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

风力涡轮机技术的进步和对风力发电潜力的重新评估导致了美国和世界范围内风能能力的迅速积累。已经有几个国家要求其电力需求的很大一部分由风力涡轮机产生。在传统上被认为风力资源太低而不能经济开采的地区，许多风力发电场项目正在开发中。在许多领域，风能现在比传统的能源生产方法成本更低。在选择风电场选址时，规划者依赖于区域风气候学(平均值和标准差)，该区域风气候学是从地表风速观测的统计插值法得出的，这些风速观测值不在涡轮机的高度，分布稀疏，质量可能有问题。当附近没有观测时，这种内插可能包含很大的误差，特别是在水域或复杂地形(通常是一些风力最大的地区)。因此，风电场选址方法在很大程度上是后发的，从气候角度来看，最好的选址可能会被忽视。传统统计方法的替代方法是使用区域数值气候模式(RCM)在精细的时间(小时)和空间(12公里)尺度上提供风速估计，并在风力涡轮机的高度而不是地面上这样做。因此，本文研究的主要目标是开发一个基于区域气候模型(RCM)的风电场选址地理信息系统(GIS)。这项研究将解决的关键问题是，RCM/GIS方法是否代表着对当前使用的统计技术(例如，空间内插、测量-关联-预测[MCP]、概率密度函数[pdf])的重大改进。这项研究将利用美国林业局运营的MM5 RCM的风速输出，用于北美五大湖地区的火灾天气分析。模型输出将根据该地区几个地面观测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提供比传统统计方法显著的改进。在验证后，RCM的输出将包括在地理信息系统中，并与其他风电场选址标准相结合，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确定一个地区的最佳风电场选址。在最初的模型开发和验证之后，这笔赠款将促进在另一个地区(英国)对RCM/GIS模型进行评估，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。这项将在东英吉利大学进行的评估还将为欧洲领先的风能研究人员提供一个机会，就这种模式是否适合不同的地区提供意见。这项研究致力于为风电场的最佳选址提供一种新的方法，使它们能够以最经济的方式运行，并将对社会和环境的破坏降至最低。它也代表了RCM在大气科学领域之外的一种新的实际用途。这类研究将突出区域气候模型在实际应用中的优势和局限性。此外，通过使用区域气候模式，可以有效地估计地表风观测稀少或缺乏的区域的风资源。这种能力将促进近海地区以及欠发达国家的风能项目的发展，这些国家将从独立能源基础设施的发展中受益匪浅。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。

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.