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Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Mechanical Engineering

Year Degree Awarded

2016

Month Degree Awarded

May

First Advisor

Matthew Lackner

Second Advisor

Blair Perot

Third Advisor

Sanjay Arwade

Subject Categories

Computer-Aided Engineering and Design | Energy Systems | Numerical Analysis and Scientific Computing | Theory and Algorithms

Abstract

More and more wind turbines have been grouped in the same location during the last decades to take the advantage of profitable wind resources and reduced maintenance cost. However wind turbines located in a wind farm are subject to a wind field that is substantially modified compared to the ambient wind field due to wake effects. The wake results in a reduced power production, increased load variation on the waked turbine, and reduced wake farm efficiency. Therefore the wake has long been an important concern for the wind farm installation, maintenance, and control. Thus a wake simulation tool is required. Due to the temporal and spatial variability of wind speed, direction, turbulence, and atmospheric stability, it becomes very challenging to accurately estimate the wake profile and the power losses due to the wake. The current tools that are used to model the wake are either not accurate enough or require too much computation time. This research creates and develops superior approaches to the traditional wind farm wake analysis tool. Three major contributions are presented: creation and utilization of a wind farm wake model that accurately and efficiently addresses the wake effects in an arbitrary wind farm with arbitrary inflow condition, new versatile statistical and efficient approaches for the meandered wake center modeling, and new technical approaches to model the dynamic wake effects of both onshore and floating wind turbines that could be further developed for control needs. These new modeling approaches and technical strategies are unified into a comprehensive Wind Farm Modeling Program (WFMP). With the incorporation of FAST, WFMP provides a unified, flexible, and efficient approach for wind farm efficiency estimation and turbine loads assessment. In addition it enables several other analysis, such as mooring dynamics analysis and hydro-elastic analysis of waked offshore wind turbines, both of which were not able to be performed until WFMP is created. WFMP can drastically improve wind farm design, modeling, and control.

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