Abstract
The National Renewable Energy Laboratory’s 5-MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the 5-MW wind turbine uses a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into fast-paced development cycles, as systems engineering tools such as Wind-Plant Integrated System Design & Engineering Model (WISDEM ®) [1] are employed, and as a greater focus on controls co-design practices is encouraged, demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5-MW controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process while maintaining or improving the performance of the legacy NREL 5-MW controller.
Highlights
The National Renewable Energy Laboratory’s (NREL’s) 5-MW baseline wind turbine [2] has become ubiquitous in modern wind turbine research
Legacy NREL 5-MW controller We offer a brief overview of the legacy NREL 5-MW controller that is presented in [2]
A selection of time-domain simulation results is presented to provide some initial results of the performance of the generic controller as compared to the legacy NREL 5-MW controller
Summary
The National Renewable Energy Laboratory’s (NREL’s) 5-MW baseline wind turbine [2] has become ubiquitous in modern wind turbine research. We describe the necessary input parameters to the control algorithm and present some preliminary results of the controller performance as compared to the legacy NREL 5-MW controller The result of this is an open-source code base for generic controlling tuning. In order to define the linear gain schedule, the sensitivity of the aerodynamic power to the rotor-collective blade-pitch angle is necessary, and it is generally found through linearization routines available through aeroelastic design tools such as OpenFAST [7]. (1) does not offer any ability to tune the generator torque response characteristics For these reasons, we employ a wind speed estimator to implement a tip-speed ratio tracking generator torque PI controller in below-rated operation. In above-rated operation, the legacy blade pitch controller PI gain-schedule formulation necessitates a number of aeroelastic simulations to find wind turbine performance characteristics. A low-pass filter on the generator speed is employed with a corner frequency of one-third of the first edgewise natural frequency of the turbine blades
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