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.

随着当前利用风力资源生产更高水平的电力的趋势，风力发电输出的不确定性和波动对电网运营，特别是所谓的发电调度运营提出了越来越大的挑战。发电调度是指根据预测的需求来调度传统的发电厂的输出，但是当风能成为主要的电力来源时，这变得困难。这是由于风作为一种资源的不可预测性。为了将风能无缝集成到电网中，必须改进风电场规模的风电输出建模，从几秒钟到一天。来自大气的风波动和由涡轮机-涡轮机相互作用引起的风波动的定量表征是准确预测风力输出的核心组成部分。即使电网运营商可以获得这样的预测，与增强的电力系统操作相关的好处既没有被充分理解也没有被利用。这个问题是可持续能源基础设施的一个根本问题，涉及到波动的风力发电纳入电网。本研究旨在开发基础知识和指导方针，以缩小大气流量和风电场电力输出之间的差距，并整合这种联系，以有效和可靠地运行电网。整体方法有可能使电网接受更高水平的风能渗透。它最终将有助于降低风力发电的成本，并帮助它成为国家可再生能源组合的一个有吸引力和可行的选择。该项目还将资助研究生和本科生的教育发展，并将努力向公众、风能工程界和K-12教育传播成果。该研究项目旨在开发一个整体框架，以缩小大气湍流和风电场电力输出之间的差距，提高电网运行效率。为了实现这一目标，一个跨学科的团队将协同他们的分析，实验和数值专业知识，以解决改善风电预测和电网运营的基本问题。高性能计算将用于表征和量化昼夜周期内发生的湍流动力学变化（即，24小时昼夜循环）以及它们在风电场水平调节功率波动的能力。此外，一个通用的方法，风力发电场功率输出参数化将开发占时间范围内的时间尺度（从秒到小时），沿着其方差和频谱结构的功率输出的变化。最先进的风力预测将被整合到电网设计先进的控制和操作工具中。最终目标是实现更高水平的风能，可以集成到电力系统中，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场功率输出的一般参数化，以及鲁棒和经济的频率控制设计。这项工作将整合风能系统、电网以及两者之间相关接口所涉及的物理过程，包括i）与大气稳定状态和昼夜周期相关的风电建模中的不确定性; ii）风电场规模的电力输出波动的短期和提前一小时预测; iii）使用风输出预测增强电网运营。UIUC和PSU的设施以及PI的各种专业知识为开展这项研究提供了理想的环境。