Eunshin Byon

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We examine optimal repair strategies for wind turbines operated under stochastic weather conditions. In-situ sensors installed at wind turbines produce useful information about the physical conditions of the system, allowing wind farm operators to make informed decisions. Based on the information from sensors, our research objective is to derive an optimal(More)
In this multi-university collaborative research, we will develop a framework for the dynamic data-driven fault diagnosis of wind turbines which aims at making the wind energy a competitive alternative in the energy market. This new methodology is fundamentally different from the current practice whose performance is limited due to the non-dynamic and(More)
The global wind power industry involves operations in highly stochastic environments and thus faces challenges in enhancing reliability and reducing maintenance costs. Earlier studies related to wind energy facility reliability and maintenance focused more on qualitative aspects, discussing the unique influencing factors in wind power operations and their(More)
Wind farms provide a source of clean and renewable energy. However, unlike many industries where machines are operated under more or less static conditions, wind turbines suffer from stochastic loading due to the hourly or seasonal variation of wind speed and direction. The stochastic loading of wind turbines makes their degradation or failure prediction(More)