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

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The characteristics of the relation between wind speed U30 and RMS errors onmean wind speed are summarized in figure 6.4. It can be stated that errorscalculated for tower 5428 are lower than those calculated for tower 5424. The factcould be related to the height of the three measurement stations of the tower 5428(30-40-50 m) respect to the stations of tower 5424 (15-30m). Measurements closeto the ground are difficult to predict due to the complex orographic effects.Figure 6.4: Relation between RMS errors and sector wind speed.Moreover, a general trend for RMS errors can be underlined in the graph, showingthat errors become lower when wind speed U30 is becoming higher. Again, this factis related to the importance of thermal effects, that decreases in presence of a highwind speed.99
Anyhow, the trend of the linear interpolation is different according to themeasurement period. Thermal effects are different along the year, due to solarradiation and thermal inertia of the terrain, inducing different wind breezes in the allarea.Finally, it must be noticed that in the tower 5424 for the period November-December there is the best alignment of the data, while in the period April-May themarker circled in black shows a non correct behavior compared with the other dataand should be excluded by the analysis. The point corresponds to sector 0°, whichhas a low frequency during the considered measurement period and could beinfluenced by errors in the statistic analysis. Concerning the tower 5428, data arewell disposed in a trend in both periods.100
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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
Page 57 and 58: 3.6 RemarksA CFD study of a boundar
Page 59 and 60: Some experimental wind data of this
Page 61 and 62: Both the pictures 4.3 and 4.4 have
Page 63 and 64: Table 4.2: Description of the color
Page 65 and 66: In this periods, data are recorded
Page 67 and 68: In the following pages, a short des
Page 69 and 70: 4.3.2 Mast 5424-15 m Period April-M
Page 71 and 72: 4.3.4 Mast 5424-15 m Period Novembe
Page 73 and 74: 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: From the error analysis, it is foun
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 and 126: Figure 6.10 g/hFigure 6.10 i/lFigur
Page 127 and 128: to have a better agreement during t
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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wind energy resource evaluation in a site of central italy ... - WindSim

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