In wind resource-rich regions such as the U.S. Great Plains, wind energy development in recent years has increased at a brisk rate in recent years. Climatologically, this region is also where severe weather events such as thunderstorms are common; failures of wind turbines in recent events suggest a need for retrospective analysis and re-evaluation of design for associated transient inflow conditions. To meet the nation?s goals of 20% wind energy by 2030 more wind turbines will likely be sited in the Great Plains where failures in extreme weather events are expected; suggested climate change influences on the changing frequency and severity of such events exacerbates concerns about today?s turbine designs.
This project seeks to develop advanced mesoscale and large-eddy-simulation (LES) procedures for the generation of thunderstorm-related inflow wind fields, informed and validated by diverse data streams, so as to make possible safe design and assessment of future wind turbines.
This project is structured in four phases. In Phase 1, PIs will consider about 20 case studies representing severe weather events recorded in West Texas over the period, 2005-2012. A wide array of data sets for these events is available for validation of the 4-D mesoscale-LES inflow fields that will be developed. These flow fields will be employed in aeroelastic simulation of loads on single utility-scale wind turbine units as well as arrays. In Phase 2, PIs will assess the validity of ?engineering? simulation models based on older field campaigns (e.g., NIMROD and JAWS) against physics-based and data-driven mesoscale-LES models. The focus in Phase 3 of this project is on the development of low-dimensional representations of the inflow wind fields to be used to predict turbine loads accurately and efficiently. This will take coordination between the two collaborating researcher teams with complementary non-overlapping expertise. Consideration of turbine extreme and fatigue limit states over the long term will guide the low- dimensional model development. Finally, in Phase 4, PIs tackle the future projection component of this study. Armed with the inflow modeling from the previous phases, PIs address life-cycle performance of turbine units and arrays. Over a service life of 20 years, a turbine may be expected to experience several extreme weather events. For candidate Great Plains sites, PIs will examine anticipated load profiles on turbine components over the long term, taking into consideration changing climate effects (such as in changes in the frequency and severity of thunderstorms), informed by climate model data and with considerations for uncertainty. PIs expect, thus, to provide a picture of expected performance (and uncertainty on the same) of turbine units as they are considered in the context of failure against ultimate and fatigue limit states.
The students involved in the research effort will develop skills in statistical modeling, boundary layer meteorology, turbulence simulation, aeroelastic and structural analysis, and reliability-based design procedures for wind turbines against extreme and fatigue limit states. While these skills are not part of a typical curriculum, there is a dire need for trained engineers who can assist with analyses of the kind that will be developed in this project. Indeed, today, for advanced analysis, consulting assistance is routinely sought from Western Europe. The PIs will provide education and training/internship opportunities for graduate and undergraduate students of engineering and atmospheric sciences to serve this economically vibrant industry. Minority undergraduate students will be engaged as research assistants through the Texas Research EXperience (TREX) program. The National Renewable Energy Laboratory will provide summer internship opportunities for students, and collaboration opportunities in research between their engineers and the PIs and their students. K-12 student and teacher involvement in planned STEM learning is planned with the Science House program at North Carolina State University.
