Passive Acoustic Detection of Wind Turbine In-Flow Conditions for Active Control and Optimization
Wind is a significant source of energy; however, the human capability to produce electrical energy still has many hurdles to overcome. One of these is the unpredictability of the winds in the atmospheric boundary layer (ABL). The ABL is highly turbulent in both stable and unstable conditions (based on the vertical temperature profile) and the resulting fluctuations can have a dramatic impact on wind turbine operation. Any method by which these fluctuations could be observed, estimated, or predicted could provide a benefit to the wind energy industry as a whole. Based on the fundamental coupling of velocity fluctuations to pressure fluctuations in the nearly incompressible flow in the ABL, This work hypothesizes that a ground-based array of infrasonic pressure transducers could be employed to estimate the vertical wind profile over a height relevant for wind turbines. To analyze this hypothesis, experiments and field deployments were conducted. Wind tunnel experiments were performed for a thick turbulent boundary layer over a neutral or heated surface. Surface pressure and velocity probe measurements were acquired simultaneously. Two field deployments yielded surface pressure data from a 49 element array. The second deployment at the Reese Technology Center in Lubbock, TX, also included data from a smaller aperture, 96-element array and a 200-meter tall meteorological tower. Analysis of the data successfully demonstrated the ability to estimate the vertical velocity profile using coherence data from the pressure array. Also, dynamical systems analysis methods were successful in identifying and tracking a gust type event. In addition to the passive acoustic profiling method, this program also investigated a rapid response Doppler SODAR system, the optimization of wind turbine blades for enhanced power with reduced aeroacoustic noise production, and the implementation of a wireless health monitoring system for the wind turbine blades. Each of these other objectives was met successfully. The use of phase unwrapping applied to SODAR data was found to yield reasonable results for per-pulse measurements. A health monitoring system design analysis was able to demonstrate the ability to use a very small number of sensors to monitor blade health based on the blade's overall structural modes. Most notable was the development of a multi-objective optimization methodology that successfully yielded an aerodynamic blade design that produces greater power output with reduced aerodynamic loading noise. This optimization method could be significant for future design work.
- Research Organization:
- University of Mississippi, University, MS
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE)
- DOE Contract Number:
- EE0003269
- OSTI ID:
- 1037463
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
ACOUSTIC DETECTION
ACOUSTICS
AERODYNAMICS
BOUNDARY LAYERS
DESIGN
FLUCTUATIONS
HYPOTHESIS
IMPLEMENTATION
INCOMPRESSIBLE FLOW
MONITORING
MONITORS
OPTIMIZATION
PROBES
SENSORS
SYSTEMS ANALYSIS
TRANSDUCERS
VELOCITY
WIND TUNNELS
WIND TURBINES
passive acoustic detection
wind turbine in-flow conditions
turbine health monitoring
turbine design optimization
turbine noise reduction