Kurtuluş DEĞER, Musa Galip ÖZKAYA, Fatih Emre BORAN

Modelling and Analysis of Future Energy Scenarios on the Sustainability Axis

Bu çalışma Türkiye için 2030 yılına ait sürdürülebilir bir elektrik enerjisi karması seçeneği önerilmesini amaçlamaktadır. İlk olarak, MLP ANN ve GPRM’yi kapsayan bir yöntem kullanılarak Türkiye’nin 2030 yılı elektrik enerjisi talebi tahmin edilmiştir. ANN modelinde dikkate alınan bağımsız değişkenler nüfus, GDP, ithalat, ihracat ve IPI olmaktadır. Her bir bağımsız değişkenin gelecekteki değerleri tek değişkenli zaman serisi yaklaşımı temelinde bir GPRM modeli kullanılarak tahmin edilmiştir. ANN modeli daha sonra bağımsız değişkenlerin gelecekteki değerleri temelinde elektrik enerjisi talebinin tahmin edilmesinde kullanılmıştır. İkinci olarak, tahmin edilen elektrik talebi dikkate alınarak dört farklı elektrik karması senaryosu geliştirilmiştir. Senaryoların sürdürülebilirlik değerlendirilmesi TOPSIS kullanılarak çevresel, ekonomik, teknik ve sosyal kategorileri dâhilinde sınıflandırılmış on farklı kritere göre gerçekleştirilmiştir. Buna ek olarak, belirtilen kategoriler için dört farklı ağırlık seti belirlenmiş ve bir duyarlılık analizi de gerçekleştirilmiştir. 2030 yılı için yapılan tahmin işlemine göre Türkiye’nin elektrik enerjisi talebi ≈ 384,569 GWh olarak bulunmuştur. TOPSIS metodu ile yapılan değerlendirmeye göre, karşılaştırmalı olarak daha yüksek nükleer enerji üretim yüzdesine sahip olan Senaryo-(C) en sürdürülebilir elektrik enerjisi karması senaryosu olarak belirlenmiştir.

Anahtar Kelimeler:

Enerji, Sürdürülebilirlik Değerlendirmesi, Yapay Sinir Ağı, Gri Tahmin, TOPSIS

Modelling and Analysis of Future Energy Scenarios on the Sustainability Axis

This study aims to propose a sustainable electricity mix option for Turkey by 2030. First, the electricity demand of Turkey by 2030 is estimated by employing a method that comprises MLP ANN and GPRM. Population, GDP, imports, exports, and IPI are considered independent variables used in the ANN model. The future values of each of the independent variables are predicted by a GPRM model based on a univariate time series approach. ANN model is then employed to predict electricity demand based on the future values of independent variables. Secondly, four diverse electricity mix scenarios are developed considering the forecasted electricity demand. The sustainability evaluation of the scenarios is performed using TOPSIS method considering ten different criteria classified into environmental, economic, technical, and social categories. Furthermore, four diverse weight sets are determined for the given categories, and also a sensitivity analysis is carried out. Turkey’s electricity demand is found out as ≈ 384,569 GWh according to the prediction for the year 2030. The Scenario-(C), which has a comparatively higher percent of nuclear energy generation, is determined as the most sustainable electricity mix scenario according to evaluation with the TOPSIS method.

Keywords:

Energy, Sustainability Assessment, Artificial Neural Network, Grey Prediction, TOPSIS,

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