Analyzing Effects of Turbulence on Power Generation Using Wind Plant Monitoring Data: Preprint
In this paper, a methodology is developed to analyze how ambient and wake turbulence affects the power generation of a single wind turbine within an array of turbines. Using monitoring data from a wind power plant, we selected two sets of wind and power data for turbines on the edge of the wind plant that resemble (i) an out-of-wake scenario (i.e., when the turbine directly faces incoming winds) and (ii) an in-wake scenario (i.e., when the turbine is under the wake of other turbines). For each set of data, two surrogate models were then developed to represent the turbine power generation (i) as a function of the wind speed; and (ii) as a function of the wind speed and turbulence intensity. Support vector regression was adopted for the development of the surrogate models. Three types of uncertainties in the turbine power generation were also investigated: (i) the uncertainty in power generation with respect to the published/reported power curve, (ii) the uncertainty in power generation with respect to the estimated power response that accounts for only mean wind speed; and (iii) the uncertainty in power generation with respect to the estimated power response that accounts for both mean wind speed and turbulence intensity. Results show that (i) under the same wind conditions, the turbine generates different power between the in-wake and out-of-wake scenarios, (ii) a turbine generally produces more power under the in-wake scenario than under the out-of-wake scenario, (iii) the power generation is sensitive to turbulence intensity even when the wind speed is greater than the turbine rated speed, and (iv) there is relatively more uncertainty in the power generation under the in-wake scenario than under the out-of-wake scenario.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy Wind and Water Power Technologies Office
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1123216
- Report Number(s):
- NREL/CP-5D00-60989
- Resource Relation:
- Conference: To be presented at the AIAA Science and Technology Forum and Exposition, 13-17 January 2014, National Harbor, Maryland
- Country of Publication:
- United States
- Language:
- English
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