A preliminary study of wind power potential in Bahrain

Renewable Energy Vol. 3, No. 1. pp. 67 74. 1993 Printed in Great Britain.

0960-1481/93 $6.00+.00 Pergamon Press Ltd

TECHNICAL

NOTE

A preliminary study of wind power potential in Bahrain A. K. SOM and F. M. Ragab Physics Department, College of Science, University of Bahrain, P.O. Box 32038, State of Bahrain (Received 31 January 1991 ; accepted 2 March 1991)

Abstract--Several attempts have been made over the last ten years to evaluate the wind speed and the power potential in Bahrain. From our analysis of the wind data, an important characteristic is revealed in that the wind speed in summer months are more than that in winter months. This characteristic is opposite to the prevailing wind speed parameters in most European countries. In Bahrain the mean hourly wind speed can reach up to 7 m s ~ during the summer months compared to 3.8 m s- t during the winter. This paper also gives a detailed analysis of hourly wind speed variation with atmospheric pressure. The m a x i m u m and m i n i m u m mean power available each m o n t h are calculated as a function of the speed input. An evaluation was made of the kinetic energy density in kWh m 2 as a function of the wind speed of the 12 m o n t h period ot" the year 1990, and the output data were compared with the corresponding data for the period 1985 to 1987. The probability distribution function f ( v ) dv of wind speed together with the duration function T(v) were evaluated for winter and summer of the two periods. Weibull distribution was presented through calculating the scale parameter C(m s-~) and the dimensionless shape parameter K of the Weibull function. It appears from our analysis that the expected energy from the wind in Bahrain lies in the medium range which could be used as an alternative source of energy specially in the summer m o n t h s when the energy is most needed. However, an immediate application seems to be limited to water pumping and electric power generation using relatively small wind generators.

INTRODUCTION

is equal to 1.2mv~, where m is the mass of air passing through a volume 7"with speed vf (free stream velocity). Since m = pv (where p is the density of air), and the volume of air passing through an area A with speed ~f in a time t is Avrt then m = p A v f t and kinetic energy is

One of the alternative energy forms being considered today is wind power. Wind was exploited as a source of energy up to the time of industrial revolution. Windmills were used for pumping water and for grinding pulses and grains where only mechanical energy was employed. At the beginning of the twentieth century, attempts were made to generate electric power using windmills. However, major obstacles to the wider use of the energy were economic factors, since the fossil fuels were cheaper. During the seventies, because of the chronic energy crisis and increasing cost of fossil fuels, and the general awareness of pollution due to radiation from nuclear power plants and carbon and sulphur emissions from thermal power plants, scientists turned their attention to developing efficient wind generators for electric power production. Although wind is free and renewable, the power generating equipment is expensive and the electric power generation system is complex. Again, wind itself is stochastic ; wind flow is not to be expected all the time, there are also calm periods. Hence, alternative stand-by generators are necessary. Both wind and the power-generating equipment are pollution-free and do not cause any thermal load on the environment. However, an array of wind generators may cause both sonic and infrasonic noise and create interference in the path of frequency modulator waves.

K = l/2pA~'f~t,

Pin = d K / d t = 1/2pAy, ~.

(1)

To obtain the power extracted from the wind we assume that the rotor is replaced by a disc containing many blades which produces uniform changes in the velocity of the air passing through it. Let the velocity of the air acting on the rotor be vr and the velocity of air leaving the rotor v~, the wake velocity. Application of m o m e n t u m and energy relationships show that the effective average axial velocity at the disc, vr, is given by tTr = l/2(t'f+Vw)

(2)

that is, equal retardation of the flow is imposed upstream and downstream of the disc. The power output P from the disc can be expressed as the rate of extraction of kinetic energy from this flow, that is P = l/2pAvr(rl2--v~,)

(3)

but the velocity of the wind acting on the rotor is less than the input velocity t,~ = v~-(l-a)

AVAILABLE P O W E R A N D EXTRACTABLE POWER OF T H E W I N D

(4)

where a is called the axial interference factor, and therefore z,~ = e f ( 1 - 2 a ) .

The power in wind is equal to energy per unit time. The energy available [1] is the kinetic energy of the wind which

(5)

Substituting tr and z'w from equations (4) and (5) into (3) we 67

68

Technical Note

Table 1. Weibull distribution parameters for winter and summer seasons of Bahrain K

interval or duration, expecially when the speed is above the cut-in speed of the turbine. (iii) The mean wind power density.

C

Period

Winter

Summer

Winter

Summer

1985 1987 1990

1.96 2.06

2.1 2.16

6.28 6.96

7.17 7.65

The Weibull distribution is characterized by two parameters : the dimensionless shape parameter, k ; and the scale parameter C which has units similar to the speed (m/s). The probability density function for the wind velocity v is given by f ( v ) = (k/c)(v/c) k i exp [ - v / c y ' ]

(9)

where k and c are given by Putnam [5] as : k = 0.83(v) t/2'

get (6)

e = 2~r2pv~a(l--a) 2

where r is the radius of the blades. The maximum power output is obtained by equating the first derivative d P / d a to zero, giving a = 1/3. Substituting for a = (1/3) into eq. (6) we have: 8

Pmax = ~ ' r

2

3

pvf.

(10)

where v is the mean wind velocity and F is the gamma function. The values of k and c for the winter and summer seasons are listed in Table 1 for 1985-87 and 1990. The cumulative distribution of Weibull function is expressed as :

(7)

Pm,x 16 - 0.593 Pin 27

(11)

f ( v ) = i~'~f(v) dv = l - e x p [ - ( v / e ) k ] . do

Therefore the maximum theoretical efficiency should be t/-

~)]

c = v/[F(l+k

(8)

Accordingly, the number of hours in a year with v > v~ is given by : T(v) = 8760 exp [ - (v/cy']

which is the Betz's limit [2]. MATHEMATICAL ANALYSIS In order to evaluate the wind energy potential of any site, it is important to derive the expected probability distribution of the site's wind speed. Regarding this aspect much attention has been given to the Weibull function, which gives a good match with the experimental data according to Poje and Cividini [3] and Darwish and Sayigh [4]. The wind speed probability distribution is essential in wind energy studies, and can be used to evaluate :

(12)

where 8760 is the number of hours in one year. Using the above values of k and c for Bahrain for the winter (1985-1987) (1"96"] ( ~ Z ) ° f(v) = \6.28//

U

96 exp { - ( 6 ~ ) V

T(v) = 8760 exp { - (6_2~)

196

(21 (v y,

}

exp{-;i7}

Table 2. Power density (W m 2) and energy density (kWh m 2) of the wind for the twelve month period 1985-1987

Month

Max. ave. wind speed (m s ~)

Power density

Energy density

10 min. ave. wind speed (m s t)

Power density

Energy density

January February March April May June July August September October November December

5.54 6.62 6.59 6.17 6.76 7.58 6.28 4.72 4.66 5.55 5.16 5.88

102 174 172 141 185 261 149 63 60 102 82 122

75.88 116.92 127.96 101.52 137.64 187.92 110.85 46.87 43.2 75.88 59.04 90.76

3.23 3.77 4.11 3.43 4.93 4.25 3.49 2.64 2.61 3.05 2.96 3.79

20 32 42 24 72 46 26 11 10 17 15 32

14.88 21.5 31.24 17.28 51.84 34.22 19.34 8.18 7.2 12.64 10.8 23.8

(13)

1.96

and for the summer 1985-1987 :

(i) The capacity factor for a particular wind turbine generator used in producing any form of energy. (ii) The probability for the wind speed to lie in a certain

}

(14)

69

Technical Note Table 3. Power density (W m 2) and energy density (kWh m 2) of the wind for the twelve m o n t h period of 1990

Month January February March April May June July August September October November December

Max. ave. wind speed (m s - ~)

Power density

Energy density

10 min. ave. wind speed (m S 1)

Power density

Energy density

6.76 6.68 6.78 6.9 6.56 7.79 6.17 6.48 6.3 5.43 5.66

188.43 181.82 190.11 200.56 170.2 288.36 143.27 165.97 152.52 97.66 110.6

140.19 127.75 141.44 144.00 126.63 207.62 106.60 123.48 109.8I 72.65 79.632

4.01 3.36 3.22 3.38 3.29 3.74 2.87 2.85 2.7 2.66 2.33

39.33 23.14 20.36 23.55 21.72 31.9[ 14.42 14.12 12.00 10.72 7.71

29.26 15.55 15.55 16.96 16.16 22.98 10.72 10.5 8.64 7.96 5.55

Air d e n s i t y l . 2 2 k g m

V

3at25C.

21

where the value of v ranges from 1 to 12 m s ~ in our calculation. Similar distribution functions are obtained for the two seasons of 1990 by substituting the corresponding values of c and k given in Table 1 in equations (13)-(16).

at 10 a.m. Also, the m i n i m u m value of P corresponds to the m i n i m u m value o f v at 4 p.m. The m o n t h of June gives the m a x i m u m average value of wind speed v in Bahrain during any calendar year. Figure 3 shows the daily variation of m a x i m u m and m i n i m u m wind speed during June 1990. During this m o n t h peaks o f t occur

Table 4. Weibull distribution values W I N D DATA ANALYSIS The wind velocity data were obtained from the weather station on the roof of the physics block, University of Bahrain, at a height of 10 /~m from the ground. The data were averaged over one hour (referred to as the maximum) and averaged over 10 minutes (the minimum). Tables 2 and 3 give the power density (W m - 2) and energy density (kWh m 2) for each m o n t h of the year. Table 2 gives the data for 1985-1987 while Table 3 gives the same parameters for 1990. Table 4 gives the Weibull distribution function f(v)dv and the number of hours per year T(v) where t: > x for the two seasons during the periods 1985 1987 and 1990. It has been suggested that in order to get reliable data for wind speed, a statistical evaluation of 10 years' data should be made. However, we examined the wind speed data obtained by the meteorological office of Bahrain and compared our analysis with the results obtained by Alnaser [6] where the data obtained by the meteorological station were evaluated. Figures I and 2 demonstrate the diurnal variation of the m a x i m u m wind speed with the atmospheric pressure on 6 October 1990 and on 28 October 1990, respectively. The wind usually blows at varying speeds as a result of a change in the isobaric values of atmospheric pressure. It is shown, from Fig. 1, that the wind speeds which lie between 3.75 m s ~ and 11.75 m s ~correspond to an atmospheric pressure between 1008.2 m b and 1011.2 mb. It is also clear from the graph that the peaks of wind speed are correlated to the prevailing pressure difference during that day. The same pattern of v P behaviour is shown in Fig. 2 with reduced values of wind speed which do not exceed 9 m s '. The pressure varies between the values of 1009.25 mb and 1011.8 mb. The peak value of P corresponds to the peak value of v

Summer 1985/86/87

Summer 1990

Values of V

f(v)

T(v)

f(v)

T(v)

I 2 3 4 5 6 7 8 9 10 11 12

0.033 0.067125 0.09564 0.11488 0.12321 0.12098 0.1101933 0.093817 0.075016 0.056511 0.040192 0.027028

8621.18 8180.08 7461.35 6531.32 5480.06 4403.02 3384.94 2488.20 t747.81 1172.58 750.959 468.90

0.026326 0.056362 0.0835 0.104015 0.1167 0.117876 0.111572 0.098848 0.082361 0.06477 0.04809 0.033818

8652.57 8289.99 7673.76 6846.50 5877.37 4847.67 3837.12 2911.71 2116.26 1472.82 979.12 622.39

Winter [985/86/87 I 2 3 4 5 6 7 8 9 I0 11 12

0.052 0.0935 0.12138 0.13391 0.13226 0.0197 0.10053 0.07894 0.058224 0.04049 0.02661 0.01656

8523.00 7877.00 6924.70 5795.60 4622.00 3510.00 2542.50 1756.38 1156.86 727.12 436.11 249.64

Winter 1990 0.03715 0.073079 0.093425 0.11951 0.125648 0.12104 0.1082259 0.0905022 0.0711211 0.052691 0.036884 0.024435

8600.50 8113.87 7341.50 6364.25 5281.70 4193.86 3184.58 2311.58 1603.34 1063.34 672.20 406.07

70

Technical Note f l i

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0 1 2 3 4 5 6 7 8 9101112131415161718192021222324 Time (hr) Fig. 1. Hourly wind speed (m s- ') and pressure (mb), 6/10/90. 1 0 z2

0.8 0.6 0.4 0.2

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v}

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1 2 3 4 5 6 7 8 9101112131415161718192021222324 Time (hr) Fig. 2. Hourly wind speed (m s- ;) and pressure (mb), 28/10/90.

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1213141516171

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1920212223242526272

Days of the month Fig. 3. The daily wind speed for June in m s i, 1990.

'82'9

Technical Note

71

8 7 6 5

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Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec. Months of the year Fig. 4. Monthly wind speed over the period 1985-1987.

at different days with an average value of v = 7.79 m s ' which is above the cut-in values required for the operation of any turbine in Bahrain. Figure 4 shows the wind speed variation during each m o n t h of the period 1985 1987. The peaks of both parameters (maximum and m i n i m u m v) occur during June and May, respectively. During 9 m o n t h s of the year, V/> 5.5. m s ~ which is greater than the cut-in speed of the turbine. The average power density in W m 2 was calculated as a function of the prevailing average wind speed during the period 1985-1987 and the relationship is shown in Fig. (5). The graph represents the dependence of power P produced from the wind on the cube of the wind speed v 3. Values of P > 120 W m 2 could be obtained when r ~> 5.7

m s - ~, which is not far from the mean value of v during this period. Figure 6 gives the average wind power density and energy density produced from the wind during each m o n t h of 1990, with June having the peak value of nearly 190 k W h m 2 and October with the m i n i m u m value 72 k W h m 2. The m a x i m u m and m i n i m u m values of power density follow suit with 288 W m 2 during June and 96 W m - 2 during October. Figures 7 and 8 give the Weibull velocity distribution function for the summer of 1985 1987 and 1900. f(v) dv gives the probability for the wind speed to lie between v and (v+dv). The distribution function tends to zero after v = 12 m s ~. The two peaks occur at v between 5 m s - ~and 6 m s ' which

200 190

/-

180

E

t-

o

170 160 150 140 130 120 I10 100 90 80 70 60 50

/.

/

/

./

/ /

/

o•

/ 4

I

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5

6

7

8

Average wind speed (m/s) Fig. 5. Power of the wind averaged over three years (1985-1987).

72

Technical Note

i210 200 190 180 170 160 150 140 130 120 110 100 90 80 70

280 260 ~" 240

R i

I

I

Jan. Feb. Mar. Apr. May

e-

J

June July Aug. Sep. Oct. Nov. Dec.

Months of the year

Fig. 6. M a x i m u m wind power and energy density for Bahrain during 1990.

13 12 11

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9 8

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Wind speed (m/s) Fig. 7. Weibull velocity distribution function for summer 1985 1987 and 1990 for Bahrain.

14

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Wind speed (m/s) Fig. 8. Weibull velocity distribution function for winter 1985 1987 and 1990 for Bahrain.

Technical Note

:~

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3

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Wind speed (m/s) Fig. 9. The duration distribution curve for summer 1985 1987 and 1990 for Bahrain.

are the average velocities of the distribution. Figure 8 shows the distribution function f(v)dv for the two periods for winter. It is noticeable that the most probable velocities are less (4 m s ' and 5 m s ~) than the corresponding summer values, The duration distribution curves for summer 1985 1987 and 1990 are shown in Fig. 9 and those for winter in Fig. 10. T(v) or thousand hours in a year gives the duration as a function of velocity. For velocity 5 m s ' and higher during summer, the number of hours is 5500 for the first period and

6000 for the second. Figure 10 shows that the number of hours in a year during winter where wind speed is more than 5.5 m s ' (the annual mean wind speed) is approximately 4000, which is about 47% of the total hours per year. Wind energy is an indirect form of solar energy, as the winds result from the fact that the earth's equatorial regions receive more solar radiation than the polar regions, causing large-scale convection currents in the atmosphere. T h o u g h the detailed processes are complex, only about 1% of incident solar radiation is converted to wind energy by this method.

81 7

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Wind speed (m/s) Fig. I0. The duration distribution curve for winter 1985 1987 and 1990 for Bahrain.

Technical Note

74 DISCUSSION

The application of current technology to the design and construction of wind turbines led to rapid progress and it is now clear that most future applications of wind turbines will involve the generation of electricity. Where there is a utility electricity supply the output from the wind turbines can be fed into the supply network, permitting the partial shutdown of power stations and the saving of fuel. The value of the wind turbines output is then the value of the fuel saved. The technical feasibility of this mode of operation has already been demonstrated in the USA and some European countries, where hundreds of megawatts of wind turbine capacity have been installed. In remote locations, where the meain source of electricity is the diesel engine, wind turbines have many applications supplementing or replacing the diesel engine. For power levels above 10 kW it is usual to retain the diesel engine which provides the certainty of power on demand; the function of the wind turbine is then to save diesel fuel and to reduce the overall cost of energy delivered. At lower power levels wind turbines with battery storage may allow diesel engines to be eliminated altogether. Wind/ battery systems can be used in remote areas in a wide range of applications including for lighting, for radio and television receivers and for radio telephones. Wind systems in the l0 kW 100 kW range may be used on their own for irrigation, desalination and ice-making. The use of wind as an energy source requires that the cost of energy from the wind turbines be competitive with the cost of energy from conventional sources. Bahrain, being an island in the Arabian Gulf, is blessed with a high flux of daily solar energy and an average wind speed exceeding 5.5 m s annually. The state thus has the possibility of generating electricity using wind power; however, no attempt has yet been made to use wind turbines for electricity generation. The most important information needed for an assessment of a renewable energy source is the frequency of occurrence of each speed over the full range of wind speeds in the area swept by the blades of a wind generator. Wind power potential has not been thoroughly investigated. Two serious studies by Alnaser [6] and Abdulla [7] gave a comprehensive outline about the applicability of wind energy in Bahrain and the accompanying analysis of meteorological data about wind speed. Recently a significant study of Bahrain [8] showed average velocities of 6.1 m s (maximum) and 3.9 m s- ~ (minimum). These values are in agreement with those observed by us. Khallat et al. [9] evaluated the wind energy resources in Kuwait, and found values of v, f(v) dV and T(v) less than ours, although the shape off(v) and T(v) were similar in character. CONCLUSIONS in the past decade the development of wind turbines has progressed. Although the potential of wind energy as a

resource is large, because of its stochastic nature, wind turbines cannot provide continuous steady power. However, they play an important role in saving power. It has been shown that wind turbines operating in parallel with diesel engines can reduce fuel consumption by about 40%. From our study, wind energy can provide more than 1800 kWh m 2 annually, which is significant in generating electricity, and in desalination and water pumping projects. The power density obtained from wind in Bahrain can reach more than 280 W m 2 in June which is comparable to (and sometimes higher than) the power density in European countries, America or Canada. It is concluded here that the Weibull distribution is a suitable form to represent the probability of wind speed data for Bahrain, as a comprehensive study of wind power potential. This preliminary study could be considered as the basis for further research and development of the wind technology in the near future. Acknowledgements--The authors would like to express their sincere thanks to Mrs Sara Dawood for the special care she took in typing this manuscript and to Mr Adnan Jaffar for his kind assistance in drawing the graphs.

REFERENCES

1. A. K. Sore and V. J. Khoury, A laboratory investigation into the efficiency of a small wind generator. Energy Environment 3, 1764-69 (1990) ; Proc. First World Renewable Energy Congress (edited by A. A. M. Sayigh). Pergamon Press,Oxford (1990). 2. A. Betz, Windenergie Und lhre Anwendung Dutch Wind Muhlen. Vanderhoeck and Ruprecht, (36ttingen (1942). 3. D. Poje and B. Cividini, Assessment ofwind energy potential in Croatia. Solar Energy 41,543-554 (1988). 4. A. S. K. Darwish and A. A. M. Sayigh, Wind energy potential in Iraq. Solar Wind Technol. 5, 215--222 (1988). 5. P. C. Putnam, Power from the Wind. Van Nostrand, New York (1948). 6. W. E. Alnaser, Characteristics of the available wind energy in Bahrain. Solar Energy 43, 3-6 (1989). 7. Y. A. (3. Abdulla, New equations for predicting wind speed variation in Bahrain for the whole year and with different heights. Proc. 8th Miami International Conference on Alternative Energy Sources, Florida (1987). 8. (3. M. Feregh, A. S. K. Darwich and A. A. M. Sayigh, Wind energy potential for Bahrain. Proc. First World Renewable Energy Congress (edited by A. A. M. Sayigh). Pergamon Press, Oxford (1990). 9. M. K. Khallat, A. Y. Hassan and S. Rahman, Evaluation of wind energy resources in Bahrain. Energy Environment 3, 1775 1780 (1990); Proc. First WorM Renewable Energy Congress (edited by A. A. M. Sayigh). Pergamon Press, Oxford (1990).