Wind Data Collection and Analysis in Kumasi

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Wind Data Collection and Analysis in Kumasi

Eric Osei Essandoh

1

, Abeeku Brew- Hammond

1,2

, Faisal Wahib Adam

1

1

Mechanical 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.

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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

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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 areais 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 km2 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/m

2

)

Wind

Speed at

50 m (m/s)

Total Area

(km

2

)

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

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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.

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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

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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.

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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

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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

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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

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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

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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

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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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Amedzofe and Nkwanta

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Figure

Fig. 1. Wind Resource Map of Ghana at 50 m. Source: NREL, USA
Fig. 1. Wind Resource Map of Ghana at 50 m. Source: NREL, USA p.3
Table I  Class 3 and above Wind resource of Ghana at 50 m

Table I

Class 3 and above Wind resource of Ghana at 50 m p.3
Table II Historical Measurement of Wind Speeds in Ghana.

Table II

Historical Measurement of Wind Speeds in Ghana. p.4
Fig. 2. Obstructions on Site.
Fig. 2. Obstructions on Site. p.5
Fig. 3. Wind Monitoring System
Fig. 3. Wind Monitoring System p.5
Fig. 6. Wind Speed at KNUST Site 0001 for April, 2011
Fig. 6. Wind Speed at KNUST Site 0001 for April, 2011 p.6
Fig. 8. Wind Speed at KNUST Site 0001 for May, 2011
Fig. 8. Wind Speed at KNUST Site 0001 for May, 2011 p.6
Fig. 5. Wind Direction Distributions at KNUST Site 0001 for March, 2011
Fig. 5. Wind Direction Distributions at KNUST Site 0001 for March, 2011 p.6
Fig. 9. Wind Direction Distributions at KNUST Site 0001 for May, 2011
Fig. 9. Wind Direction Distributions at KNUST Site 0001 for May, 2011 p.6
Fig. 10. Monthly Average Wind Speed From March to September, 2011
Fig. 10. Monthly Average Wind Speed From March to September, 2011 p.6
Fig. 4. Wind Speed at KNUST Site 0001 for March, 2011
Fig. 4. Wind Speed at KNUST Site 0001 for March, 2011 p.6
Fig. 13.  Average Hourly Wind Speeds for each month of the Third Quarter of  2011
Fig. 13. Average Hourly Wind Speeds for each month of the Third Quarter of 2011 p.7
Fig. 12. Hourly Frequency Distributions of Wind Directions for March –September, 2011
Fig. 12. Hourly Frequency Distributions of Wind Directions for March –September, 2011 p.7
Fig. 11. Hourly Wind Speed Frequency Distributions for March, 2011 to September, 2011 for Site 0001 at KNUST
Fig. 11. Hourly Wind Speed Frequency Distributions for March, 2011 to September, 2011 for Site 0001 at KNUST p.7
Fig. 14. Average Daily Wind Speed for each of the months in the Third  Quarter of 2011
Fig. 14. Average Daily Wind Speed for each of the months in the Third Quarter of 2011 p.7
Fig. 16. Wind Rose and Wind Speed Distributions for July 2011 to September  2011
Fig. 16. Wind Rose and Wind Speed Distributions for July 2011 to September 2011 p.8
Table III 13-MONTH WIND DATA COLLECTION ON SITE 0001 AT KNUST

Table III

13-MONTH WIND DATA COLLECTION ON SITE 0001 AT KNUST p.8
Fig. 17. WAsP Weibull Distribution Curve for Wind Speeds from July1 to                    September 30, 2011 for Site 0001 at KNUST
Fig. 17. WAsP Weibull Distribution Curve for Wind Speeds from July1 to September 30, 2011 for Site 0001 at KNUST p.8
Fig. 15. Time Series Graph of Wind Directions and Wind Speeds
Fig. 15. Time Series Graph of Wind Directions and Wind Speeds p.8
Table IV Comparison of the Directly Measured Monthly Average Wind Speeds Obtained for KNUST Site 0001 and Weather Underground Inc

Table IV

Comparison of the Directly Measured Monthly Average Wind Speeds Obtained for KNUST Site 0001 and Weather Underground Inc p.9
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

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 p.10
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

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 p.11
Table VII Results of Aventa AV-7 at an Average Wind Speed of 1.9 m/s measured at

Table VII

Results of Aventa AV-7 at an Average Wind Speed of 1.9 m/s measured at p.11
Table VIII Results of Fuhrlander FL 30 (30.0 kW) at an Average Speed of 1.9 m/s

Table VIII

Results of Fuhrlander FL 30 (30.0 kW) at an Average Speed of 1.9 m/s p.12