A Revenue Optimizing Commercial Wind Turbine

一项创新研究计划旨在优化加拿大风能资产的盈利能力。该建议源于一个成功的实地研究项目，该项目现在包括来自温莎大学和安大略省西部大学的学生和研究人员。商业风力发电场是一项大型资本投资。风力涡轮机的维护成本通常很高，因为除了维修期间涡轮机停机的成本外，还包括维修/更换故障部件的成本(S)。商用风力涡轮机的使用寿命通常为20年，这取决于这些机器的老化程度，它们可能达到或超过这一预测门槛，而其他机器可能根本达不到。在所有情况下，随着这些机器接近其预期寿命，将要求重新认证它们的操作和结构完整性，以便能够投保。能够确定风力涡轮机是否因日常运行负荷或由于个别但极端的负荷事件(如强风切变、龙卷风或下击暴流)而遭受损坏，对风电场所有者来说将具有重要价值。了解机器的结构能力是否以及可能如何受到影响，可以使风电场运营商在更严重的、潜在的灾难性故障之前很好地进行维护。它还可能有助于确定如何操作机器，以在其使用寿命内优化收入产生。候选人和他的团队将利用温莎大学开发的不断发展的结构健康监测系统，跟踪在常规操作加载期间如何发生和积累损伤。这包括对涡轮机基础的监测，这是以前的研究没有全面解决的一个方面。为了模拟风切变、龙卷风和下击暴流等极端风事件对结构的影响，将开发一个50：1比例的气动弹性模型，用于在西安大略大学正在建设的WindEEE穹顶旋风测试设施中进行测试。这一多学科研究计划在空气动力学、结构力学和机器学习方面具有巨大的潜力。

An innovative research program is aimed at optimizing the profitability of wind energy assets in Canada. The proposal originates from a successful field research program that now includes students and researchers from both the Universities of Windsor and Western Ontario. Commercial wind farms are large capital investments. The cost of wind turbine maintenance is often significant as it is marked by the cost of service/replacement of the failed component(s) in addition to the cost of turbine downtime during the repairs. The commonly quoted service life of a commercial wind turbine is 20 years, depending on how these machines age, they may reach or exceed this predicted threshold while others may not make it at all. In all cases, as these machines approach their life expectancy it will be required that their operational and structural integrity be recertified in order to be insurable. The ability to determine if wind turbines have sustained damage due to everyday operational loading or due to isolated but extreme loading events like intense wind shears, tornados, or downbursts would be of significant value to a wind park owner. Understanding if, and potentially how, the structural capacity of a machine has been compromised can allow wind park operators to effect maintenance well in advance of more significant, potentially catastrophic failures. It may also help determine how to operate the machines to optimize revenue generation over their service life. The candidate and his team will utilize an evolving structural health monitoring system, developed at the University of Windsor, to track how damage occurs and accumulates during regular operational loading. This includes monitoring of the turbine foundation, an aspect that has not been comprehensively addressed by previous research. To simulate the structural impact of extreme wind events like wind shears, tornados, and downbursts, a 50:1 scaled aeroelastic model will be developed for testing in the WindEEE Dome swirling wind testing facility that is currently under construction at the University of Western Ontario. This multidisciplinary research program has great potential to yield discoveries in aerodynamics, structural mechanics, and machine learning.