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力电势的重新评估导致了美国和全球风能的迅速积累。已经有几个国家要求风力涡轮机产生大量的电力需求。在传统上认为风能资源太低而无法进行经济提取的地区，许多风电场项目正在开发中。现在，在许多领域，风能的成本少于传统的能源生产方法。在选择风电场地点时，规划人员依靠区域风气候（平均值和标准偏差），这些区域气候源自未在涡轮机高峰的地面风速观察的统计插值，稀疏分布，质量可疑。当不存在附近的观测值时，尤其是在水或复杂的地形上（通常是一些最风的地区），这种插值可能包含很大的错误。结果，风电场选址方法在很大程度上是事后事后，并且在气候上最好的地点可能会被忽略。传统统计方法的一种替代方法是使用区域数值气候模型（RCM）在良好的时间（每小时）和空间（12 km）尺度上提供风速估算，并在风力涡轮机的高度上进行，而不是表面。因此，本论文研究的主要目的是为了风场选址而开发基于区域气候模型（RCM）的地理信息系统（GIS）。这项研究将解决的关键问题是，RCM/GIS方法是否代表了当前使用的统计技术的显着改善（例如，空间插值，测量 - 可及性预测[MCP]，概率密度函数[PDF]）。这项研究将利用美国森林服务局在北美大湖地区开展的MM5 RCM的风速输出。该模型输出将在整个地区的几个水面站的风速观察记录中进行验证。预计RCM将在区域风资源的精细分辨率估计中对传统统计方法提供显着改善。经过验证后，RCM的输出将包括在GIS中，并加上其他风电场选址标准，以创建一个选址工具，该工具将根据风电场开发商确定的考虑因素来识别该地区的最佳风电场站点。在最初的模型开发和验证之后，该赠款促进了对不同地区（英国）的RCM/GIS模型的评估，在此，风能开发也正在迅速增长，并且已经进行了大量风气候研究。这项评估是在东英吉利大学进行的，还将为领先的欧洲风能研究人员提供一个机会，以提供有关这种模型对多样化和多样化地区的适用性的意见。这项研究努力提供了一种新方法，以最佳的地位，以便它们可以在经济上最大程度地运作，并且对社会和环境的干扰最少。它也代表了大气科学领域之外的RCM的新用途。这样的研究将突出使用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，可以有效地估计地表风观测到稀疏或缺乏的区域的风资源。这种能力将促进海上场所以及较不发达国家的风能项目的发展，这些国家将从独立的能源基础设施的发展中受益匪浅。此外，作为博士学位论文研究改进奖，该奖项还将提供支持，以使有前途的学生能够建立强大的独立研究职业。