FORECASTING ENERGY DEMAND IN TURKEY USING DIFFERENT METAHEURISTIC METHODS: A COMPARATIVE STUDY

Taner Sevmiş; Rasim Çekik

doi:10.17780/ksujes.1580774

EN TR

FORECASTING ENERGY DEMAND IN TURKEY USING DIFFERENT METAHEURISTIC METHODS: A COMPARATIVE STUDY

Abstract

Energy demand forecasting plays a crucial role in shaping energy policies, particularly for countries like Turkey that experience rapid industrialization and urbanization. Accurately predicting energy demand helps to ensure energy supply security and to guide strategic investments, especially in transitioning towards renewable energy sources. This study explores the use of modern metaheuristic optimization methods to forecast Turkey's energy demand up to the year 2035, focusing on the effectiveness of various techniques in addressing this complex, multi-dimensional problem. The dataset used spans from 1979 to 2011 and includes economic and demographic indicators such as GDP, population, imports, and exports, which are key drivers of energy demand. Several metaheuristic algorithms, including The African Vultures Optimization Algorithm (AVOA), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Dynamic Bayesian Optimization (DBO), were applied to this dataset. A comparative analysis of these methods demonstrated that AVOA, GWO, DBO, and other similar approaches yielded the most accurate predictions, with minimum total error rates. The analysis revealed that the AVOA method outperformed other methods in terms of accuracy and computational efficiency by obtaining the lowest total error of 0.2391 and relative error percentage of 0.3565. The study highlights the significant role metaheuristic approaches play in improving the accuracy of energy demand forecasts and informs future policy decisions by identifying critical factors affecting Turkey’s energy consumption patterns. The findings are expected to contribute to more effective long-term energy planning and the development of sustainable energy policies.

Keywords

TÜRKİYE'DE ENERJİ TALEBİNİN FARKLI METASEZGİSEL YÖNTEMLER KULLANILARAK TAHMİNİ: KARŞILAŞTIRMALI BİR ÇALIŞMA

Öz

Enerji talebi tahmini, özellikle hızlı sanayileşme ve kentleşme yaşayan Türkiye gibi ülkelerde enerji politikalarının şekillendirilmesinde kritik bir rol oynamaktadır. Enerji talebinin doğru bir şekilde tahmin edilmesi, enerji arz güvenliğinin sağlanmasına ve yenilenebilir enerji kaynaklarına geçişte stratejik yatırımların yönlendirilmesine yardımcı olur. Bu çalışma, Türkiye'nin 2035 yılına kadar olan enerji talebini tahmin etmek amacıyla modern metasezgisel optimizasyon yöntemlerinin kullanımını araştırmakta ve bu karmaşık, çok boyutlu problemi ele almadaki etkinliklerini incelemektedir. Çalışmada, 1979-2011 yıllarını kapsayan ve GSYH, nüfus, ithalat ve ihracat gibi enerji talebinin temel belirleyicilerini içeren bir veri seti kullanılmıştır. Bu veri seti üzerinde Afrika Akbabaları Optimizasyon Algoritması (AVOA), Gri Kurt Optimizasyonu (GWO), Balina Optimizasyon Algoritması (WOA) ve Dinamik Bayes Optimizasyonu (DBO) gibi çeşitli metasezgisel algoritmalar uygulanmıştır. Karşılaştırmalı analiz sonuçları, AVOA, GWO, DBO ve benzeri yaklaşımların en düşük toplam hata oranlarıyla en doğru tahminleri sağladığını göstermektedir. Analizler, AVOA metodunun 0,2391 ile en düşük toplam hatayı ve 0,3565 bağıl hata yüzdesini elde ederek doğruluk ve hesaplama verimliliği açısından diğer yöntemlerden daha iyi performans gösterdiğini ortaya koymuştur. Çalışma, enerji talebi tahminlerinde metasezgisel yaklaşımların önemli bir rol oynadığını vurgulamakta ve Türkiye’nin enerji tüketim eğilimlerini etkileyen kritik faktörleri belirleyerek gelecekteki politika kararlarına ışık tutmaktadır. Bulgular, uzun vadeli enerji planlamasının daha etkili hale getirilmesine ve sürdürülebilir enerji politikalarının geliştirilmesine katkı sağlamayı amaçlamaktadır.

Anahtar Kelimeler

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Details

Primary Language

English

Subjects

Query Processing and Optimisation , Data Mining and Knowledge Discovery , Optimization in Manufacturing

Journal Section

Research Article

Authors

Taner Sevmiş
0000-0003-0034-4252
Türkiye

Rasim Çekik ^*
0000-0002-7820-413X
Türkiye

Publication Date

March 3, 2025

Submission Date

November 7, 2024

Acceptance Date

January 31, 2025

Published in Issue

Year 2025 Volume: 28 Number: 1

DOI

https://doi.org/10.17780/ksujes.1580774

IZ

https://izlik.org/JA85KB67HG

Cite

RIS / Bibtex

APA

Sevmiş, T., & Çekik, R. (2025). FORECASTING ENERGY DEMAND IN TURKEY USING DIFFERENT METAHEURISTIC METHODS: A COMPARATIVE STUDY. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 28(1), 441-459. https://doi.org/10.17780/ksujes.1580774

Cited By

METEOROLOJİK VERİLER KULLANILARAK RÜZGÂR ENERJİSİ ÜRETİMİNİN FARKLI MAKİNE ÖĞRENMESİ YÖNTEMLERİ İLE TAHMİN EDİLMESİ

Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

https://doi.org/10.17780/ksujes.1667861