This document contains the design and operation principles for the wind turbine emulator (WTE) located in the Distributed Energy Technologies Laboratory (DETL) at Sandia National Laboratories (Sandia). The wind turbine emulator is a power hardware -in-the-loop (PHIL) representation of the research wind turbines located in Lubbock, Texas at the Sandia Scaled Wind Farm Technology (SWiFT) facility. This document describes installation and commissioning steps, and it provides references to component manuals and specifications.
This report documents the use of wind turbine inertial energy for the supply of two specific electric power grid services; system balancing and real power modulation to improve grid stability. Each service is developed to require zero net energy consumption. Grid stability was accomplished by modulating the real power output of the wind turbine at a frequency and phase associated with wide-area modes. System balancing was conducted using a grid frequency signal that was high-pass filtered to ensure zero net energy. Both services used Phasor Measurement Units (PMUs) as their primary source of system data in a feedforward control (for system balancing) and feedback control (for system stability).
The Scaled Wind Farm Technologies (SWiFT) facility operated by Sandia National Laboratories (SNL) has, in support of the Atmosphere to electrons (A2e) research program, acquired measurements of wind turbine wake dynamics under various atmospheric conditions and while interacting with a downstream wind turbine. SNL researchers, in collaboration with National Renewable Energy Laboratory (NREL) researchers, installed a customized LIDAR system created by the Technical University of Denmark (DTU) in one of the SWiFT wind turbines (Figure 1) and operated that turbine with intentional yaw-versus-winddirection misalignment to study the behavior of the turbine wake under numerous combinations of atmospheric conditions and turbine yaw offsets. The DTU-customized LIDAR provided detailed measurements of the wake’s shape and location at many distances downwind of the turbine (Figure 2). These measurements will benefit wind energy researchers looking to understand wind turbine wake behavior and improve modeling and simulation of wake dynamics, including the “wake steering” affect that is observed when turbine yaw offset is controlled. During the test campaign, two SWiFT wind turbines were operated at the same time to observe the influence of the turbines on each other as the wake of the upwind turbine was observed sweeping over and interacting with the downwind turbine.
The Scaled Wind Farm Technology (SWiFT) facility, operated by Sandia National Laboratories for the U.S. Department of Energy's Wind and Water Power Program, is a wind energy research site with multiple wind turbines scaled for the experimental study of wake dynamics, advanced rotor development, turbine control, and advanced sensing for production-scale wind farms. The SWiFT site currently includes three variable-speed, pitch-regulated, three-bladed wind turbines. The six volumes of this manual provide a detailed description of the SWiFT wind turbines, including their operation and user interfaces, electrical and mechanical systems, assembly and commissioning procedures, and safety systems.
This document describes the software development practice areas and processes which contribute to the ability of SWiFT software developers to provide quality software. These processes are designed to satisfy the requirements set forth by the Sandia Software Quality Assurance Program (SSQAP). APPROVALS SWiFT Software Quality Assurance Plan (SAND2016-0765) approved by: Department Manager SWiFT Site Lead Dave Minster (6121) Date Jonathan White (6121) Date SWiFT Controls Engineer Jonathan Berg (6121) Date CHANGE HISTORY Issue Date Originator(s) Description A 2016/01/27 Jon Berg (06121) Initial release of the SWiFT Software Quality Assurance Plan
A reduction in cost of energy from wind is anticipated when maximum allowable tip velocity is allowed to increase. Rotor torque decreases as tip velocity increases and rotor size and power rating are held constant. Reduction in rotor torque yields a lighter weight gearbox, a decrease in the turbine cost, and an increase in the capacity for the turbine to deliver cost competitive electricity. The high speed rotor incurs costs attributable to rotor aero-acoustics and system loads. The increased loads of high speed rotors drive the sizing and cost of other components in the system. Rotor, drivetrain, and tower designs at 80 m/s maximum tip velocity and 100 m/s maximum tip velocity are created to quantify these effects. Component costs, annualized energy production, and cost of energy are computed for each design to quantify the change in overall cost of energy resulting from the increase in turbine tip velocity. High fidelity physics based models rather than cost and scaling models are used to perform the work. Results provide a quantitative assessment of anticipated costs and benefits for high speed rotors. Finally, important lessons regarding full system optimization of wind turbines are documented.
This report documents the design, fabrication, and testing of the SMART Rotor. This work established hypothetical approaches for integrating active aerodynamic devices (AADs) into the wind turbine structure and controllers.
This report documents the data post-processing and analysis performed to date on the field test data. Results include the control capability of the trailing edge flaps, the combined structural and aerodynamic damping observed through application of step actuation with ensemble averaging, direct observation of time delays associated with aerodynamic response, and techniques for characterizing an operating turbine with active rotor control.
The preliminary design for a three-bladed cross-flow rotor for a reference marine hydrokinetic turbine is presented. A rotor performance design code is described, along with modifications to the code to allow prediction of blade support strut drag as well as interference between two counter-rotating rotors. The rotor is designed to operate in a reference site corresponding to a riverine environment. Basic rotor performance and rigid-body loads calculations are performed to size the rotor elements and select the operating speed range. The preliminary design is verified with a simple finite element model that provides estimates of bending stresses during operation. A concept for joining the blades and support struts is developed and analyzed with a separate finite element analysis. Rotor mass, production costs, and annual energy capture are estimated in order to allow calculations of system cost-of-energy. Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd Evaluation Only. Created with Aspose.Pdf.Kit. Copyright 2002-2011 Aspose Pty Ltd
Prior work on active aerodynamic load control (AALC) of wind turbine blades has demonstrated that appropriate use of this technology has the potential to yield significant reductions in blade loads, leading to a decrease in wind cost of energy. While the general concept of AALC is usually discussed in the context of multiple sensors and active control devices (such as flaps) distributed over the length of the blade, most work to date has been limited to consideration of a single control device per blade with very basic Proportional Derivative controllers, due to limitations in the aeroservoelastic codes used to perform turbine simulations. This work utilizes a new aeroservoelastic code developed at Delft University of Technology to model the NREL/Upwind 5 MW wind turbine to investigate the relative advantage of utilizing multiple-device AALC. System identification techniques are used to identify the frequencies and shapes of turbine vibration modes, and these are used with modern control techniques to develop both Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) LQR flap controllers. Comparison of simulation results with these controllers shows that the MIMO controller does yield some improvement over the SISO controller in fatigue load reduction, but additional improvement is possible with further refinement. In addition, a preliminary investigation shows that AALC has the potential to reduce off-axis gearbox loads, leading to reduced gearbox bearing fatigue damage and improved lifetimes.