Türkiye'nin Yenilenebilir Enerji Potansiyelinin ve Çevre Protokolü Uyumluluğunun Değerlendirilmesine Yönelik Bir Makine Öğrenimi
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2025
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Küresel ısınma konusu 21. yüzyılın en kritik sorunlarından biri olarak tanımlanmakta ve fosil yakıt tüketimi sera gazı emisyonlarına en büyük katkıyı yapan unsur olarak görülmektedir. Bu sorunlara yanıt olarak dünya genelinde ülkeler, Paris Anlaşması gibi uluslararası iklim taahhütlerini yerine getirmek ve uzun vadeli sürdürülebilirlik hedeflerine ulaşmak için yenilenebilir enerji kaynaklarına geçişlerini hızlandırmaktadır. Türkiye hem ulusal enerji stratejisi hem de uluslararası yükümlülükleriyle uyumlu bir hedef olan 2053 yılına kadar net sıfır emisyona ulaşma hedefini belirlemiştir. Bununla birlikte, coğrafi, ekonomik ve teknolojik kısıtlamalar nedeniyle fosillerden yenilenebilir enerji kaynaklarına geçiş zorlu bir süreçtir. Bu çalışma, çevresel protokoller ve gelecekteki elektrik talebi projeksiyonları ile Türkiye'deki yenilenebilir enerji kapasitesini ve verimliliğini değerlendirmeyi amaçlamaktadır. Gelecekteki elektrik üretim ve kapasite eğilimlerinin belirlenmesi için elektrik üretim-iletim verileri ve ulusal enerji planları kullanılmaktadır. Bu çalışma kapsamında Çoklu makine öğrenimi modeli çeşitli senaryolarda çalıştırılarak sonuçlar elde edilmiştir. Sonuç olarak, düzenleyici tedbirlerin ve finansal yatırımların yansımaları incelenmiş ve ileriye dönük çıkarımlar elde edilmiştir. Bulgular, sürdürülebilir enerji politikalarının oluşturulmasında ve yatırımların yönlendirilmesinde senaryo tabanlı modellemenin önemini vurgulamaktadır.
The issue of global warming has been identified as one of the most critical challenges of the 21st century, with the consumption of fossil fuels being identified as a major contributor to greenhouse gas emissions. In response to these challenges, countries worldwide are expediting their transition towards renewable energy sources to meet international climate commitments, such as the Paris Agreement, and to achieve long-term sustainability goals. Türkiye has set itself the target of reaching net-zero emissions by 2053, a goal which is in alignment with both its national energy strategy and its international obligations. Nevertheless, due to geographical, economic and technological constraints, the transition from fossils to renewable energy sources is challenging. The present study aims to assess the capacity and efficiency of renewable energy in Türkiye with environmental protocols and future electricity demand projections. Electricity generation-transmission data and national energy plans are used to identify future electricity generation and capacity trends. In the context of this study, a range of machine learning models are executed across diverse scenarios, yielding a series of outcomes. Consequently, the repercussions of regulatory measures and financial investments were examined, and prospective inferences were derived. The findings emphasize the significance of scenario-based modelling in the formulation of sustainable energy policies and the guidance of investment decisions within the context of climate change mitigation.
The issue of global warming has been identified as one of the most critical challenges of the 21st century, with the consumption of fossil fuels being identified as a major contributor to greenhouse gas emissions. In response to these challenges, countries worldwide are expediting their transition towards renewable energy sources to meet international climate commitments, such as the Paris Agreement, and to achieve long-term sustainability goals. Türkiye has set itself the target of reaching net-zero emissions by 2053, a goal which is in alignment with both its national energy strategy and its international obligations. Nevertheless, due to geographical, economic and technological constraints, the transition from fossils to renewable energy sources is challenging. The present study aims to assess the capacity and efficiency of renewable energy in Türkiye with environmental protocols and future electricity demand projections. Electricity generation-transmission data and national energy plans are used to identify future electricity generation and capacity trends. In the context of this study, a range of machine learning models are executed across diverse scenarios, yielding a series of outcomes. Consequently, the repercussions of regulatory measures and financial investments were examined, and prospective inferences were derived. The findings emphasize the significance of scenario-based modelling in the formulation of sustainable energy policies and the guidance of investment decisions within the context of climate change mitigation.
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Enerji, Energy
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Sustainable Development Goals
3
GOOD HEALTH AND WELL-BEING

6
CLEAN WATER AND SANITATION

7
AFFORDABLE AND CLEAN ENERGY

8
DECENT WORK AND ECONOMIC GROWTH

9
INDUSTRY, INNOVATION AND INFRASTRUCTURE

11
SUSTAINABLE CITIES AND COMMUNITIES

12
RESPONSIBLE CONSUMPTION AND PRODUCTION

13
CLIMATE ACTION

17
PARTNERSHIPS FOR THE GOALS
