Reliability based evaluation of wind power systems
Prof. Dr. Serkan Eryilmaz
Department of Industrial Engineering
Date: December 7, Friday, 13:40
Place: EA 409
Wind enery is one of the rapidly growing renewable energies in the world. A typical wind power system consists of wind turbines which convert the kinetic energy in the wind into electrical energy, and they are the main components of the wind energy system. The power generated by a wind turbine is dependent on wind speed which is a random variable. Therefore, the power produced by a wind turbine is also a random variable. There are two sources of randomness for a single wind turbine. The one which is external is concerned with the wind speed, and the other one is related to internal structure, i.e. mechanical state (down or up) of the turbine. Obviously, the latter one is related to reliability of the turbine. Manifestly, both sources have impact on the performance of the turbine, i.e. the power produced by the turbine. In this talk, the reliability based analysis of the capacity of the wind power system will be presented. The usefulness of the results will be demonstrated for some wind speed probability distributions and wind turbine models to evaluate the aggregate power that will be produced by the plant.
Joint work with Dr. Yılser Devrim (Atılım University, Department of Energy Systems Engineering)
Bio: Dr. Serkan Eryılmaz is currently vice president for research at Atilim University. He is the present co-chair of the System Reliability Technical Committee of the European Safety and Reliability Association. He served as Associate Editor for the IEEE Transactions on Reliability, and is currently serving as an Area Editor of the IISE Transactions-Quality & Reliability Engineering. Professor Eryılmaz’s research interests include reliability, applied probability and stochastic modeling. He is the author of more than 150 publications. He was honored by TUBITAK Science Incentive Award thanks to his highly qualified studies on system reliability in the field of stochastic models/processes in operations research.