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Author ORCID Identifier
N/A
AccessType
Open Access Dissertation
Document Type
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.
DOI
https://doi.org/10.7275/8420396.0
Recommended Citation
Hao, Yujia, "Wind Farm Wake Modeling and Analysis of Wake Impacts in a Wind Farm" (2016). Doctoral Dissertations. 667.
https://doi.org/10.7275/8420396.0
https://scholarworks.umass.edu/dissertations_2/667
Included in
Computer-Aided Engineering and Design Commons, Energy Systems Commons, Numerical Analysis and Scientific Computing Commons, Theory and Algorithms Commons