Time Dependent CFD Analyses of Wind Quality in Complex

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					 Time Dependent CFD Analyses of
 Wind Quality in Complex Terrain

      Claude Abiven1, José M. L. M. Palma2 and Oisin Brady1




          Power, Scotland
(1) Natural
(2) FEUP/CEsA, Faculty of Engineering University of Porto, Portugal




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                    Centre for Wind Energy and Atmospheric Flows
Outline


   1.   Site overview
   2.   Wind characteristics        critical sectors
   3.   Steady state versus time dependent analyses
           •   300º winds
           •   0º winds
           •   180º winds
   4.   Conclusions




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                  Centre for Wind Energy and Atmospheric Flows
Site overview - topography



                                                     Highly complex topography

                                                     No trees

                                                     Three planned turbines




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          Centre for Wind Energy and Atmospheric Flows
Site overview – wind rose



                                                   One year dataset of 10-min
                                                   average measurements


                                                   140-day dataset of 1Hz wind
                                                   measurements

                                                   50 m mast




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          Centre for Wind Energy and Atmospheric Flows
CFD code

VENTOS® CFD code:

•              written by researchers from the university of Porto,
               Portugal
•              3D Reynolds-averaged Navier-Stokes CFD solver
•              κ-ε turbulence model
•              transport equation discretised by finite volume techniques

References
[1] Simulation of the Askervein flow. Part 1: Reynolds averaged Navier-Stokes equations (k-ε turbulence model).
    Boundary Layer Meteorology. V.107, 501-530, 2003.
[2] Linear and nonlinear models in wind resource assessment and wind turbine micro-siting in complex terrain.
    Journal of Wind Engineering and Industrial Aerodynamics. V. 96, 2308-2326, 2008.



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                                Centre for Wind Energy and Atmospheric Flows
Wind characteristics: critical sectors
                        Measured
                        Computed
                                             Values of turbulence intensity are
                                             large for sectors 0º, 180º, 300º


                                                 Values of veer are large for
                                                 sectors 0º, 150º, 300º


                                                  In-depth analysis of sectors
                                                 0º, 180º, 300º is carried out




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           Centre for Wind Energy and Atmospheric Flows
300º winds: steady state                                          wind direction
 Y




     Large values of veer are caused by                    This can be seen on the wind rose
               the topography


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                   Centre for Wind Energy and Atmospheric Flows
300º winds: steady state                             wind turbulence




                                                     High turbulence coincides
                                                     with flow divergence
                                                     at the channel outlet




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          Centre for Wind Energy and Atmospheric Flows
300º winds                                                power spectrum

   measured



                                          Measured and simulated peak
                                          positions are in good agreement
                                          T ≈ 1000s


   simulated                               Simulations can help us
                                          understand the reason for these
                                          peaks




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               Centre for Wind Energy and Atmospheric Flows
EOF analysis

EOF = Empirical Orthogonal Functions

Widely used in climate sciences

From a spatial variable evolving with time

         (i.e. map of wind speed as a function of time)

EOFs split the signal into spatial patterns of this variable associated with a time
series. Each pattern explains part of the variance of the original signal.

         (i.e. maps of wind speed high and lows and their evolution in time)



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                    Centre for Wind Energy and Atmospheric Flows
300º winds                                        EOF of wind speed



                                           The first EOF is associated with an
                                           oscillation of period ≈ 1000s
                                           followed by a steady state

                                           Most of the variability occurs at
                                           and downwind of the turbines

                                           High-lows are the sign of an
                                           oscillation




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             Centre for Wind Energy and Atmospheric Flows
300º winds                              frame by frame analysis




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             Centre for Wind Energy and Atmospheric Flows
0º winds: steady state                                     wind direction




                                                          A system of vortices forms
                                                          downwind of the hill




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           Centre for Wind Energy and Atmospheric Flows
0º winds                                                  power spectrum


   measured

                                          Measured and simulated peak
                                          positions are in good agreement
                                          T ≈ 1000s


                                           Simulations can help us
   simulated                              understand the reason for these
                                          peaks




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               Centre for Wind Energy and Atmospheric Flows
0º winds                              frame by frame analysis




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           Centre for Wind Energy and Atmospheric Flows
190º winds: steady state                                        wind direction




  The wind is forced around the hill                  This can be seen on the wind
    and appears as a wind from                                    rose
        direction 210 on site

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                 Centre for Wind Energy and Atmospheric Flows
150º winds: steady state                                        wind direction




  The wind is forced around the hill
                                                      This can be seen on the wind
    and appears as a wind from
                                                                  rose
        direction 90 on site


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                 Centre for Wind Energy and Atmospheric Flows
170º winds                                               power spectrum

  measured


                                         Measured and simulated peak
                                         positions agree reasonably well:
                                         100s < T < 300s


  simulated                               Simulations can help us
                                         understand the reason for these
                                         peaks




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              Centre for Wind Energy and Atmospheric Flows
170º winds                              frame by frame analysis




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             Centre for Wind Energy and Atmospheric Flows
Conclusions

1. Low wind occurrences are caused by nearby mountains, which divert
   the flow from its original direction.

2. Spectral analyses show the preferred time scales.

3. EOF and frame by frame analysis are used to relate the preferred
   time scale to a physical event.

4. The model is able to reproduce time-dependent phenomena in
   complex terrain, as measured by the met mast.

5. 10-min averaged data and conventional analysis hide important flow
   features that can impair the wind farm operation.



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                 Centre for Wind Energy and Atmospheric Flows