Model-Based Simulation of Wind Turbine Inflow Turbulence and Design Loads: An Integrative Plan for Research and Learning, CMS 0449128
PI: Lance Manuel, University of Texas, Austin
An understanding of the spatial structure of the three-dimensional inflow wind velocity field is important for the safe design of wind turbines. Current attempts at characterizing this inflow turbulence in design guidelines are overly conservative and have not been developed following field studies of turbine performance and simultaneous recording of associated wind conditions (because such tests are expensive). Also, today's guidelines recommend design loads based on inflow coherence spectral models that have been shown to be inconsistent with measurements, especially for spatial separations on the order of rotor diameters and smaller. Moreover, the design guidelines do not employ turbine aerodynamic and structural dynamic response simulations of sufficiently long durations to match the desired return periods (on the order of 20 years) typical for ultimate and fatigue limit states. Clearly, there is a need for more field test programs and efficient modeling procedures to accurately describe the inflow and turbine response so as to arrive at more accurate design loads. Intellectual Merit The proposed career development plan addresses each of the issues raised. First, it offers a novel untried approach to characterizing the inflow turbulence random field by extracting spatially preferred "modes" that describe the inflow using empirical orthogonal decomposition of wind velocity statistics and spectra derived directly from newly available field measurements. Second, it offers an efficient procedure to make more realistic the possibility of carrying out long-duration aerodynamic simulations for turbine response while utilizing the decomposition of the inflow structure. Finally, it proposes a framework, based on structural reliability and response surface concepts, for deriving design loads by combining inflow characterization with turbine response statistics conditional on inflow. The proposed plan blends the use of extensive field data with simulation studies in addressing an important problem that could lead to more economical wind turbine designs and sustain the continued harvesting of wind as a renewable energy source. To summarize, at the heart of the proposed research plan are, in order, the following tasks: (i) development of efficient modeling techniques for characterizing the random spatial structure of wind inflow using field data - this will yield principal orthogonal preferred spatial "modes" that optimally describe the wind field; (ii) characterizing turbine response for the preferred spatial turbulence modes identified in (i) using turbine aerodynamic simulations; and (iii) establishing a probabilistic (structural reliability-based) framework that integrates (i) and (ii) to permit derivation of design ultimate and fatigue loads using simulations long enough to realistically reflect return periods on the order of 20 years. Research, education, and outreach activities that relate to this plan are outlined in this proposal. Broader Impacts An important point that needs to be made is that despite the tremendous growth in wind energy in the U.S., our nation is seriously short of trained engineers in this field and routinely has to seek technical/consulting assistance from Western Europe. This needs to change, and this career development plan will present some ideas the PI has to provide such training opportunities to our undergraduate and graduate students including internship opportunities that will be facilitated by this plan, K-12 involvement, and curriculum enhancements that the PI has planned. This research study will, it is expected, offer a learning experience as well for individuals of various backgrounds: graduate and undergraduate research assistants, middle/high students and teachers, and university students in the PI's undergraduate engineering statistics course and in a planned graduate wind engineering course. Details related to these activities are outlined in this proposal. Two significant entities that have expressed their support for the success of this plan include (a) Sandia National Laboratories, who will provide the field data for the efforts outlined and will also provide summer research internship positions to five undergraduate minority students; and (b) the PI's institution's Equal Opportunity in Engineering (EOE) program, who will facilitate the involvement of an underrepresented/minority student in this research. Letters of commitment from both these organizations are included in the "Supplementary Documents" section of this proposal outlining their support.
