Türkiye'nin yenilenebilir enerji potansiyelinin ve çevre protokolü uyumluluğunun değerlendirilmesine yönelik bir makine öğrenimi

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.