Thesis
Wind farm wake modeling for power prediction and detection of wildlife activity using X-band Doppler radar
University of Iowa
Master of Science (MS), University of Iowa
Spring 2020
DOI: 10.17077/etd.005378
Abstract
The purpose of this research is to advance wind farm wake modeling and improve research techniques for understanding and mitigating impacts to bats due to wind farm development. Bat fatalities associated with wind turbines are an increasing concern with the widespread development of wind energy. Until now, research has focused on using biometrical and statistical techniques involving acoustic detection of bat activity and carcass surveys to develop mitigation strategies. However, there is an urgent need to develop and improve systematic strategies for smart wind turbine curtailment to mitigate bat fatalities while minimizing power loss. Unlike the perspective of biometricians that focus on bat habitat and post construction mortality surveys to evaluate impacts, the present study is motivated by the hypothesis that wind farms modify bat activity due to turbine wakes causing variations in wind speed within and around wind farms. Based on carcass survey evidence and wind farm operational characteristics, a model is proposed to describe the extent of low wind speed regions behind turbines in wind farms, that may provide preferable pathways for bats to fly when ambient wind speed is greater than the curtailment limit, where bats typically fly. To investigate the hypothesis further and detect bat activity within wind farms, a new approach is developed utilizing Doppler radar.
A calibration procedure for wind farm wake modeling using a simple analytical approach and wind turbine operational data was developed to improve the identification of low wind speed regions preferable for bat activity. The proposed procedure uses a Gaussian-based analytical wake model and wake superposition model. The wake growth rate varies across the wind farm based on the local streamwise turbulence intensity. The wake model was calibrated by implementing the proposed procedure with turbine pairs across the wind farm. The performance of the proposed procedure was validated at an onshore wind farm in central Iowa, USA. The results were compared with the industry standard wind farm wake model and have shown a higher prediction accuracy in sitewide wind speed and power prediction. This new SCADA-based calibration procedure can be used to identify potential low-wind habitat for bats in the wake of wind turbines and for wind farm operational optimization. Together, along with bat activity monitoring, this framework can provide a useful tool for real-time wind farm control and smart curtailment.
In order to study bat activity and their interaction with wind turbines and to investigate the feasibility of using Doppler radar for bat detection at a large wind farm, a bat detection experiment was conducted during the fall migration period within a wind farm in Iowa, USA. An X-band polarimetric Doppler radar was deployed to scan the entire wind farm and surrounding area up to 16 km. The results show the potential of X-band radar for detecting bat activity levels at a wind farm using the change in radar reflectivity and Doppler velocity information. The results can provide guidance to develop carcass survey strategies and improve understanding of bat activity within a wind farm.
Details
- Title: Subtitle
- Wind farm wake modeling for power prediction and detection of wildlife activity using X-band Doppler radar
- Creators
- Jian Teng
- Contributors
- Corey Markfort (Advisor)Anton Kruger (Committee Member)James Buchholz (Committee Member)
- Resource Type
- Thesis
- Degree Awarded
- Master of Science (MS), University of Iowa
- Degree in
- Mechanical Engineering
- Date degree season
- Spring 2020
- DOI
- 10.17077/etd.005378
- Publisher
- University of Iowa
- Number of pages
- xiii, 71 pages
- Copyright
- Copyright 2020 Jian Teng
- Language
- English
- Description illustrations
- color illustrations
- Description bibliographic
- Includes bibliographical references (pages 57-59).
- Public Abstract (ETD)
Bats, an indispensable part of ecosystems, are at risk due to collisions with wind turbine blades. Wind energy development is closely regulated to minimize risk of mortality for threatened and endangered bat species. There is a critical need for strategies that reduce risk of bat fatality and minimize power loss due to wind farm curtailment.
This study is motivated by the hypothesis that wind farms modify bat activity due to turbine wakes which reduce wind speed and cause variations in wind speed within and around wind farms. To investigate the hypothesis further and provide a tool for understanding wind variation within the wind farm, a calibration procedure is developed for wind farm wake modeling. The proposed procedure uses a simple analytical approach with real-time wind turbine operational data to determine the wind speed variation. This new procedure can be used for identifying potential bat habitat and for wind farm operational optimization. Together, along with bat activity monitoring, this framework can provide a useful tool for real-time wind farm control and smart curtailment.
To study bat activity around wind turbines and to investigate the feasibility of using Doppler radar for bat detection at wind farms, an experiment was conducted during the fall migration period within a wind farm in Iowa. Doppler radar is demonstrated to be a viable method to detect bat activity level using its signal strength and velocity information. The development of radar detection can improve survey strategies and advance understanding of bat activity within a wind farm.
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9983949492102771
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