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

本项目旨在开发改进的控制策略，以帮助降低浮动海上风电场的能源成本。风力发电机组控制的主要目的是随着风环境的变化调节发电。然而，对于漂浮式风力发电场来说，最好利用风能的控制策略还有待研究。提高浮动式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。“风能愿景”的目标是到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水深超过60米的水域，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，包括改进公开可用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，这些课程的改进将更好地为缅因大学机械工程专业的毕业生提供STEM技能，以推进具有成本效益的海上风能生产。技术描述本项目的主要目标是通过综合数值模拟，制定、实施和量化集成多个输入和控制动作的先进浮式海上风力发电场控制方法的性能。这个项目将改进强大的开源计算机辅助工程工具FAST。农场模拟浮动风力涡轮机农场目前正在开发的国家可再生能源实验室。该工具对海上风电研究人员和设计师非常感兴趣，因为它功能强大，计算效率高，并允许对整个风电场进行分析。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螺距、发电机扭矩、机舱偏航和流-结构耦合控制体系结构，以寻求最大限度地获取能量，并将浮式风力发电场的结构负载最小化。将测试新的非线性模型预测控制（NMPC）方案，该方案结合了前馈激光雷达风测量和关键浮动平台自由度。这些NMPC技术将扩展到允许单个叶片控制，以最大限度地减少由风切变、大气湍流和机舱偏航误差引起的不对称转子负载。农场级别的尾流转向算法将得到加强，以解释由于平均环境负荷而导致的显著横向移动浮动风力涡轮机。本文还将研究采用现有船体水压载的低成本、主动流固耦合调谐质量系统对改善浮式风力发电机整体性能的影响。这项提议的研究最终将成为主动控制方法的先驱，这种方法可以显著降低浮动风力发电场的能源成本。该奖项反映了美国国家科学基金会的法定使命，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.