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

非技术性描述本项目旨在开发改进的控制策略，以帮助降低海上浮动风电场的能源成本。 风力涡轮机控制的主要目的是随着风力环境的变化来调节功率产生。 然而，控制策略，最好地利用风能的浮动风力发电场还有待研究。 提高浮动海上风力涡轮机技术的成本竞争力对于满足美国能源部的要求至关重要。的风能愿景目标是到2050年利用86吉瓦的风能。 特别是，近60%的美国海上风力资源位于60米以上的水中，这需要浮动而不是固定底部的风力涡轮机技术。 该项目将产生几个重要的好处，包括改进公开的浮动风力涡轮机农场模拟工具和模型，这些工具和模型被美国和世界各地的许多研究人员使用。 此外，缅因州大学机械工程专业的课程将在控制系统和可再生能源领域得到加强。 反过来，这些课程的增强将更好地准备缅因州机械工程大学的毕业生与STEM技能需要推进成本效益的海上风能production.Technical DescriptionThe主要目标，这个项目是制定，实施和量化的性能先进的浮动风力海上涡轮机农场控制方法集成多个输入和控制行动，通过使用全面的数值模拟。 该项目将改进目前正在国家可再生能源实验室开发的用于模拟浮动风力涡轮机农场的强大的开源计算机辅助工程工具FAST.Farm。 该工具对海上风电研究人员和设计人员非常感兴趣，因为它强大，计算效率高，并允许分析整个风电场。 有了这个改进的工具，拟议的研究将探索几种新的主动风力涡轮机叶片桨距，发电机扭矩，机舱偏航和流体结构耦合控制架构，寻求最大限度地提高能量捕获和最小化结构载荷的浮动风电场。 新的非线性模型预测控制（NMPC）方案将进行测试，其中包括前馈激光雷达风测量和关键浮动平台自由度。 这些NMPC技术将被扩展到允许单个叶片控制，以最大限度地减少风切变、大气湍流和机舱偏航误差引起的不对称转子载荷。 农场级尾流转向算法将得到增强，以考虑到浮动风力涡轮机由于平均环境载荷而可能经历的显著横向运动。 还将研究采用现有船体压载水的低成本、主动流体-结构耦合调谐质量系统对改进浮动风力涡轮机整体性能的影响。 该研究计划最终将成为主动控制方法的先驱，可以显著降低浮动风电场的能源成本。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.