The influence of mobility modes within Positive Energy Districts (PEDs) has gained limited attention, despite their crucial role in reducing energy consumption and greenhouse gas emissions. Buildings in the European Union (EU) account for 40% of energy consumption and 36% of greenhouse gas emissions. In comparison, transport contributes 28% of energy use and 25% of emissions, with road transport responsible for 72% of these emissions. This study aims to design and optimize a synthetic PED in Istanbul that integrates renewable energy sources and public mobility systems to address these challenges. The renewable energy sources integrated into the synthetic PED model include solar energy, hydrogen energy, and regenerative braking energy from a tram system. Solar panels provided a substantial portion of the energy, while hydrogen energy contributed to additional electricity generation. Regenerative braking energy from the tram system was also utilized to further optimize energy production within the district. This system powers a middle school, 10 houses, a supermarket, and the tram itself. Optimization techniques, including Linear Programming (LP) for economic purposes and the Weighted Sum Method (WSM) for environmental goals, were applied to balance cost and CO₂ emissions. The LP method identified that the PED model can achieve cost competitiveness with conventional energy grids when hydrogen costs are below $93.16/MWh. Meanwhile, the WSM approach demonstrated that achieving a minimal CO₂ emission level of 5.74 tons requires hydrogen costs to be $32.55/MWh or lower. Compared to a conventional grid producing 97 tons of CO₂ annually, the PED model achieved reductions of up to 91.26 tons. This study contributes to the ongoing discourse on sustainable urban energy systems by addressing key research gaps related to the integration of mobility modes within PEDs and offering insights into the optimization of renewable energy sources for reducing emissions and energy consumption.

All the studies in urban railways gained importance with the requirement of developing in this area. However, not only technological development but also energy-saving conditions have great importance. One of these efficiency conditions is to know the optimum operating conditions. There are two electronic drive-warning systems. These warning systems are Driver Advisory System (DAS) and Automatic Train Operation (ATO), which are algorithm-based. To enrich these algorithms with meta-heuristic methods provides that it can be adapted to the changing operating conditions. Thus, flexible management can be achieved. In this study, the Particle Swarm meta-heuristic and Fmincon which is a nonlinear programming solver in MATLAB methods are used to calculate optimum driving speed, acceleration, cruising, coasting, and full braking times under different operating conditions. Comparative optimization results of these selected methods are presented. Thus, attention is drawn to the efficiency in driving technique with different optimization methods. Specific speed-specific driving time matches obtained can be used to develop innovative driving warning systems.

Increasing the utilization rate of regenerative braking energy in rail systems is one of the ongoing applications increasing in significance in recent years. In rail systems, braking is made with two ways, mechanical and electrical. While the energy released due to mechanical braking cannot be recovered, the energy released due to electrical braking can be reused as regenerative braking energy. This regenerative braking energy varies according to the dynamics of the system and it can be given back to the grid, stored in storage devices or burned in resistors (it is not desired). This study develops a novelty algorithm within the scope of this objective and provides the calculation of the regenerative braking energy recovery rate and then making a decision for storage or back to grid of this energy. Afterwards, the regenerative braking energy was calculated with the help of this algorithm for Eskisehir-Ankara and Ankara-Eskisehir trips in two different passengers (load) scenarios, using the YHT 65000 high-speed train, which was chosen as a case study. Then, with a decision maker added to this classical regenerative braking energy algorithm, it will be decided whether this energy will be stored or forward back into the grid for the purpose of providing non-harmonic energy to the grid.

Demiryolu taşımacılığı, güvenilir, rekabetçi ve çevre dostu bir ulaşım ve yük taşıma alternatifi olduğu için günümüzde, demiryolu hatlarındaki trafiğin artması kaçınılmaz bir durumdur. Artan yolcu talebi sonucu sıklaşan seferler, tren hızlarının yükselmesi ve yüklerinin artması ile birleşince mevcut demiryolu üstyapısına önemli ek yükler getirmektedir. Bu ek yükler, raylarda olası problemlerin ortaya çıkma olasılığını arttırmaktadır. Buna bağlı olarak, raylarda görülen kusurlar daha önemli hale gelmiş; rayların kusurlara karşı kontrol edilmesi ve bakımının zamanında yapılması büyük önem kazanmıştır. Bu çalışmada ray görüntüleri Artık Ağ mimarisini kullanan evrişimli yapay sinir ağı ile eğitilmiş ve ray üzerindeki kusurlar ve ray kırıkları yüksek bir başarıyla sınıflandırılmıştır. Böylelikle birebirine karışma ihtimali fazla olan ve ayrıca ray kırığı probleminin öncülü olabilecek ciddi ray yüzey kusurlarının başlangıç aşamasında tespiti ile bakım onarım faaliyetlerine katkı sunabileceği düşünülmektedir.

The global transition toward renewable energy is recognized as a critical strategy for mitigating climate change by reducing CO₂ emissions. This study examines the relationship between renewable energy adoption and carbon emissions in Germany, France, and Türkiye, utilizing Pearson correlation and Ordinary Least Squares (OLS) regression on data from 2008 to 2015. Unlike many studies on single-country contexts, this research adopts a comparative approach to assess how national energy profiles and policy frameworks influence emission outcomes. Findings indicate that France, supported by a balanced nuclear-renewable mix, achieves the most consistent emission reductions. Germany exhibits a moderate negative correlation between renewables and emissions but maintains high absolute emission levels. Türkiye, meanwhile, reveals weak or even positive correlations between renewables and emissions, reflecting challenges in integrating low-carbon solutions. These insights highlight the significance of context-specific strategies in designing effective energy transition policies and contribute to the broader discourse on aligning national actions with global climate targets.