1. IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org
ISSN (e): 2250-3021, ISSN (p): 2278-8719
Vol. 04, Issue 09 (September. 2014), ||V1|| PP 09-32
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A Realistic Estimate of Annual Typical Daily Wind Power of different heights in Urban Armidale NSW, Australia
Yasser Maklad1
1(University of New England, Armidale NSW 2351 NSW Australia– School of Environmental & Rural Science - email: ymaklad@myune.edu.au)
Abstract: - Wind is one of the common sources of renewable and clean energy. It is really difficult to predict wind performance at any specific moment. In addition to the very intermittent nature of wind, wind behaviour and speed are directly affected by several factors, specifically the nature of the environment and the height that wind blows at. Wind behaviour at urban large city areas and urban suburban areas is completely different than such behaviour at open terrain and flat unobstructed areas. Wind performance in urban and areas are completely different from either open areas or capital cities with huge high rise buildings. Wind is more disturbed and turbulent and wind speed decreases due to the existence of several obstructions, mostly buildings either single storey or medium rise or high rise buildings in addition to trees. Moreover, wind speed at different heights is directly affecting win energy can be generated from using wind turbines. Thus, it is never an easy task to provide a reliable realistic estimate of wind energy at a specific urban location or city. Many trials based on using meteorological announced wind speed which is a clear overestimation and misled non-specialists due to the fact that meteorological observations are conducted on specified heights (mostly 10 meters) in an open place with no restriction, this would provide a wind speed much higher than wind speed would occur in the urban environment of the same town. Armidale is a regional city in New South Wales (NSW) in Australia, as well it is the highest town all over Australia. This study aims to provide a justified realistic/creditable/ reliable estimate of annual typical daily wind power. The reason of this justification that this study depends on an accurate estimate wind speed at different heights calculated specifically for urban Armidale. Such estimate would be a great benefit of wind energy specialists and non-specialists households to obtain an estimate of daily potential wind power in Armidale.
Keywords: - Armidale NSW, wind power, test meteorological year, test reference year, wind speed, micro-scale energy generation, micro-wind turbines
I. INTRODUCTION
While wind flows over an open area which approaches the boundaries of the built-up area, it faces a high surface roughness, created by existing buildings. The increased resistance resulting from this roughness reduces the wind flow at the level of the urban canopy. In this way a transitional zone is created between the ground and the undisturbed wind flow above the urban air dome, which is called “urban boundary layer”. The “undisturbed flow” is called the “gradient wind” and its velocity is called the gradient velocity. While, near the ground, wind experiences friction. Its speed is reduced more steeply and its turbulence increases. [1, 2 &3].
The main urban design elements which change wind conditions are: the overall density of the urban area, size and height of the individual buildings; existence of high-rise buildings, orientation of the streets, availability, size distribution, and aspects of design of open spaces and green shelter belts. [4, 5 & 6].
Wind field is characterized by two parameters: the vertical profile of the mean wind speed and the turbulence spectrum. Both parameters are affected and modified by the profile of the terrain and, in an urban setup, by the urban structure [4, 5, 6 & 7].
Micro-scale energy generation ranges from [0.5 to 10] kW which suits domestic/residential, educational and small commercial applications.
Most wind energy development in NSW will be in rural and regional areas. Wind energy is especially attractive to these communities because of the potential for employment, industry development, income for landholders, and supplementing existing tourist attractions. An independent study commissioned by Sustainable Energy Development Authority of NSW [8] showed that employment created by sustainable energy development tended to be concentrated in rural and regional areas. The study found that: manufacturing wind turbines creates 3–6 jobs per Megawatt of installed capacity; installation creates 0.5–0.8 jobs per Megawatt; the operation and maintenance of wind turbines creates 0.05–0.5 jobs per Megawatt [9 &10].
2. A Realistic Estimate of Annual Typical Daily Wind Power of different heights in Urban Armidale
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This study focuses on the generation of wind energy at urban Armidale NSW, Australia as a sample of regional Australian cities at heights (8, 9 &10) meters. This scope is selected mainly to provide micro-scale wind energy generation systems’ designers an annual realistic mean daily wind power at such heights of micro-wind turbines’ possible installations.
II. DATA AND LOCATION
A previous study estimated urban mean daily wind speed at (8, 9 &10m height was developed [11]. That study was generated based on a previous generated meteorological wind test reference year (TRY) which was generated based on the daily mean wind speed recorded during the period 1994–2010 recorded at Armidale’s Airport Weather Station (AWS). That TYR was generated utilising Finkelstein-Schafer (FS) statistics [12 &13].
In Australia, meteorological observations are recorded by the Australian Bureau of Meteorology (BOM) weather stations are widely spreader in lots of cities and towns around Australia. In this study, the global wind speed data recorded by Armidale Airport Weather Automatic Station and published on the BOM’s website where it was collected. The missing and invalid measurements account for 0.001% of the whole database of mean wind speed; those were replaced with the values of preceding or subsequent days by interpolation. During the calculations process, any year found with more than ten days in any month observations not available was excluded. “Table 1” provides geographical information for Armidale town and the periods of the relevant mean wind speed data and “figure 1” shows Armidale’s location in NSW, Australia.
Table 1 Geographical and mean wind speed database information of Armidale NSW, Australia
Longitude ( †E)
Latitude( †S)
Elevation (m)
Mean Daily Wind Speed
Period
Total years
Armidale
151.67
30.52
970-1070
1994—2013
20
Figure1 Armidale NSW, Australia location
3. A Realistic Estimate of Annual Typical Daily Wind Power of different heights in Urban Armidale
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III. METHODOLOGY
The power of wind can be estimated by using the following equation [14]:
푃(푣)= 12 휌퐴푣̅3 (1)
where ρ is the mean air density, ν3 is the mean value of the third power of the wind velocity, and A is the swept area.
In addition, for a height less than 100 m, the power density of the wind above the ground level is given by [15]:
푃ℎ=푃10( ℎ 10) 3훼 (2)
where P10 is the corrected power available in wind at a height of 10 m and α is the roughness factor, usually in the range 0.05–0.5. Wind velocity data were extrapolated by using the following power-law formula [16]:
푣1 푣2=( ℎ1 ℎ2) 훼 (3)
where v1 and v2 are the wind velocities at heights h1 and h2, respectively.
The capacity factor Cp is one of the performance parameters of wind turbines that both the user and manufacturer need to know. It represents the fraction of the total energy delivered over a period, Eout, divided by the maximum energy that could have been delivered if the turbine were used at maximum capacity over the entire period. The capacity factor Cp of a wind turbine can be calculated as the following [15]:
퐶푝= 퐸표푢푡 퐸푟 (4)
IV. GENERATION OF A TYPICAL ANNUAL MEAN WIND POWER
“Tables2, 9 & 16” show urban daily wind speed values obtained from Test Reference Year data for Armidale NSW, Australia at (8,9 &10) m height in (m/s). Applying the above methodology to those urban mean daily wind speed, results in mean daily wind power in kWp as shown in “ Tables 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21 & 22) “ shows the calculated power in kWh per day for wind turbines’ swept area of 10 m2 operating at height (8, 9 & 10) m above ground for all months for capacity factors (10, 20, 30, 40, 50 & 55)%. Additionally, Tables (23 & 24) shows the calculated power in kWh per month for wind turbines’ swept area of 10 m2 operating at (8, 9 & 10) m height above ground. An area of 10m2 was selected for simplification purpose. Apparently, the higher the more wind power generated, as well the greater wind turbine capacity factor (Cp), the greater wind power.
23. A Realistic Estimate of Annual Typical Daily Wind Power of different heights in Urban Armidale
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Table 23 Power in kWh per month for wind turbines’ swept area of 10 m2 operating at heights (8 & 9) m above ground
Month
8m H
9m H
Cp=10%
Cp=20%
Cp=30%
Cp=40%
Cp=50%
Cp=55%
Cp=10%
Cp=20%
Cp=30%
Cp=40%
Cp=50%
Cp=55% January 27.799 55.591 83.393 111.194 138.984 152.883 29.989 59.983 89.971 119.96 149.958 164.951
February
22.362
44.717
67.078
89.441
111.796
122.975
24.172
48.349
72.521
96.697
120.872
132.959 March 19.77 39.544 59.313 79.084 98.851 108.737 21.371 42.739 64.11 85.48 106.855 117.533
April
15.397
30.792
46.186
61.575
76.969
84.67
16.636
33.272
49.908
66.545
83.182
91.501 May 15.408 30.81 46.218 61.618 77.025 84.723 16.656 33.305 49.96 66.611 83.271 91.589
June
19.699
39.404
59.104
78.808
98.507
108.356
21.271
42.532
63.804
85.067
106.338
116.969 July 21.526 43.044 64.57 86.096 107.616 118.378 23.252 46.501 69.755 93.009 116.257 127.881
August
31.896
63.789
95.686
127.587
159.479
175.419
34.441
68.88
103.32
137.762
172.204
189.425 September 25.504 51.001 76.503 102.009 127.512 140.259 27.559 55.114 82.674 110.23 137.788 151.567
October
23.974
47.945
71.919
95.896
119.871
131.851
25.915
51.822
77.737
103.644
129.559
142.511 November 21.809 43.612 65.421 87.236 109.036 119.942 23.552 47.104 70.657 94.211 117.766 129.545
December
22.5
44.996
67.496
90
112.493
123.744
24.293
48.585
72.879
97.172
121.466
133.611 Total Annual 267.644 535.245 802.887 1070.544 1338.139 1471.937 289.107 578.186 867.296 1156.388 1445.516 1590.042
Table 24 Power in kWh per month for wind turbines’ swept area of 10 m2 operating at 10 m height above ground
Month
10m H
Cp=10%
Cp=20%
Cp=30%
Cp=40%
Cp=50%
Cp=55% January 32.171 64.334 96.506 128.675 160.848 176.929
February
25.915
51.826
77.744
103.656
129.575
142.53 March 22.908 45.807 68.717 91.62 114.526 125.979
April
17.84
35.677
53.516
71.354
89.196
98.114 May 17.853 35.699 53.554 71.401 89.254 98.176
June
22.812
45.625
68.44
91.254
114.064
125.471 July 24.933 49.859 74.796 99.728 124.659 137.124
August
36.923
73.839
110.762
147.675
184.599
203.054 September 29.54 59.076 88.62 118.156 147.696 162.465
October
27.765
55.523
83.291
111.055
138.819
152.696 November 25.25 50.5 75.757 101.006 126.261 138.886
December
26.061
52.118
78.185
104.247
130.309
143.34 Total Annual 309.971 619.883 929.888 1239.827 1549.806 1704.764
V. CONCLUSION AND RECOMMENDATIONS
Predicting wind power could be generated is a sophisticated task. As wind has an intermittent nature, nobody can tell any specific moment whether there will wind nor not or what would the wind speed. This task is much more complicated when it comes to consider urban areas where wind speed decay because of buildings and trees, as well turns to be turbulent. This paper considered developing a realistic/reliable/creditable database of annual mead daily typical wind speed based on previously published generated wind speed at urban Armidale for heights (8, 9 &10) meters which has been based on wind speed meteorological test reference year published and generated earlier. Such consequent calculations justifies and enhance the reliability of generated wind power. It is a common issue that mostly new micro-turbines users gets very frustrated of their turbines under-performance, although the fact that they have overestimated the available wind speed, actually, there are misled by overestimated meteorological historically recorded wind speed at their towns or cities. This paper considered Armidale, the highest city in Australia, as a sample of Australian regional cities. As well, the selected heights (8, 9 & 10) meters were meant, considering that most buildings, in Armidale, of (5 to 7) meters height, by adding
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another three meter for the micro-turbine installation, this would suit the selected heights in this study.
Needless to emphasise that, it is highly urged to base any wind power calculations or modelling on urban wind speeds. This would reflect the real picture of urban wind power potential and would save any disappointment of not reaching the expected energy generation which is usually misled by overestimation of wind speed due to the dependence on meteorological wind speed.
.
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[12] Maklad, Y. Generation of an Annual Typical Daily Wind Speed for Heights Equal and Less than 10 meters for Urban Armidale NSW, Australia, IOSR Journal of Engineering (IORJEN) 4(8), 2014, 31-42.
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