No abstract

No abstract

No abstract

The important parts of a transformer, such as the core, windings, and insulation materials, are in the oil-filled tank. It is difficult to detect faults in these materials in a closed area. Dissolved Gas Analysis (DGA)-based fault diagnosis methods predict a fault that may occur in the transformer and take the necessary precautions before the fault grows. Although these fault diagnosis methods have an accuracy of over 95%, their validity is controversial since limited data are used in the studies. The success rates and reliability of fault diagnosis methods in transformers, one of the most important pieces of power systems equipment, should be increased. In this study, a hybrid fault diagnosis system is designed using DGA-based methods and Fuzzy Logic. A mathematical approach and support vector machines (SVMs) were used as decision-making methods in the hybrid fault diagnosis systems. The results of tests performed with 317 real fault data sets relating to transformers showed accuracy of 95.58% using a mathematical approach and 96.23% using SVMs.

The increasing consumption of energy and the greenhouse-gas emissions are challenges in the transport and building sectors. Compared to the other transportation types public railway transport systems are the most energy efficient regarding carbon footprint. Modern urban railway public transport systems have the significant advantages of large passenger capacity, punctuality, safety, going green in the urban environment and reducing carbon footprint, is a scientific consensus. However, the energy demand for railways are increasing in proportion to passenger load, require implementing innovative solutions for optimizing the energy consumption and reducing carbon emission. Leadership in Energy and Environmental Design (LEED) is a building rating system used worldwide. The credit categories of the LEED consist of seven different topics from the Energy and Atmosphere to Materials and Resources. In this study, the LEED certification application to railway station and facilities will be discussed mainly energy efficiency criteria.