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Transcript of Wind Data Collection and Analysis in Kumasi - IJENS · Wind Data Collection and Analysis in Kumasi...
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 12
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
Wind Data Collection and Analysis in Kumasi Eric Osei Essandoh
1, Abeeku Brew- Hammond
1,2, Faisal Wahib Adam
1
1Mechanical Engineering Department, KNUST, Kumasi
2 The Energy Center (TEC), KNUST, Kumasi
Abstract-- This paper contributes to the effort being made by
The Energy Center (TEC), KNUST and African Union
Commission to disseminate knowledge of Renewable Energy
Technologies (RETs) and as well increase the awareness of the
general public especially the youth of Africa in RETs by
measuring the average wind speed and direction of a selected
project site (designated Site 0001) on the campus of Kwame
Nkrumah University of Science and Technology (KNUST). In
order to generate a comprehensive wind data report for Site 0001
on KNUST campus a building-integrated hybrid mast (placed at
a height of 20 m above ground level), NRG Wind instruments
and data retriever as well as Stata, Microsoft Excel and WAsP
software were employed. The wind data provided in this paper
include monthly and annual average wind speeds, monthly wind
gusts, prevailing wind direction and turbulence intensity of air
flow among other parameters for Site 0001 on KNUST campus.
The wind data made available by this paper can be used by both
students and the general public alike for educational and
agricultural purposes, air pollution and small wind turbine
assessments in Kumasi.
Index Term-- Renewable Energy Technologies; building-
integrated hybrid mast, air pollution
I. INTRODUCTION
The writing of this research paper was partially driven by the
need to revive the collection of climatic data initiated in 1993
but stopped in 2004 by the Solar Energy Application
Laboratory (SEAL) of the Mechanical Engineering
Department of KNUST. Weather data sets were collected by
SEAL by employing weather monitoring equipment such as a
propeller anemometer, radiometers for both global and diffuse
irradiation, air-temperature/ relative humidity sensor and a
rain gauge which were all manufactured by Kipp and Zonen.
The climatic data collected by SEAL was obtained at a height
of about 7 m. An annual average wind speed of about 1.5 m/s
was recorded at the project site (the roof top of the building
housing SEAL). This paper collected real wind data on two
principal characteristics of wind namely wind speed and wind
direction at a recording site which was located on top of the
new classroom block of College of Engineering (COE) on
KNUST campus at a height of 20 m.
Another interesting reason why this research work was carried
out was the quest to draw or attract the attention of local
scientific researchers in particular and science students in
general to the need for the development of an alternative
cleaner energy resource to reduce the reliance of Ghana on the
most widely used fuel - fossil fuel which is unclean,
potentially expensive, finite, a contributor to climate change
and an exhaustible energy resource. Coupled to this, is the
need to reduce the harmful effect of global warming by
switching from the use of fossil fuels to renewable energy
sources so as to conserve the fossil fuel or to forgo entirely the
fraction of the fossil fuel which is intended to be conserved.
Global warming is caused by greenhouse gases (GHG)
liberated into the atmosphere during the combustion of fossil
or conventional fuels and other anthropogenic activities. The
phenomenon of global warming is as a result of the inability
of the trapped GHG to leave the atmosphere to outer space
thus causing an atmospheric temperature disturbance on the
Earth surface which in turn causes climatic change. This
phenomenon indeed throws a big challenge to the entire global
scientific committee to look for a solution that will disable
these heat trapping gases (GHG) to lose this property that they
now possess which scares and poses a serious threat on the
globe. Climate change is the single most pressing issue facing
the World today (IPCC, 2007 as cited by Agbeve M.S. et’
al., 2011).
There is really the need for the whole world to adopt the EU
protocol which makes them responsible to be committed to
limiting global warming to a maximum average temperature
increase of 2 ◦C above pre-industrial levels (Lectenbohmer et
al., 2005). In addition, there is the need for any responsible
nation to try to diversify its energy mix by introducing some
quota of renewable energy to enhance its energy mix, access
and security. This work also disseminates some amount of
knowledge in renewable energy technology and therefore
raises awareness of people in renewable energy technologies
and to be precise wind resource assessment (an aspect of wind
power technology), an area which is less known in this part of
the world.
This paper summarizes wind data collected from 1 March,
2011to 30 September, 2011 on the campus of Kwame
Nkrumah University of Science and Technology (KNUST)
using NRG System Incorporated of USA’s wind monitoring
equipment made up of one # 40 maximum cup anemometer, a
200P wind vane and a Wind Explorer™ all mounted on a
building-integrated tower.
Wind resource assessment is carried out to quantify the
characteristics of the wind resource at a location to determine
the viability or the non-viability of a wind energy project. This
clearly confirms the fact that wind resource assessment is an
essential component of either pre- or full feasibility studies.
The most significant and critical parameter which needs to be
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 13
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
considered first in any wind resource assessment without any
doubts is the wind speed and for this reason the feasibility of
most wind power project mainly hinges on the magnitude of
the wind velocity.
II. OBJECTIVES OF THE STUDY
The main objective of this paper is to rebuild the capacity to
collect and analyze wind data on KNUST campus and thereby
establish a platform for future research work at KNUST on
wind energy.
The specific objectives of this paper are given as follows:
(1) To collect and analyze wind data at a height of 20 metres.
(2) To use wind data to calculate wind power potential for the
selected site at KNUST
III. SCOPE AND LIMITATIONS OF WORK
This research work was planned to cover:
the design and implementation of a wind monitoring
system
the collection of the two principal kinds of wind data
(wind speeds and directions), these data were
sampled every two (2) seconds and averaged every
(10) ten minutes.
the analysis of both internally binned wind data
stored in a Wind Explorer™ and time-series wind
data stored on a DataPlug that is plugged in the Wind
Explorer™.
the Comparison of observed wind speeds at a site on
KNUST campus with other sources of wind data
(RETScreen and Weather Underground Inc. wind
data).
the calculation of the wind power density and the
plotting of the wind speed histogram and wind rose
of KNUST Site 0001 through the analysis of time-
series wind data
the estimation of the output power of two selected
wind turbine models from the library of an online
Wind Power Calculator designed and developed by
Meteotest of Switzerland based on size (the two
smallest turbines in the library of the Power
Calculator were selected).
This research work measured wind speed and wind direction
using a proprietary wind monitoring equipment (NRG
Systems Inc. # 40 Maximum anemometer and # 200P Wind
Vane) leaving out air temperature, density, pressure, solar
irradiation, precipitation or amount of rainfall and humidity.
The measurement of icing frequency was not an issue because
the site does not experience snowfall. Each of the two wind
sensors used for the measurement was mounted on a lateral
boom attached to a 5.8 m tall galvanized steel tubular tower
supported in a concrete base on the rooftop of a 15 m three-
storey building (belonging to the College of Engineering of
KNUST).
The wind monitoring system was placed on the rooftop in the
vicinity of a satellite dish and a communication tower which
increased the turbulent structure or zone of the wind flow
around the wind monitoring system.
The height of the anemometer was 5 m above the rooftop and
20 m above the ground while the wind vane was about 4.90 m
above the rooftop and about 19.90 m above the ground. The
height of the wind instruments above the rooftop of the
building was specifically chosen and was not up to the
standard meteorological height of 10 m due to infrastructural
constraints. As a result of this the anemometer and the vane
used for the measurement were engulfed by turbulent wind
flow which affects the sensitivity of the wind instruments.
Seven months internally binned wind speeds and directions
(Captured on the display pages of a Wind Explorer™) were
organized and made available for analysis due to time
constraints while only the last three months time-series wind
data (stored on a 128 KByte DataPlug) was made available for
analysis due to accidental erasing of data from the DataPlug.
The raw wind data stored on the DataPlug for the first four
months of the measurement period was erased. Stata software
was used for the analysis of the internally binned wind data
while the Wind climate Analyst component of WAsP and the
Microsoft Excel Software were separately used for the
analysis of the three month time-series wind data. The full
WAsP software could not be used for the analysis of the three
month wind data because the wind data which was retrieved
from the DataPlug was limited in size (minimum
recommended size of wind data for analysis by the full WAsP
software is one year). No climate-adjustment was done.
However, the wind measurement campaign for this research
work was carried out for one year and as a result a one year
internally binned monthly average wind speeds and wind
directions were captured on the display pages of the Wind
Explorer™.
WIND RESOURCE OF GHANA
A glance at the wind resource map of Ghana at 50 m
developed by the National Renewable Energy Laboratory of
USA during the Solar Wind Energy Resource Assessment
(SWERA) programme in August, 2002 reveals through colour
coding that the bulk of the wind resources of the country are
class 3 wind resources and are available at a few locations in
regions like Western, Central, Greater Accra, Eastern, Volta,
Ashanti, Brong Ahafo and Northern region while some few
sites in Volta region especially the area close to the Ghana-
Togo border is endowed with good to excellent wind resource
(depicted by the wind resource map of Ghana at 50 m
developed by the National Renewable Energy Laboratory of
USA-NREL). However, the SWERA report establishes that
there are other few locations in both the Eastern and Northern
regions of Ghana which are also endowed with good to
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 14
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
excellent wind resource (not clearly depicted on the wind
resource map of Ghana at 50 m). The land size of Ghana
endowed with class 3 and above wind resources is a very
small fraction of the total land size of Ghana and for this
reason the appropriate measures must be put in place by
stakeholders in prospective wind power projects to ensure the
optimum utilization of these wind sites for wind power
projects in order not to waste these wind resource sites.
Specifically, a land area of about 1128 km2 which is about 0.5
% of Ghana’s total land area is endowed with a class 3 wind
resource or higher (Park, et al., 2009). The total land area of
Ghana is about 238533 km2 while the land and water areas are
227, 533 km2 and 11,000 km
2 respectively (Index Mundi,
2011).
The breakdown of the total wind resource land area of 1128
km2 of Ghana into several wind classes puts 0.3 % of it under
Class 3 (designated as moderate wind resource), 0.1% of it
under class 4 (designated as good wind resource), less than
0.1% of it under class 5 (designated as excellent wind
resource) and less than 0.1% of it under class 6 (also
designated as excellent wind resource) - (Agbeve M.S. et al.,
2011). The wind resource map of Ghana at 50 m and the
distribution of the wind resource of the country into the
various classification of wind resource (per NREL
classifications) are shown in figure 1 and Table I below
respectively.
Fig. 1. Wind Resource Map of Ghana at 50 m.
Source: NREL, USA
Table I
Class 3 and above Wind resource of Ghana at 50 m
Wind
Resource
Designation
Wind
Class
Wind
Power
Density at
50 m
(W/m2)
Wind
Speed at
50 m (m/s)
Total Area
(km2)
Windy
Land as a
Percentage
of Ghana’s
Total
Land (%)
Potential
Installed
Capacity
(MW)
Moderate 3 300 - 400 7.1 – 7.5 715 0.3 3575
Good 4 400 – 500 7.5 – 8.4 265 0.1 1340
Very Good 5 500 – 600 8.4 – 9.0 82 < 0.1 410
Excellent 6 600 – 800 9.0 – 9.9 63 < 0.1 315
Total 1128 0.5 5640
Source: Agbeve M.S. et al, 2011 and NREL, USA
HISTORICAL PERSPECTIVE OF WIND MEASUREMENTS
IN GHANA
Weather conditions were measured in Accra, the national
capital of Ghana as far back as 1921. This was the year that
the agency which was responsible for meteorological data
collection in the then Gold Coast measured wind direction at a
site in Accra using a wind vane. In 1936, the above agency
now, Ghana Meteorological Agency (GMA) installed a cup
counter anemometer and William H. Dine‘s pressure tube
anemometer to measure instantaneous wind speeds and
directions in Accra. They have since been recording wind
speed and direction data at 2 m above ground level (a.gl) at all
the 22 synoptic stations sited within every latitude (between
4 4’ and 11 11’ N) and longitude (between 3 11’W and 1
11’E) of the country. The data obtained from GMA indicate
average wind speeds of approximately 2.4 m/s at 2 m agl at
stations set up with objectives other than for energy
applications. The
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132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
sites were deliberately selected for their low wind regimes as
the measurements were made for meteorological and
agricultural applications (Nkrumah, 2002).
Studies on wind measurements conducted under the
supervision of Professor F.O. Akuffo of Kwame Nkrumah
University of Science and Technology using historical data
from the GMA and captured in Akuffo (1991 as cited by
Nkrumah, 2002) suggest that the average wind speed across
the country is 1.7m/s. The study also indicated that a
maximum monthly average wind speed of about 3.4 m/s came
from the Eastern coastline of the Accra plains. These
measurements were taken at a height of 2 m above ground
level. NEK UMWELTTECHNIK GmbH of Switzerland in
March, 1999 in collaboration with Future Energy of Koblenz,
Germany as client and service provider respectively installed
two masts 10m and 40m in each of three selected sites namely
Prampram, Ningo and Ada. These three towns are all located
in the Accra plains along the eastern coastline. This project
undertaken by NEK UMWELTTECHNIK GmbH received
support from DEG-DeustschInvestitons-
UndEntwicklungsgellchaft GmbH of Cologne, Germany after
obtaining project execution permit from the then Ministry of
Mines and Energy, now Ministry of Energy (the mining
functions are now performed by another ministry). Wind
measurements taken at the above-mentioned sites lasted for
about a year spanning from May, 1999 to June, 2000. An
annual average wind speed of 5.8 m/s for these three sites was
recorded at a height of 10m by NEK UMWELTTECHNIK
GmbH (Nkrumah, 2002). In June, 1999 the Energy
Commission of Ghana began to take wind measurements at
eleven (11) coastal sites east and west of the Greenwich
Meridian (around Accra). In August, 2002, the Solar Wind
Energy Resource Assessment (SWERA) program in
collaboration with the Energy Commission and the GMA
began a nationwide wind resource assessment in Ghana.
As part of the SWERA project, a wind resource map of Ghana
with a resolution of 1 km2 (shown in Figure 1 above) was
developed by NREL of USA. Information on some wind
measurements carried out by the Energy Commission and
other independent entities in Ghana are tabularized in Table II
below. There are no official proofs or documents for wind
measurements carried out by private individuals.
In August 2010, Eleqtra West Africa Limited started taking
wind measurements at Ada in the Greater Accra region of
Ghana at a height of 60m. The monthly average wind speed
recorded at this site was quoted by Mr. Kobina Arthur, a wind
technician of Eleqtra West Africa Limited as 4.95 m/s in a
telephone interview on 8th
February 2012.
In November, 2011, Energy Commission (EC) in conjunction
with GEDAP/MOE (World Bank) started taking wind
measurements at five selected sites at a height of 60 m. These
five sites are Atiteti and Avata in the Volta region, Great
Ningo in the Greater Accra region, Ekumfi Edumafa, Gomoa
fetteh and Senya Bereku in the Central region.
In another development a joint wind resource assessment
project is currently being undertaken by EC/Vestas at two
selected sites. The selected sites for the EC/Vestas Wind
resource assessment project are Kablavo (near Adafoah) and
Anloga. Wind measurements for these sites would be taken at
a height of 80 m. This information was given by Mr.
Mawufemo Madjinou of Energy Commission in a
conversation on 7th
February, 2012.
Table II
Historical Measurement of Wind Speeds in Ghana.
METHODOLOGY
A wind monitoring system comprising approximately 5.8
metre tall galvanized steel tubular tower instrumented with
two principal wind sensors and a data logger was installed on
the rooftop of a three-storey building at a height of 20 m
above ground level to undertake a wind resource assessment at
KNUST.
Wind speeds and directions were collected using NRG Wind
Explorer TM
(a data logger) and each of the following wind
sensors: NRG #40 cup and 200P wind vane. These wind
sensors were mounted on booms attached to a building –
mounted mast. The wind monitoring system was completely
installed on 18 February, 2011 but was test run until 28
February, 2011 when actual data logging began. The NRG #
40 maximum cup anemometer was compared to a Deuta
Anemo brand hand- held anemometer in the absence of a
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 16
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
standard calibrator to estimate its accuracy. The values
recorded by the NRG # 40 maximum cup anemometer were
0.5 m/s greater than that of the Deuta Anemo hand-held
anemometer during the test run.
Wind data in the form of wind speed and direction were
sampled every two seconds by the Wind Explorer. These data
were then combined with the standard deviations of the wind
data and averaged and stored every ten minutes by the NRG
Wind Data logger. During these 10 minutes averaging periods
a binary file is generated and held on the data plug. These
binary files were later combined with a site file and converted
into an ASCII text file using the NRG Data Retriever
Software. The ASCII text file was subsequently imported into
a Notepad and an excel spreadsheet. Statistical analysis
software called Stata was used to analyze the seven month in-
built wind data stored in the Wind Explorer. Stata was used to
create bar graphs which depict mean monthly variations in the
wind data for the seven separate months of March to
September, 2011. It was also used to create the hourly
frequency distributions of wind speeds and wind directions for
the first seven-month period of wind measurements. A
program called Climate Analyst distributed alongside the main
WAsP Software Worldwide by the Wind Energy Department
of Risøe DTU of Denmark was used to generate time-series
graphs of the wind direction and wind speed using the wind
data for the three contiguous months of July, August and
September, 2011. This software was also used to produce
wind rose, wind speed histogram and some calculations based
on the wind data for the third quarter of the year, 2011 for
Kumasi.
SITE DESCRIPTION
The site used for the wind measuring instrument campaign
was located on the campus of Kwame Nkrumah University of
Science and Technology (KNUST) which is a few metres
northeast of the Kumasi –Accra road. The University is
actually located in a suburb of Kumasi called Ayeduase at a
geographic coordinate of latitude, 6.4 ◦N and longitude, 1.3
◦W
and at an elevation of about 263 m. The wind monitoring
tower equipped with the relevant instruments was mounted
and guyed on a 3-storey building belonging to the College of
Engineering (COE) of KNUST. This building also houses the
Energy Center (TEC), KNUST. The wind monitoring system
was raised in a concrete base foundation on an approximately
7 m by 5 m rooftop floor space putting the wind monitoring
system at a height of 20 m above ground level (anemometer
height) and 5 m above the rooftop of the COE new classroom
block. This site was designated as KNUST Site 0001. Figures
2 and 3 below show the obstacles on the wind recording site
and the wind monitoring system respectively.
Fig. 2. Obstructions on Site.
Fig. 3. Wind Monitoring System
IV. RESULTS AND DISCUSSIONS
SITE DATA ANALYSIS
This section of the paper analyzes the real and primary data of
interest collected during the research work and presents some
results as follows using both manually organized frequency
distribution of wind speeds and directions from March 1, 2011
to September 30, 2011 as well as time-series wind data for the
third quarter of 2011 ( July, 2011 – September, 2011).
WIND SPEED AND DIRECTION DISTRIBUTIONS: The
wind speed and direction distributions for only the first three
months (March, 2011–May, 2011) of the period for wind
measurement campaign of this work are shown in figures 4 to
9 below since the nature of the distributions were almost the
same
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 17
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
Fig. 4. Wind Speed at KNUST Site 0001 for March, 2011
Fig. 5. Wind Direction Distributions at KNUST Site 0001 for March, 2011
Fig. 6. Wind Speed at KNUST Site 0001 for April, 2011
Fig. 7. Wind Speed Direction Distributions at KNUST Site 0001 for April,
2011
Fig. 8. Wind Speed at KNUST Site 0001 for May, 2011
Fig. 9. Wind Direction Distributions at KNUST Site 0001 for May, 2011
Figures 10 and 11given below show graphs of Monthly
average wind speeds and hourly wind speed frequency
distributions respectively. Figure 12 shows the hourly wind
direction frequency distributions.
Fig. 10. Monthly Average Wind Speed From March to September, 2011
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 18
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
Fig. 11. Hourly Wind Speed Frequency Distributions for March, 2011 to
September, 2011 for Site 0001 at KNUST
Fig. 12. Hourly Frequency Distributions of Wind Directions for March –
September, 2011
MICROSOFT EXCEL SOFTWARE ANALYSIS OF
WIND SPEED DISTRIBUTION FOR THE THIRD
QUARTER OF THE YEAR, 2011
The Excel graphs provided in figures 13 and 14 below depict
the average hourly wind speeds and the average diurnal wind
speeds respectively.
Fig. 13. Average Hourly Wind Speeds for each month of the Third Quarter of
2011
Fig. 14. Average Daily Wind Speed for each of the months in the Third
Quarter of 2011
A quick glance of figure 13 shown above reveals that the
overall highest wind speed occurred in July at about 11: 00
A.M. A similar glance at figure 14 above reveals that the
thirteenth day of August registered the overall highest wind
speed.
WAsP SOFWARE ANALYSIS OF WIND SPEED AND
DIRECTION DISTRIBUTIONS FOR THE THIRD
QUARTER OF THE YEAR, 2011
WIND DIRECTION AND SPEED TIME-SERIES
GRAPH
The graph shown in figure 15 just below depicts the wind
direction time-series graph on top of that of the wind speed.
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 19
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These graphs show the plots of the ten (10) minute average
wind directions and speeds against time. They show the
variations of the above wind characteristics about their mean
values and how they spread from their mean values within
their respective specific standard deviations.
Fig. 15. Time Series Graph of Wind Directions and Wind Speeds
WIND ROSE AND WIND SPEED HISTOGRAM
GENERATED BY WAsP FROM WIND DATA FOR
JULY TO SEPTEMBER, 2011.
The wind rose and wind speed histogram for the wind
recording Site (Site 0001 at KNUST) for the third quarter of
the year, 2011 are shown in figure 16 given below.
Fig. 16. Wind Rose and Wind Speed Distributions for July 2011 to September
2011
Fig. 17. WAsP Weibull Distribution Curve for Wind Speeds from July1 to
September 30, 2011 for Site 0001 at KNUST
Table III
13-MONTH WIND DATA COLLECTION ON SITE 0001 AT KNUST
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Table IV Comparison of the Directly Measured Monthly Average Wind Speeds Obtained for KNUST Site 0001 and Weather Underground Inc. Monthly Average Wind
Speeds for 2011
Month/Year Wind Speed, m/s
(Directly Measured
at KNUST Site
0001 at 20 m )
Wind Speed, m/s
(Measured by
Weather
Underground Inc.
at 10 m )
Wind Speed, m/s
(Weather
Underground Inc.
Monthly Average
wind Speeds
extrapolated from
10 m to 20 m )
Estimated
Percentage Error,
% (calculated by
using Monthly
Average Wind
Speeds directly
measured at
KNUST site 0001 at
20 m and Weather
Underground Inc.
Wind Speeds
extrapolated from
10 m to 20m )
January, 2011 N/A*
1.1 1.2 N/A
February, 2011 N/A 1.4 1.5 N/A
March, 2011 2.0 1.7 1.9 5.0
April, 2011 2.1 1.9 2.1 0
May, 2011 2.1 2.2 2.4 -14.3
June, 2011 2.1 1.9 2.1 0
July, 2011 2.5 1.9 2.1 16.0
August, 2011 2.6 2.2 2.4 7.7
September,2011 2.0 1.9 2.1 -5.0
October, 2011 1.5 1.7 1.9 -26.7
November, 2011 1.5 1.5 1.7 -13.3
December, 2011 1.2 1.5 1.7 -41.7
*N/A means not applicable
Hint: Extrapolation of wind speeds was carried out using the 1/7 Power Law.
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 21
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Table V
Comparison of Directly Measured Monthly Average Wind Speeds at 20 m at KNUST Site 0001 from March, 2011 to December, 2011 and RETScreen Historical
Monthly Average Wind Speeds Extrapolated from 10 m to 20 m
Month Wind Speed, m/s
(Directly Measured
at KNUST Site
0001 at 20 m in
2011 )
Wind Speed, m/s
( Historically
Recorded Monthly
Average Wind
Speeds at 10 m by
RETScreen )
Wind Speed, m/s
( RETScreen
Monthly Average
Wind Speeds
Extrapolated from
10 m to 20 m )
Estimated
Percentage Error,
% (Using Directly
Measured Monthly
Average Wind
Speeds at KNUST
Site 0001 at 20 m
and RETScreen
Monthly Average
Wind Speeds
Extrapolated from
10 m to 20 m )
January N/A 1.5 1.7 N/A
February N/A 2.1 2.3 N/A
March 2.0 2.1 2.3 -15.0
April 2.1 2.1 2.3 -9.5
May 2.1 2.1 2.3 -9.5
June 2.1 2.1 2.3 -9.5
July 2.5 2.6 2.9 -16.0
August 2.6 2.1 2.3 11.5
September 2.0 2.1 2.3 -15.0
October 1.5 2.1 2.3 -53.3
November 1.5 1.5 1.7 -13.3
December 1.2 1.5 1.3 -8.3
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Table VI Comparison of RETScreen Historical Monthly Average Wind Speed for Kumasi and Weather Underground Inc. 2011 Monthly Average Wind Speeds for Kumasi
VELOCITY PROFLE AND POWER PRODUCTION
OUTPUT FOR TWO SELECTED TURBINES AT
KNUST SITE 0001
The annual average wind speed of 1.9 m/s is used to generate
both the velocity profile of the site and the annual power
output for two smallest wind turbines selected from the library
of an online Power Calculator. Both the Velocity profile and
the Power Calculator were developed by Meteotest on behalf
of Suisse Eole of Switzerland. The velocity Profile calculator
requires the roughness length of a candidate site, the wind
speed and the height at which it was measured to estimate the
wind velocity profile of any site under investigation (candidate
site). The velocity profile of Site 0001 at KNUST is shown in
figure 18 below. This graph shows how the wind speed at Site
0001 varies with height. The two selected wind turbines from
the library of the Meteotest online Power Calculator in
ascending order of size or capacity are the Aventa AV-7 (6.75
kW) and Fuhrlander FL 30 ( 30.0 kW). The power calculator
by its design requires the annual mean wind speed and the
density of the candidate site. Since air density is dependent on
air temperature and pressure of the location, thus the standard
density of 1.225 kg/ m3 adopted by the power calculator as its
default value needs to be corrected based on the pressure,
temperature and the elevation of the candidate site. Hence, a
corrected density value of 1.2 kg/m3 was calculated and used
for Site 0001.
The velocity profile of Site 0001 on KNUST campus
generated by the Wind Velocity Profile calculator for the site
under investigation is shown in figure 18. The results of the
two selected turbines mentioned above by way of annual
power production are shown in Tables IV and V for the
Aventa AV-7 (6.75 kW) and Fuhrlander FL 30 (30.0 kW)
wind turbines respectively.
Fig. 18. Wind Speed Profile for Site 0001 based on annual mean speed of
1.9m/s at 20 m (Generated by Meteotest Wind Profile Calculator)
Table VII
Results of Aventa AV-7 at an Average Wind Speed of 1.9 m/s measured at
Site 0001 at KNUST
International Journal of Mechanical & Mechatronics Engineering IJMME-IJENS Vol:13 No:04 23
132004-5858-IJMME-IJENS © August 2013 IJENS I J E N S
Table VIII Results of Fuhrlander FL 30 (30.0 kW) at an Average Speed of 1.9 m/s
Measured at Site 0001 at KNUST
CONCLUSIONS
This paper presents the wind data summary of the wind that
blew at site 0001 at KNUST mainly from March, 2011 to
September, 2011 in addition to the annual average wind speed
of 1.9 m/s at 20 m above ground level (agl) calculated from
the monthly average wind speeds for March, 2011 to
February, 2012. Other wind characteristics for KNUST Site
0001 provided by this paper are the air density of 1.2 kg/m3,
turbulence intensity (0.4 or 40 %), and the prevailing wind
direction (northwest). Through the use of the two selected
turbines from the library of the power calculator developed by
Meteotest this paper confirms the fact that wind speeds of <
4.5 m/s at the hub height of an installed wind turbine produce
uneconomical power as indicated by low capacity factors of
4.4 % and 0.2 % for the selected Aventa AV-7 (6.75 kW) and
the Fuhrlander, FL 30 (30.0 kW) wind turbines respectively.
The annual average wind speed of 1.9 m/s obtained for
KNUST Site 0001 at 20 m is surprisingly almost equal to the
annual average wind speed of 1.9997 m/s obtained by
RETScreen at 10 m agl (if not rounded- up) for Kumasi
several years ago. However, the annual average wind speed
for Site 0001 is as expected greater than that of the Weather
Underground Inc. measured at 10 m (1.75 m/s) for Kumasi in
the year, 2011. Even, in this instance, there were certain
monthly average wind speeds obtained by Weather
Underground Inc. which were greater than their corresponding
monthly average wind speeds obtained for Site 0001. This
shows that the airflow at Site 0001 was seriously influenced
by turbulence as confirmed by the relatively high turbulence
of 0.4 obtained by this paper. In light of the above, a site well
exposed to air in Kumasi should be used to establish the
validity of site 0001 wind profile which presupposes that even
at a height of 150 m, the annual average wind speed will be <
4 m/s.
ACKNOWLEDGEMENT
We wish to thank the Energy Commission of Ghana and the
Centre for Scientific and Industrial Research, Accra for
lending us the wind monitoring equipment used for the
research work and the Risϕe DTU- National Laboratory for
Sustainable Energy, Wind Energy Division of Denmark,
especially their staff, Heidi Jacobsen Serny, who issued a
temporary educational licence for the use of the WAsP
Climate Analyst software for the preparation of this paper.
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