wind energy resource evaluation in a site of central italy ... - WindSim

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Tables 6.12 and 6.13 summarize the calculation of the RMS errors relative to thecross-checking procedure conducted by speed-up and reported in the figures 6.9and 6.10.Table 6.12: RMS errors for period April-May.Table 6.13: RMS errors for period November-December.The results of the cross checking by speed-up instead of mean wind velocityconfirmed the results of the previous analysis. The period April-May was still betterreproduced by CFD calculations and the best dataset was the one at station 5424 at15 meters height. Moreover, the sector interpolation option was found to be helpful117
to have a better agreement during the period April-May, while in the periodNovember-December CFD results show worst match against experimental data.It must be noticed also that the sector interpolation function does not influence in astrong way the total error (shown in tables 6.12 and 6.13), which keeps the sameorder of magnitude both in cases April-May and November-December.6.8 RemarksA CFD simulation of the windfield of a site in central Italy was carried out. Thechosen parameters to build the geometrical grid and to set the solver settings werechosen to reach a sufficient accuracy level without any divergence problem.The velocity vertical profiles were studied and the agreement between CFD andexperimental data was correct only in the dominant sectors where thermal effectswere reduced.Turbulence intensity was also studied, showing that the WindSim codeunderestimates the experimental data and that turbulence intensity level is stronglyinfluenced by seasonal thermal effects.The cross checking of the experimental data collected by the two mastsmeasurement was finally performed. The best wind dataset in predicting windexperimental data was found in station 5424 at 15 meters height,The “sector interpolation” option [4] was tested, demonstrating that it can behelpful in some case to find a better agreement between experimental and CFDdata.118
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UNIVERSITÀ DEGLI STUDI DI CAGLIARI
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IndexIndex page IAcknowledgmentsVII
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CHAPTER 4: Characteristics of the s
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6.7.1 Mean wind velocity page 1096.
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This thesis is the result of a prac
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WindSim is a software developed by
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CHAPTER 1. Atmospheric Boundary Lay
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Figure 1.1: Example of an atmospher
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1.5 The WindSim numerical codeWindS
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(κ−ε RNG or the Low Reynolds),
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1.5.4 RESULTSThe Results module all
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Figure 1.2: Example of TKE vertical
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CHAPTER 2. Simulations over flat te
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inlet position (0 meters), station
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2.4 Height distribution factor sens
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e decreased, to avoid to build thin
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Figure 2.10: Vertical profiles for
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CHAPTER 3. Simulations over 2D hill
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Table 3.1: Measurement coordinatesS
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The results shown above demonstrate
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Figure 3.6: Sketch of the 15 km lon
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Figure 3.9: Influence of the height
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Figure 3.13: Zoom of the hill top r
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3.5.2) = ∙.The two models for att
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H [m] hill heightν[m 2 /s] air cin
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Figure 3.18: Particular of the nume
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Finally, the horizontal x velocity
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Figure 3.25: Z velocity componentFi
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3.6 RemarksA CFD study of a boundar
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Some experimental wind data of this
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Both the pictures 4.3 and 4.4 have
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Table 4.2: Description of the color
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In this periods, data are recorded
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In the following pages, a short des
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4.3.2 Mast 5424-15 m Period April-M
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4.3.4 Mast 5424-15 m Period Novembe
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4.3.6 Mast 5428-40 m Period April-M
Page 75 and 76: 4.3.8 Mast 5428-50 m Period Novembe
Page 77 and 78: 4.3.10 Mast 5428-30 m Period Novemb
Page 79 and 80: 4.4.2 Mast 542870
Page 81 and 82: 4.5.2 Mast 542872
Page 83 and 84: CHAPTER 5. Test of the Free Stream
Page 85 and 86: case the wind is blowing from the e
Page 87 and 88: Geometrical modelTable 5.3: Input p
Page 89 and 90: Figure 5.6: Vertical profiles in po
Page 91 and 92: The orthogonalization of the grid h
Page 93 and 94: Figure 5.9: Map of speed-ups for di
Page 95 and 96: Figure 5.30: Speed-2D at 30 m heigh
Page 97 and 98: Figure 5.12: Speed-2D at 30 m heigh
Page 99 and 100: CHAPTER 6. Analysis of the wind fie
Page 101 and 102: Table 6.2: Boundary conditions and
Page 103 and 104: 6.5 Vertical profiles of VelocityTo
Page 105 and 106: characterized by high wind speed (5
Page 107 and 108: From the error analysis, it is foun
Page 109 and 110: Anyhow, the trend of the linear int
Page 111 and 112: Concerning the CFD simulations, val
Page 113 and 114: Analyzing RMS error table for tower
Page 115 and 116: A general overview of the figure 6.
Page 117 and 118: 6.7 Cross Checking of wind dataIn t
Page 119 and 120: Figure 6.8 a/bFigure 6.8 c/dFigure
Page 121 and 122: Table 6.11: RMS error for cross che
Page 123 and 124: Figure 6.9 e/fFigure 6.9 g/hFigure
Page 125: Figure 6.10 g/hFigure 6.10 i/lFigur
Page 129 and 130: Figure 7.2: Weibull fitting of the
Page 131 and 132: Figure 7.5: Perspective view of the
Page 133 and 134: The calculated AEP has been reporte
Page 135 and 136: ConclusionsIn this thesis the evalu
Page 137 and 138: Bibliography[1] CRASTO G. - Numeric
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