Collaborative Research: A Holistic Approach to Wind Energy Integration: From the Atmospheric Boundary Layer to the Power Grid

合作研究：风能整合的整体方法：从大气边界层到电网

• 批准号: 1610897
• 负责人: Leonardo Chamorro
• 金额: $ 26.75万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1610897&HistoricalAwards=false
• 关键词: Collaborative; Research; Holistic; Approach; Wind

With the current trends towards higher levels of electric power produced using wind resources, the uncertainties and fluctuations of wind power output are increasingly challenging power grid operations and especially the so-called generation dispatch operations. Generation dispatch refers to scheduling traditional power plant output based on predicted demand, but this becomes difficult when wind energy becomes a major source of electric power. This is due to the unpredictability of wind as a resource. To seamlessly integrate wind energy to the power grid, it is imperative to improve the modeling of wind power output at the scale of wind farms, from seconds up to a day ahead. The quantitative characterization of wind fluctuations from the atmosphere and those induced by turbine-turbine interactions is a central component towards accurately predicting wind power output. Even with such predictions available to grid operators, the benefits associated with enhanced power system operations have neither been fully understood nor exploited. This problem is a fundamental issue of sustainable energy infrastructure related to the integration of fluctuating wind power into the power grid. This research aims to develop fundamental knowledge and guidelines to close the gap between atmospheric flow and wind farm electric power output, and to integrate this linkage to efficiently and reliably operate power grids. The holistic approach has the potential to allow the electric power grid to embrace higher levels of wind energy penetration. It will ultimately aid in decreasing the cost of wind power and help it become an attractive and viable option for the nation's renewable energy portfolio. The project will also fund the educational development of both graduate and undergraduate students, and significant efforts will be made to disseminate the results to the general public, the wind energy engineering community, and to the K-12 education.The research project aims to develop a holistic framework to close the gap between atmospheric turbulence and wind farm electric power output to increase the efficiency of power grid operations. To achieve this goal, an interdisciplinary team will synergize their analytical, experimental, and numerical expertise to address the foundational problems of improving wind power prediction and power grid operations. High-performance computing will be used to characterize and quantify the variations of the turbulence dynamics occurring over the diurnal cycle (i.e., 24 hour day/night cycle) and their ability to modulate power fluctuations at the wind-farm level. Furthermore, a generic approach to wind-farm power output parametrization will be developed to account for temporal power output variability over a range of time scales (from seconds to hours), along its variance and spectral structure. The state-of-the-art wind power predictions will be integrated to design advanced control and operational tools for power grids. The ultimate goal is to achieve higher levels of wind energy that can be integrated to the electric power systems, and to contribute towards a future sustainable energy infrastructure. The potentially transformative aspects of the research include the development of a general parametrization of wind farm power output, and robust and economic frequency control designs. The work will integrate the physical processes involved in wind energy systems, the power grid and the associated interface between the two, including i) uncertainties in wind power modeling associated with the atmospheric stability state and diurnal cycle; ii) short-term and hourly-ahead forecasting of electrical power output fluctuations at the wind farm scale; and iii) enhancing power grid operations using the wind output prediction. The facilities at UIUC and PSU as well as the diverse expertise of the PIs provide an ideal environment for conducting this research.

随着目前使用风能资源产生的较高电力的趋势，风能输出的不确定性和波动越来越具有挑战性，越来越具有挑战性的功率电网操作，尤其是所谓的发电发动机操作。一代调度是指根据预测需求安排传统的发电厂产量，但是当风能成为电力的主要来源时，这变得困难。这是由于风的不可预测性作为资源。为了将风能无缝整合到电网，必须在风电场的规模上改善风能输出的建模，从秒到未来一天。从大气中的风波动和涡轮涡流相互作用引起的风波的定量表征是准确预测风能输出的核心组成部分。即使有了网格运营商可用的预测，与增强的功率系统操作相关的好处既没有被完全理解也没有得到利用。这个问题是可持续能源基础设施的一个基本问题，与将波动的风能整合到电网中有关。这项研究旨在开发基本的知识和准则，以缩小大气流量与风电源电力输出之间的差距，并将这种联系与有效，可靠地运行电网。整体方法有可能使电力电网采用更高水平的风能渗透。它最终将有助于降低风能的成本，并帮助它成为美国可再生能源投资组合的有吸引力和可行的选择。该项目还将为研究生和本科生的教育发展提供资金，并将为将结果传播给公众，风能工程社区以及K-12教育。该研究项目旨在开发一个整体框架，以弥合大气湍流与风场电力电力的差距，以提高电网电网运营效率。为了实现这一目标，跨学科团队将协同其分析，实验性和数值专业知识，以解决改善风能预测和电网操作的基本问题。高性能计算将用于表征和量化昼夜周期中发生的湍流动力学的变化（即24小时的白天/夜间周期）及其在风向电源水平上调节功率波动的能力。此外，将开发出一种通用的风向功率输出参数化的方法，以说明沿其差异和光谱结构的时间尺度（从秒到小时）上的时间功率输出可变性。最先进的风电预测将集成到设计电网的高级控制和操作工具。最终的目标是实现可以集成到电力系统的更高水平的风能，并为未来的可持续能源基础设施做出贡献。该研究的潜在变革方面包括开发风电源功率输出的一般参数，以及强大而经济的频率控制设计。这项工作将整合风能系统，功率电网和两者之间的相关界面所涉及的物理过程，包括i）与大气稳定性状态和昼夜周期相关的风能建模中的不确定性； ii）在风电场尺度上的短期和小时预测电力输出波动； iii）使用风输出预测增强电网操作。 UIUC和PSU的设施以及PI的各种专业知识为进行这项研究提供了理想的环境。