RII Track-4: Advanced Control Strategies for Floating Offshore Wind Farms

点击翻译按钮获取中文摘要

Nontechnical DescriptionThis project aims to develop improved controls strategies that can aid in reducing the cost of energy for floating offshore wind farms. The primary purpose of wind turbine controls is for regulating power production as the wind environment changes. However, control strategies that best harness wind energy for floating wind farms have yet to be investigated. Improving the cost-competitiveness of floating offshore wind turbine technology is essential for meeting the U.S. Department of Energy?s Wind Vision target of harnessing 86 GW of wind energy by 2050. In particular, nearly 60% of the U.S. offshore wind resource resides in water deeper than 60 meters, which requires floating, rather than fixed-bottom, wind turbine technology. This project will yield several important benefits, including improvements to publicly available floating wind turbine farm simulation tools and models that are used by numerous researchers in the U.S. and around the world. In addition, the curriculum for the University of Maine Mechanical Engineering program will be strengthened in the areas of control systems and renewable energy as a result this project. In turn, these curriculum enhancements will better prepare University of Maine mechanical engineering graduates with STEM skills needed to advance cost effective offshore wind energy production.Technical DescriptionThe primary goal of this project is to formulate, implement and quantify the performance of advanced floating wind offshore turbine farm control methodologies integrating multiple inputs and control actions through using comprehensive numerical simulations. This project will improve the powerful, open-source computer-aided-engineering tool FAST.Farm for the simulation of floating wind turbine farms currently being developed at the National Renewable Energy Laboratory. This tool is of high interest to offshore wind researchers and designers as it is robust, computationally efficient, and permits the analysis of entire wind farms. With this improved tool, the proposed research will explore several novel active wind turbine blade pitch, generator torque, nacelle yaw and fluid-structure coupling control architectures that seek to maximize energy capture and minimize structural loads for a floating wind farm. New nonlinear model predictive control (NMPC) schemes will be tested that incorporate feedforward LiDAR wind measurements and critical floating platform degrees of freedom. These NMPC techniques will be extended to permit individual blade control that minimize asymmetric rotor loading resulting from wind shear, atmospheric turbulence and nacelle yaw error. Farm-level wake steering algorithms will be enhanced to account for the significant lateral movement floating wind turbines can undergo due to mean environmental loads. The influence of low-cost, active fluid-structure coupling tuned mass systems employing existing hull water ballast on the improvements in floating wind turbine global performance will also be investigated. The proposed research will ultimately pioneer active control methodologies that can significantly reduce the cost of energy for a floating wind farm.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.