The contribution of hydropower in meeting electric energy needs of MINT countries

Abstract

Mexico, Indonesia, Nigeria, and Turkey (collectively referred to as MINT) are fast-growing developing countries with the potential to achieve large and technologically advanced economies in the coming decades. Energy policies must be implemented to enable them to meet their increasing energy needs effectively and efficiently without threatening environmental health. Such policies will require realistic energy projections. The main goal of this paper is to develop hydroelectric energy generation (HEG) and total electricity production (TEP) projections for MINT countries to determine the contribution of HEG to the future TEP of MINT countries. Artificial neural networks (ANNs) trained by the arithmetic optimization algorithm (AOA) is used to develop HEG and TEP prediction models. Models were developed based on socio-economic, demographic, and energy indicators. To examine model performance accuracy, results obtained from ANN-AOA models were compared with results from ANN-BP (back propagation) and ANN-Jaya models. According to error criteria, ANN-AOA models outperformed these other models with both training and test sets. Hence, ANN-AOA technique was used to develop HEG and TEP projections. According to the present projections, the total HEG and HEP values of MINT countries in 2040 is expected to increase by 55.6% and 44.4% compared to 2022, reaching 215.8 and 1530.3 TWh, respectively. In addition, while the contribution of HEG to TEP was 56.9% in 2021, this value will decrease to 51.6% in 2040. The findings of this study suggest that current hydroelectric energy investments of MINT countries are not sufficient to achieve renewable energy targets. Consequently, recommendations are included herein for the energy policies of MINT countries.

Keywords

• : MINT countries
• Hydropower generation
• AOA algorithm
• Jaya algorithm
• Neural networks

MINT ülkelerinin elektrik enerjisi ihtiyaçlarının karşılanmasında hidroelektrik enerjinin katkısı

Öz

Meksika, Endonezya, Nijerya ve Türkiye (toplu olarak MINT olarak anılacaktır), önümüzdeki on yıllarda büyük ve teknolojik olarak gelişmiş ekonomilere ulaşma potansiyeline sahip, hızla büyüyen gelişmekte olan ülkelerdir. Çevre sağlığını tehdit etmeden artan enerji ihtiyaçlarını etkili ve verimli bir şekilde karşılayabilmeleri için enerji politikaları uygulanmalıdır. Bu politikalar gerçekçi enerji projeksiyonları gerektirecektir. Bu çalışmanın temel amacı, MINT ülkeleri için hidroelektrik enerji üretimi (HEG) ve toplam elektrik üretimi (TEP) projeksiyonları geliştirerek HEG'nin MINT ülkelerinin gelecekteki TEP'sine katkısını belirlemektir. Aritmetik optimizasyon algoritması (AOA) ile eğitilen yapay sinir ağları (YSA), HEG ve TEP tahmin modellerini geliştirmek için kullanılmıştır. Modeller sosyoekonomik, demografik ve enerji göstergelerine dayalı olarak geliştirilmiştir. Model performans doğruluğunu incelemek için, ANN-AOA modellerinden elde edilen sonuçlar, ANN-BP (geri yayılım) ve ANN-Jaya modellerinden elde edilen sonuçlarla karşılaştırılmıştır. Hata kriterlerine göre, ANN-AOA modelleri hem eğitim hem de test kümelerinde bu diğer modellerden daha iyi performans göstermiştir. Bu nedenle, HEG ve TEP projeksiyonlarını geliştirmek için ANN-AOA tekniği kullanılmıştır. Mevcut projeksiyonlara göre, MINT ülkelerinin toplam HEG ve HEP değerlerinin 2040 yılında 2022'ye kıyasla %55,6 ve %44,4 artarak sırasıyla 215,8 ve 1530,3 TWh'ye ulaşması beklenmektedir. Ayrıca, HEG'nin TEP'e katkısı 2021'de %56,9 iken, bu değer 2040 yılında %51,6'ya düşecektir. Bu çalışmanın bulguları, MINT ülkelerinin mevcut hidroelektrik enerji yatırımlarının yenilenebilir enerji hedeflerine ulaşmak için yeterli olmadığını göstermektedir. Sonuç olarak, MINT ülkelerinin enerji politikalarına yönelik önerilere yer verilmiştir.

Anahtar Kelimeler

• MINT ülkeleri
• Hidroelektrik üretimi
• AOA algoritması
• Jaya algoritması
• Yapay sinir ağları

Kaynakça

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