CAREER: Probabilistic Tools for High Reliability Monitoring and Control of Wind Farms

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

The research objective of this Faculty Early Career Development (CAREER) award is to create probabilistic tools for the design of high reliability systems with application to wind energy. The research focuses specifically on two innovative methods to reduce the costs of wind energy. First, probabilistic techniques will be developed to detect faulty turbine components in a fast and accurate manner. This will enable preventative maintenance or continued operation after selected component faults. Second, tools from stochastic optimal control theory will be applied to design damage-aware control strategies for the wind farm. Currently each turbine within a wind farm is operated to maximize its own captured power while ensuring that structural loads remain within design limits. Stochastic optimal control will be used to perform this trade-off by coordinating all turbines in the wind farm. This will enable a better trade-off between the revenue from power production and the true financial costs that arise due to structural loads. The research will lead to a significant reduction in operating costs for wind turbines thus improving the economic viability of wind energy. In addition, the research will be applicable to high reliability systems in other domains including aerospace, automotive, and medical devices. The research also addresses the need to develop a highly skilled workforce to design and maintain reliable wind turbines. The plan centers on a unique collaboration with a local community college, Mesabi Range, which offers a two-year technical program in wind energy maintenance. The technicians trained at Mesabi Range will benefit from a deeper understanding of the control and monitoring systems they encounter in the field. Students and researchers at the University of Minnesota will benefit from understanding the issues faced by wind turbine technicians. Finally, the research findings will be integrated into the university undergraduate and graduate curriculum.