报告平台：腾讯会议 ID：176 520 541
报 告 人：高志伟 教授
Wind energy is contributing to more and more portions in the world energy market. However, one deterrent to even greater investment in wind energy is the considerable failure rate of turbines. In particular, large wind turbines are expensive, with less tolerance for system performance degradations, unscheduled system shut downs, and even system damages caused by various malfunctions or faults occurring in system components such as rotor blades, hydraulic systems, generator, electronic control units, electric systems, sensors, and so forth. As a result, there is a high demand to improve the operation reliability, availability, and productivity of wind turbine systems. It is thus paramount to detect and identify any kinds of abnormalities as early as possible, predict potential faults and the remaining useful life of the components, and implement resilient control and management for minimizing performance degradation and economic cost, and avoiding dangerous situations. In this talk, the approaches and results developed in the research team at Northumbria University will be introduced.
Dr. Gao joined Northumbria University in 2011, and he is the Head of Electrical Power and Control Systems Research Group. Before joining Northumbira University, he held research and academic positions respectively in Newcaslte University, University of Liverpool, University of Leicester, University of Manchester, University of Duisburg-Essen, and Tianjin University. Dr. Gao is the senior member of IEEE, and HEA fellow. He was the recipient of the Alexander von Humboldt Research Fellowship in 2004. Dr. Gao is currently the Associate Editor of IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Industral Electronics, IEEE Transactions on Automatic Control and the editorial board member of Renewable Energy (Elsevier).