand forecasting
dc.subjectEnergy consumption
dc.subjectEnergy planning
dc.subjectEnergy policy
dc.titleForecasting electricity demand in Türkiye: A comprehensive review of methods, determinants, and policy implications
dc.typeReview Article

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