Solar energy supported innovative energymodeling, optimization and analysis inrailway systemsmine

The importance is given to transport and energy in Turkey in recent years, so these studies which include transport and energy will have double remerkable. In this context, there are many components of the railways but in this thesis, three innovative studies in different areas have been carried out. The first is to determine the efficiency correctly of motors. For this purpose, the energy efficiency of induction motors, which are frequently used in railway systems, is estimated with three innovative hibrit methods; these are Artificial Neural Networks with Auto Regressive-1, Artificial Neural Networks with Auto Regressive-4, Artificial Neural Networks with Residual, and the estimation results are shared. Secondly, the estimation of solar energy -a renewable energy source- was made for 2015-2016 years information's which get from meteorology by Two-Dimensional Discrete Discrete Cosine Transform, Two-Dimensional Mychelski Algorithm and a hibrit method of combination of these two. According to these estimations, predict how amount of power can be met for a fast train for different voyages Eskişehir-Ankara direction; 6:20, 8:15, 13:10 ve 18:00 voyages) and the results are shared. Thirdly, the mathematical models of two different types of railway traction vehicles based on different speed, load, ramp and curve values are created by least squares (LSM) method and then the most efficient (optimum) working points are obtained by Gradient, Curve Superpozition with using Normalization and Particle Swarm Methods and their results are shared. The energy efficiency in the railway systems, which is generally considered in only one single point, is based on four different areas (mathematical modeling of railway traction vehicles, estimation of energy efficiency of induction motors used in railway traction vehicles, prediction of the solar power which is a clean energy source and the help of created mathematical models detection of the most efficiency working points are found) in this thesis. These findings offer applicable and sustainable solutions.