Doctoral Dissertation Research: A Regional Climate Model - Geographic Information System Approach To Wind Power Climatology

博士论文研究：区域气候模型 - 风电气候学地理信息系统方法

• 批准号: 0302469
• 负责人: Jeffrey Andresen
• 金额: $ 0.59万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2004-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0302469&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Regional; Climate

Advances in wind turbine technology and reassessments of wind power potential have resulted in a rapid buildup of wind energy capacity in the United States and worldwide. Already several nations have mandated that a substantial portion of their electricity needs be generated by wind turbines. Numerous wind farm projects are under development in regions where the wind power resource has traditionally been considered too low for economical extraction. Wind energy is now, in many areas, less costly than conventional energy production methods. In choosing wind farm sites, planners rely on a regional wind climatology (averages and standard deviations) derived from the statistical interpolation of surface wind speed observations that are not at the height of the turbine, are sparsely distributed, and may be of questionable quality. Such interpolations may contain a great deal of error when no nearby observations exist, especially over water or complex terrain (often some of the windiest regions). As a result, wind farm siting methodologies are largely post hoc and the best sites climatologically may be overlooked. An alternative to traditional statistical methods is the use of a regional numerical climate model (RCM) to provide estimates of wind speeds at a fine temporal (hourly) and spatial ( 12 km) scale, and do so at the height of the wind turbine, rather than the surface. Thus, the primary goal of this dissertation research is to develop a regional climate model (RCM) based geographic information system (GIS) for the purposes of wind farm siting. The key question this research will address is whether the RCM/GIS approach represents a significant improvement over currently employed statistical techniques (e.g., spatial interpolation, measure-correlate-predict [MCP], probability density functions [pdf]). The research will make use of the wind speed output of the MM5 RCM operated by the U.S. Forest Service for fire weather analysis over the Great Lakes region of North America. The model output will be validated against wind speed observation records at several surface stations throughout the region. It is expected that the RCM will provide a significant improvement over traditional statistical methods in the fine-resolution estimation of the regional wind resource. Upon validation, the output of the RCM will be included in a GIS and coupled with additional wind farm siting criteria to create a siting tool that will identify the optimal wind farm sites in a region based upon the considerations determined by a wind farm developer. After the initial model development and validation, this grant facilitates the evaluation of the RCM/GIS model over a different region (the UK) where wind energy development also is growing rapidly and a great deal of wind climate research already has been conducted. This evaluation, to take place at the University of East Anglia will also provide an opportunity for leading European wind energy researchers to provide input on the suitability of such a model to varied and diverse regions. This research endeavors to provide a new method for the optimal siting of wind farms such that they can operate most economically and with a minimum of disruption to society and the environment. It also represents a new and practical use for a RCM outside the realm of atmospheric science. Such research would highlight the strengths and limitations of utilizing regional climate models in practical applications. Additionally, through the use of a regional climate model the wind resource of regions where surface wind observations are sparse or lacking may be effectively estimated. Such ability would facilitate the development of wind energy projects in offshore locations as well as in less developed countries that would greatly benefit from the development of an independent energy infrastructure. Furthermore, as a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.

风力涡轮机技术的进步和风电潜力的重新评估导致美国和全球风能发电能力的迅速增强。已经有几个国家规定其大部分电力需要由风力涡轮机产生。许多风电场项目正在开发中，这些地区的风能资源传统上被认为太低而无法经济开采。现在，在许多领域，风能的成本低于传统能源生产方法。在选择风电场地点时，规划者依赖于区域风气候学（平均值和标准差），该区域风气候学是通过表面风速观测值的统计插值得出的，这些观测值不在涡轮机的高度，分布稀疏，并且质量可能存在问题。当附近不存在观测时，尤其是在水面或复杂地形（通常是一些风最大的地区）上，此类插值可能包含大量误差。因此，风电场选址方法在很大程度上是事后的，气候学上的最佳地点可能会被忽视。传统统计方法的替代方法是使用区域数值气候模型（RCM）来提供精细时间（每小时）和空间（12公里）尺度的风速估计，并在风力涡轮机的高度进行，而不是表面。因此，本论文研究的主要目标是开发基于区域气候模型（RCM）的地理信息系统（GIS），用于风电场选址。本研究将解决的关键问题是 RCM/GIS 方法是否代表着对当前使用的统计技术（例如空间插值、测量-相关-预测 [MCP]、概率密度函数 [pdf]）的显着改进。该研究将利用美国林务局运行的 MM5 RCM 的风速输出来对北美五大湖地区的火灾天气进行分析。模型输出将根据整个地区多个地面站的风速观测记录进行验证。预计RCM将在区域风资源的精细分辨率估计方面比传统统计方法提供显着改进。验证后，RCM 的输出将包含在 GIS 中，并与额外的风电场选址标准相结合，创建一个选址工具，该工具将根据风电场开发商确定的考虑因素确定某个地区的最佳风电场地点。在最初的模型开发和验证之后，这笔赠款促进了对不同地区（英国）的 RCM/GIS 模型的评估，该地区的风能开发也在迅速增长，并且已经进行了大量的风气候研究。这项评估将在东安格利亚大学进行，也将为欧洲领先的风能研究人员提供一个机会，就这种模型对不同地区的适用性提供意见。这项研究致力于为风电场的最佳选址提供一种新方法，使其能够最经济地运营，并对社会和环境造成的破坏最小化。它还代表了 RCM 在大气科学领域之外的新的实际用途。此类研究将突出在实际应用中利用区域气候模型的优势和局限性。此外，通过使用区域气候模型，可以有效地估计地面风观测稀疏或缺乏的地区的风资源。这种能力将促进近海地区以及欠发达国家风能项目的发展，这些国家将大大受益于独立能源基础设施的发展。此外，作为博士论文研究改进奖，该奖项还将为有前途的学生建立强大的独立研究生涯提供支持。