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Physics-Based Lidar Simulation and Wind Gust Detection and Impact Prediction for Wind Turbines


Abstract Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.

The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size d... (more)
Created Date 2019
Contributor Zhou, Kai (Author) / Calhoun, Ronald (Advisor) / Chen, Kangping (Committee member) / Tang, Wenbo (Committee member) / Peet, Yulia (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Subject Mechanical engineering / Electrical engineering / Fluid mechanics / Autonomous vehicle / Impact prediction / Physics-based Lidar / Simulation / Spatial wind gust
Type Doctoral Dissertation
Extent 286 pages
Language English
Copyright
Note Doctoral Dissertation Mechanical Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis