Wind Data Collection and Analysis in Kumasi - IJENS · Wind Data Collection and Analysis in Kumasi ... the analysis of both internally binned wind data stored in a Wind Explorer™

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



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



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



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



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



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



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.



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



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.



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



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



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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Wind Data Collection and Analysis in Kumasi - IJENS · Wind Data Collection and Analysis in Kumasi ... the analysis of both internally binned wind data stored in a Wind Explorer™