Research Abstracts Online
January - December 2011
University of Minnesota Twin Cities
College of Science and Engineering
of Civil Engineering
St. Anthony Falls Laboratory
PI: Seokkoo Kang
Development of a High-Resolution Computational Model for Simulating Offshore Wind Turbines and Farms
This project will contribute toward achieving the Department of Energy’s research objective to develop modeling and analysis design tools for assessing offshore wind turbine technologies. Computational modeling can play a major role in developing and evaluating the performance of novel turbine design, mooring systems, and floating platforms. In addition, computational tools provide the only feasible approach for site-specific optimization of offshore wind farms and for assessing environmental impacts of wind farms. For computational tools to make a major impact in developing offshore wind energy resources, however, they need to resolve the effects of the coupled interaction of atmospheric turbulence and ocean waves on aerodynamic performance and structural stability and reliability from the scale of an individual turbine to the scale of a complete offshore wind farm.
This project seeks to develop and validate state-of-the-art computational tools capable of simulating atmospheric turbulence and wave effects in offshore wind farms. Specific objectives are: to develop an advanced, multi-scale and multi-resolution computational framework for simulating offshore wind turbines and farms, including structural dynamics, wave dynamics, air-water interface dynamics and multi-scale atmospheric turbulence effects; to formulate the computational tools to take full advantage of massively parallel computational resources enabling computational modeling of offshore turbines and farms at unprecedented computational resolution; and to validate the computational models using data from novel laboratory measurements specifically tailored to emulate the key dynamic features of floating wind turbines and farms as well as field data from a land-based experimental field site.