Publications

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Wind turbine loads predictions by blade-element momentum theory using the standard tip-loss correction have been shown to over-predict loading near the blade tip in comparison to experimental data. This over-prediction is theorized to be due to the assumption of light rotor loading, inherent in the standard tip-loss correction model of Glauert. A higher- order free-wake method, WindDVE, is used to compute the rollup process of the trailing vortex sheets downstream of wind turbine blades. Results obtained serve an exact correction function to the Glauert tip correction used in blade-element momentum methods. It is found that accounting for the effects of tip vortex rollup within the Glauert tip correction indeed results in improved prediction of blade tip loads computed by blade-element momentum methods.

Leading edge erosion and roughness accumulation is an issue observed with great variability by wind plant operators, but with little understanding of the effect on wind turbine performance. In wind tunnels, airfoil models are typically tested with standard grit roughness and trip tape to simulate the effects of roughness and erosion observed in field operation, but there is a lack of established relation between field measurements and wind tunnel test conditions. A research collaboration between lab, academic, and industry partners has sought to establish a method to estimate the effect of erosion in wind turbine blades that correlates to roughness and erosion measured in the field. Measurements of roughness and erosion were taken off of operational utility wind turbine blades using a profilometer. The field measurements were statistically reproduced in the wind tunnel on representative tip and midspan airfoils. Simultaneously, a computational model was developed and calibrated to capture the effect of roughness and erosion on airfoil transition and performance characteristics. The results indicate that the effects of field roughness fall between clean airfoil performance and the effects of transition tape. Severe leading edge erosion can cause detrimental performance effects beyond standard roughness. The results also indicate that a heavily eroded wind turbine blade can reduce annual energy production by over 5% for a utility scale wind turbine.

Wind turbine loads predictions by blade-element momentum theory using the standard tip-loss correction have been shown to over-predict loading near the blade tip in comparison to experimental data. This over-prediction is theorized to be due to the assumption of light rotor loading, inherent in the standard tip-loss correction model of Glauert. A higher- order free-wake method, WindDVE, is used to compute the rollup process of the trailing vortex sheets downstream of wind turbine blades. Results obtained serve an exact correction function to the Glauert tip correction used in blade-element momentum methods. Lastly, it is found that accounting for the effects of tip vortex rollup within the Glauert tip correction indeed results in improved prediction of blade tip loads computed by blade-element momentum methods.

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The total energy produced by a wind farm depends on the complex interaction of many wind turbines operating in proximity with the turbulent atmosphere. Sometimes, the unsteady forces associated with wind negatively influence power production, causing damage and increasing the cost of producing energy associated with wind power. Wakes and the motion of air generated by rotating blades need to be better understood. Predicting wakes and other wind forces could lead to more effective wind turbine designs and farm layouts, thereby reducing the cost of energy, allowing the United States to increase the installed capacity of wind energy. The Wind Energy Technologies Department at Sandia has collaborated with the University of Minnesota to simulate the interaction of multiple wind turbines. By combining the validated, large-eddy simulation code with Sandia’s HPC capability, this consortium has improved its ability to predict unsteady forces and the electrical power generated by an array of wind turbines. The array of wind turbines simulated were specifically those at the Sandia Scaled Wind Farm Testbed (SWiFT) site which aided the design of new wind turbine blades being manufactured as part of the National Rotor Testbed project with the Department of Energy.

A Verification and Validation (V&V) framework is presented for the development and execution of coordinated modeling and experimental program s to assess the predictive capability of computational models of complex systems through focused, well structured, and formal processes.The elements of the framework are based on established V&V methodology developed by various organizations including the Department of Energy, National Aeronautics and Space Administration, the American Institute of Aeronautics and Astronautics, and the American Society of Mechanical Engineers. Four main topics are addressed: 1) Program planning based on expert elicitation of the modeling physics requirements, 2) experimental design for model assessment, 3) uncertainty quantification for experimental observations and computational model simulations, and 4) assessment of the model predictive capability. The audience for this document includes program planners, modelers, experimentalist, V &V specialist, and customers of the modeling results.

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Rotor design and analysis work has been performed to support the conceptualization of a wind tunnel test focused on studying wake dynamics. This wind tunnel test would serve as part of a larger model validation campaign that is part of the Department of Energy Wind and Water Power Program’s Atmosphere to electrons (A2e) initiative. The first phase of this effort was directed towards designing a functionally scaled rotor based on the same design process and target full-scale turbine used for new rotors for the DOE/SNL SWiFT site. The second phase focused on assessing the capabilities of an already available rotor, the G1, designed and built by researchers at the Technical University of München.

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The objective of this document is to accurately predict, assess and optimize wind plant performance utilizing High Performance Modeling (HPC) tools developed in a community-based, open-source simulation environment to understand and accurately predict the fundamental physics and complex flows of the atmospheric boundary layer, interaction with the wind plant, as well as the response of individual turbines to the complex flows within that plant

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