A comparative analysis of built environment and open terrain wind data by higher order statistics and performance evaluation of 5 kW HAWT using FAST
Small wind turbines (SWT) that are designed as per the IEC 61400-2 standard suffer structural and operational complexities when operating in the built environment, because such environments impose stochastic variations in wind speed and turbulence. The wind conditions in flat terrain of Östergarnsho...
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Veröffentlicht in: | Journal of physics. Conference series 2018-06, Vol.1037 (7), p.72022 |
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Sprache: | eng |
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Zusammenfassung: | Small wind turbines (SWT) that are designed as per the IEC 61400-2 standard suffer structural and operational complexities when operating in the built environment, because such environments impose stochastic variations in wind speed and turbulence. The wind conditions in flat terrain of Östergarnsholm (OG) Island, Sweden and built environment of Port Kennedy (PK), Australia are compared for turbulence intensity (TI) and intermittency. The TI of the PK wind field was 24% at mean wind speed of 15 m/s, which was higher than the Normal Turbulence Model (NTM) indicated in IEC 61400-2. The TI in the open terrain was below 18% for all mean wind speeds. Similarly, for three chosen wind speed bins within a SWT's operating range, the urban wind field had higher intermittency for smaller timescales but resulted in smaller intermittency as the time lag increased. The effect of these measured wind fields on the performance and loading of a turbine was studied at the three chosen wind speed bins using an aeroelastic model of a 5 kW SWT that was developed in FAST. The predicted output statistics using measured wind fields were compared with the assumed wind fields in the IEC 61400-2 standard. The rotor thrust and blade flapwise bending moment with PK wind data were higher than that of the IEC standard due to the increased turbulence in the inflowing wind indicating the inadequacy in the current wind standard applied for such SWTs for urban installations. |
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ISSN: | 1742-6588 1742-6596 |
DOI: | 10.1088/1742-6596/1037/7/072022 |