- Email: [email protected]
Wind power energy potential at the northeastern region of Saudi Arabia
Renewable Energy, Vol. 14, Nos. 1-4, pp. 435-440, 1998
© 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain P l h S 0 9 6 0 - 1 4 8 1 (98) 0 0 1 0 0 - 1 0960-1481/98 $•9.00+0.00
Pergamon
WIND
POWER
ENERGY POTENTIAL REGION OF SAUDI
AT THE ARABIA
NORTHEASTERN
A h m e t Z. ~ahin* and A h m e t Aksakal** *Department of Mechanical Engineering, **The Research Institute, Division 4 King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
ABSTRACT In the present study the energy potential of wind for the Eastern Province of Saudi Arabia is investigated. A suitable Weibull distribution is generated based on the data obtained for a duration of one complete year at a costal location in northeastern Saudi Arabia. Comparison of this model is made with the Rayleigh distribution of wind power densities. Two horizontal-axis type of wind energy conversion systems which operate at fixed rpm are considered and a model of quadratic power output function is used. It is found that the error in using the Rayleigh approximation will be less than 10% of the full rated power density level. @ 1998 Elsevier Science Ltd. All rights reserved.
KEYWORDS
Windenergy;Weibullmodel;windenergysystems.
INTRODUCTION Geographical areas are rated in terms of wind power density avalibality. This is done using average .wind speeds considering diurnal and seasonal variations. Although, wind speeds are influenced strongly by local topographical features, in general, it is realized that certain geographical locations are higher wind energy areas. Feasibility study of any wind energy conversion system certainly includes the study of spatial, temporal and directional variation of wind speeds.This is a very difficult task because of the extreme transitions in speed and direction of wind at most sites. Estimation of the energy capture capabilitiy of a wind energy conversion system over long periods of time with a wide range of wind conditions depends on the operating conditions and performance characteristics of the wind energy conversion system. Because of the unsteady nature of the wind, it is impossible to develop a model and determine the transient response of the wind conversion system from wind speed and power output data. Thus, wind power generation will be closely related to the wind characteristics of the site even though the performance characteristics of the wind energy conversion system are available (Wortman, 1983). 435
436
A. Z. ~AHIN and A. AKSAKAL
Sahin (1994) studied the wind power output from a horizontal axis type of small wind energy conversion system rated at 100 kW at twenty sites based on an early study made by A1-Ansari et al. (1986). Percent rated power for each site was calculated for both Weibull and Rayleigh distributions. It is shown that east and west coast areas are potentially high wind energy areas. Whereas, minimal wind energy exists in the south and central parts of the country. Sahin and Yilbas (1994) studied wind power energy potential for the Dhahran site analytically. Generating electricity utilizing wind/solar energy in Saudi Arabia was studied by E1-Shobokshy and E1-Zayat (1991) and Nasser (1981). A comparative study on the availability of wind power and solar power on the East Coast of Saudi Arabia was made by A1-Sulaiman and J a m j o u m (1992). In a more recent study, Sahin (1995) studied the plant factor variation with installation height for a 100 kW wind energy conversion system. In this work, we attempted to determine the wind energy potential for the Eastern Province of Saudi Arabia based on the data obtained for a duration of one complete year at a costal location in northeastern Saudi Arabia. Measured and approximated wind speed probibility distributions by means of Weibull and Rayleigh models are compared. Two typical small type wind energy conversion systems are selected in order to compare the suitability of size of wind energy conversion systems for the northeastern region of Saudi Arabia.
WIND
ENERGY
POTENTIAL
The kinetic energy of air in wind may be expressed as
E
1
=
~mV
(1)
where m is the total mass of the air which moves through an area A within a period of time At and V is the wind speed. Since m = p A V A t then, E = ~pAV3At
(2)
p in equation (2) is the air density. The power of the wind therefore is
P-
E
1
At - 2 pAV3
(3)
and the wind power density becomes P
Pd = - ~ =
1
(4)
-~pV 3
The mean power density on the other hand is usually calculated by: 1
< Pd >= ~ < p > <
v z
>
(5)
where < p > and < V 3 > are the mean air density and the mean of the wind speed cubed for a given period of time. The Weibull probability density distribution function of the wind speed is:
exp[ where k is a dimensionless shape factor and c = < V > /F(1 + 1/k) is the scale factor in which F is the g a m m a function. The Weibull distribution reduces to the Rayleigh distribution for k = 2 which is obtained as:
p(V)n=
-~
exp
4:]
. (7)
Wind power energy potential
437
Table 1: The probability distribution of wind speeds.
Wind Speed Range (m/s) O< 1< 2< 3-< 4-< 5-< 6< 7< 8-<
V V V V V V V V V
<1 <2 <3 <4 <5 <6 <7 <8 <9
Occurance % of time 2.5635 8.0254 14.3418 19.3418 15.843 11.1547 7.7483 5.8545 4.2032
Wind Speed Occurance Range (m/s) % of time 9< V <10 10< V <11 11-< V <12 t2-< V <13 13_< V <14 14< V <15 15< V <16 16-< V <17
3.2217 2.9446 2.5058 1.3049 0.5658 0.3003 0.0692 0.0115
The probability distribution of wind speeds for the costal region m the northeastern Saudi Arabia is given in Table 1. In approximating of this data as Weibull probability distribution, the parameters that appear in equation (6) are determined in the following manner (Keoppl, 1982). Measured wind speed values in Table 1 are divided into intervals 0 - V1, V1 - V2, ..., Vn-1 - V~ that have frequencies f l , f2, • " , f~. For this case the cumulative frequencies are Pl = f l , P2 = Pl + f2, "" ", P~ = P~-I + fn and the transformation equations are xi = In V/ y~=ln[-ln(1-pl)]
(8) i= 1,2,..-,n
(9)
The linear approximation of this data is obtained using the least squares method, in the form 9 = mx + b. Thus the Weibull parameters are obtained as
,10/ The relative probability distribution of wind speeds is given in Fig. 1. The Weibull and Rayleigh appoximations of the data are also included for comparison. It can be shown (Keoppl, 1982) that the mean of the wind speed cubed that is the third moment of the distribution for the Weibull probability model is:
[ r(l+_ 3/k) ] < V3 > w = IF a (1 + l / k ) ] < V >a
(11)
Equations (11) and (5) can be used for determining the mean power density. For k = 2, equation (11) reduces to < va >n= ( 6 ) < V >3 (12) that gives the mean of the wind speed cubed for the Rayleigh approximation.
438
A.Z. ~AHIN and A. AKSAKAL 0.2 0.18
.
.
.
.
.
0.16
=- ffM-eTr
o 14
• WEIBULL
i
0.12 0.1
0.08
0.06 0.04 0.02
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Wind Speed (m/s)
Fig. 1. The relative probability distribution of wind.
Table 2: The characteristics of the wind energy conversion systems.
Cut-in speed, Vo (m/s) Rated speed, V~ (m/s) Cut-out speed, V~ (m/s)
Rated power, PT 100 kW 200 kW 3.6 4.25 8 10 26.8 17.9
WIND ENERGY CONVERSION Two horizontal axis type small wind energy conversion systems which operate at fixed rpm are considered in this study. These are rated as 100 kW and 200 kW and their characteristics are given in Table 2. These wind energy conversion systems correspond to those of NASA 1O0 kW and US Department of Energy's Mod-OA wind machines respectively. Power output approximation of this wind energy conversion system involves a quadratic modelling that approximates the output between cut-in and rated wind speeds as P(V) = A + BV + CV 2
(13)
where A,B, and C are constants. These are evaluated by solving the followind set of equations. A + BVo + CV~ = 0 A + BV~ + C V ) = Pr A +
+ CV: :
V,J P"
(14)
Wind power energy potential
439
Table 3: Mean power output of the wind energy conversion system.
Experiment Weibull Rayleigh
Rated power = 100 kW Mean Power % Rated < P > (kW) Power % error 34.08 34.08 32.90 32.90 3.46 37.43 37.43 9.83
where V~ = (V0 + V~)/2 and V0, V~ and
Pr are
Rated power = 200 kW Mean Power % Rated < P > (kW) Power % error 41.76 20.88 36.52 18.26 12.55 49.44 24.72 18.39
cut-in speed, rated speed and rated power respectively.
The mean power output, < P >, for the wind energy conversion system may be calculated using < P >=
P(V)f(V)dV
(15)
where f(V) is the wind speed probability distribution and V~ is the cut-out speed. Table 3 shows the mean power output of the above mentioned energy conversion systems for the experimental and the two approximate analytical models of wind speed probability distributions. It is found that the error in calculating the mean power output by using a 100 kW wind energy conversion system is less than 10 % in both cases. Weibull distribution yields lower errors, indicating that the Weibull approximation is a better approximation than Rayleigh approximation. Table 3 shows that smaller wind energy conversion system operates more efficiently, since % rated power output for 100 kW wind energy conversion system is much higher than that for 200 kW. This is because the smaller wind energy conversion system would operate for a longer period due to its lower cut-in speed. Monthly variation of wind power densities for the Dhahran site is studied (Sahin, 1994) and it is observed that the wind power density is higher during the summer months. Therefore, use of wind energy in this site appears to be appropriate in generation of electrical energy for space cooling. Figure 2 shows the directional characteristics of the wind in the northeastern Saudi Arabia. Both average wind speed (m/s) and occurance time (%) are high in the directions of North-West and NorthNorth-West. These are prevailing wind directions.
CONCLUSIONS The conclusions derived from this study can be summarized as follows: 1- Wind characteristics at a costal location in the northeastern part of Saudi Arabia were investigated and models were developed using Weibull and Rayleigh wind probability distributions. 2- Weibull approximation is found to be a better approximation than that of Rayleigb model. The error is obtained to be less than 10 per cent of the full rated power density level of a 100 kW wind energy conversion system using both Weibull and Rayleigh models. 3- Smaller wind energy conversion systems are more efficient for the wind conditions in this location. Wind power density available is higher during the summer months and the prevailing wind directions are North-West and North-North-West directions.
440
A.Z. SAHIN and A. AKSAKAL 18
!
7
l
~ Occurance (%) _ _ _ _ + A v e r a gspeed e (m/s)
]1 I
16 14
6
12 &
{D "u
5
A
10
._= o
o o
6
o
2
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Wind Direction Fig. 2. Directional characteristics of the wind.
ACKNOWLEDGMENT The authors acknowledge the support of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia for this work.
REFERENCES A1-Ansari, J. M., H. Bakhsh and I.K. Madni (1986). Wind Energy Atlas for the Kingdom of Saudi Arabia. KACST Report, Saudi Arabia. A1-Sulaiman F. A. and F.A. Jamjoum (1992). Applications of Wind Power on the East Coast of Saudi Arabia. Renewable Energy, 2, 47-55. E1-Shobokshy, M. S. and R.E. E1-Zayat (1991). Assessment of Electricity Generation by Wind Power in the Kingdom of Saudi Arabia. Int. J. of Ambient Energy, 12, 39-50. Keoppl, G. W. (1982). Putnam's Power from the Wind. Van Nostrand Reinhold, New York. Nasser, A. E. M. (1981). Utilization of Wind/Solar Energy in Generating Electricity in Saudi Arabia. In: Proc. of 16th Intersociety Energy Conversion Engineering Conference Atlanta, 2060-2063. Sahin, A. Z. (1994). Determination of Wind Energy Potential for Saudi Arabia. In: Proc. of World Renewable Energy Congress-III. Reading, UK. Sahin, A.Z. (1995). Estimation of Potential Power Output From Wind Energy Conversion System in Saudi Arabia. In: P~vc. of the Fourth Saudi Engineering Conference, Jeddah, Saudi Arabia. Sahin, A. Z. and B. S. Yilbas (1994). Study into Determination of Wind Power Energy Potential for the Eastern Province in Saudi Arabia. In: Proc. of Second Saudi Symposium on Energy, Utilization and Conservation. Dhahran, Saudi Arabia. Wortman, A. J. (1983). Introduction to Wind Turbine Engineering, Butterworths, Boston.
© 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain P l h S 0 9 6 0 - 1 4 8 1 (98) 0 0 1 0 0 - 1 0960-1481/98 $•9.00+0.00
Pergamon
WIND
POWER
ENERGY POTENTIAL REGION OF SAUDI
AT THE ARABIA
NORTHEASTERN
A h m e t Z. ~ahin* and A h m e t Aksakal** *Department of Mechanical Engineering, **The Research Institute, Division 4 King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
ABSTRACT In the present study the energy potential of wind for the Eastern Province of Saudi Arabia is investigated. A suitable Weibull distribution is generated based on the data obtained for a duration of one complete year at a costal location in northeastern Saudi Arabia. Comparison of this model is made with the Rayleigh distribution of wind power densities. Two horizontal-axis type of wind energy conversion systems which operate at fixed rpm are considered and a model of quadratic power output function is used. It is found that the error in using the Rayleigh approximation will be less than 10% of the full rated power density level. @ 1998 Elsevier Science Ltd. All rights reserved.
KEYWORDS
Windenergy;Weibullmodel;windenergysystems.
INTRODUCTION Geographical areas are rated in terms of wind power density avalibality. This is done using average .wind speeds considering diurnal and seasonal variations. Although, wind speeds are influenced strongly by local topographical features, in general, it is realized that certain geographical locations are higher wind energy areas. Feasibility study of any wind energy conversion system certainly includes the study of spatial, temporal and directional variation of wind speeds.This is a very difficult task because of the extreme transitions in speed and direction of wind at most sites. Estimation of the energy capture capabilitiy of a wind energy conversion system over long periods of time with a wide range of wind conditions depends on the operating conditions and performance characteristics of the wind energy conversion system. Because of the unsteady nature of the wind, it is impossible to develop a model and determine the transient response of the wind conversion system from wind speed and power output data. Thus, wind power generation will be closely related to the wind characteristics of the site even though the performance characteristics of the wind energy conversion system are available (Wortman, 1983). 435
436
A. Z. ~AHIN and A. AKSAKAL
Sahin (1994) studied the wind power output from a horizontal axis type of small wind energy conversion system rated at 100 kW at twenty sites based on an early study made by A1-Ansari et al. (1986). Percent rated power for each site was calculated for both Weibull and Rayleigh distributions. It is shown that east and west coast areas are potentially high wind energy areas. Whereas, minimal wind energy exists in the south and central parts of the country. Sahin and Yilbas (1994) studied wind power energy potential for the Dhahran site analytically. Generating electricity utilizing wind/solar energy in Saudi Arabia was studied by E1-Shobokshy and E1-Zayat (1991) and Nasser (1981). A comparative study on the availability of wind power and solar power on the East Coast of Saudi Arabia was made by A1-Sulaiman and J a m j o u m (1992). In a more recent study, Sahin (1995) studied the plant factor variation with installation height for a 100 kW wind energy conversion system. In this work, we attempted to determine the wind energy potential for the Eastern Province of Saudi Arabia based on the data obtained for a duration of one complete year at a costal location in northeastern Saudi Arabia. Measured and approximated wind speed probibility distributions by means of Weibull and Rayleigh models are compared. Two typical small type wind energy conversion systems are selected in order to compare the suitability of size of wind energy conversion systems for the northeastern region of Saudi Arabia.
WIND
ENERGY
POTENTIAL
The kinetic energy of air in wind may be expressed as
E
1
=
~mV
(1)
where m is the total mass of the air which moves through an area A within a period of time At and V is the wind speed. Since m = p A V A t then, E = ~pAV3At
(2)
p in equation (2) is the air density. The power of the wind therefore is
P-
E
1
At - 2 pAV3
(3)
and the wind power density becomes P
Pd = - ~ =
1
(4)
-~pV 3
The mean power density on the other hand is usually calculated by: 1
< Pd >= ~ < p > <
v z
>
(5)
where < p > and < V 3 > are the mean air density and the mean of the wind speed cubed for a given period of time. The Weibull probability density distribution function of the wind speed is:
exp[ where k is a dimensionless shape factor and c = < V > /F(1 + 1/k) is the scale factor in which F is the g a m m a function. The Weibull distribution reduces to the Rayleigh distribution for k = 2 which is obtained as:
p(V)n=
-~
exp
4
. (7)
Wind power energy potential
437
Table 1: The probability distribution of wind speeds.
Wind Speed Range (m/s) O< 1< 2< 3-< 4-< 5-< 6< 7< 8-<
V V V V V V V V V
<1 <2 <3 <4 <5 <6 <7 <8 <9
Occurance % of time 2.5635 8.0254 14.3418 19.3418 15.843 11.1547 7.7483 5.8545 4.2032
Wind Speed Occurance Range (m/s) % of time 9< V <10 10< V <11 11-< V <12 t2-< V <13 13_< V <14 14< V <15 15< V <16 16-< V <17
3.2217 2.9446 2.5058 1.3049 0.5658 0.3003 0.0692 0.0115
The probability distribution of wind speeds for the costal region m the northeastern Saudi Arabia is given in Table 1. In approximating of this data as Weibull probability distribution, the parameters that appear in equation (6) are determined in the following manner (Keoppl, 1982). Measured wind speed values in Table 1 are divided into intervals 0 - V1, V1 - V2, ..., Vn-1 - V~ that have frequencies f l , f2, • " , f~. For this case the cumulative frequencies are Pl = f l , P2 = Pl + f2, "" ", P~ = P~-I + fn and the transformation equations are xi = In V/ y~=ln[-ln(1-pl)]
(8) i= 1,2,..-,n
(9)
The linear approximation of this data is obtained using the least squares method, in the form 9 = mx + b. Thus the Weibull parameters are obtained as
,10/ The relative probability distribution of wind speeds is given in Fig. 1. The Weibull and Rayleigh appoximations of the data are also included for comparison. It can be shown (Keoppl, 1982) that the mean of the wind speed cubed that is the third moment of the distribution for the Weibull probability model is:
[ r(l+_ 3/k) ] < V3 > w = IF a (1 + l / k ) ] < V >a
(11)
Equations (11) and (5) can be used for determining the mean power density. For k = 2, equation (11) reduces to < va >n= ( 6 ) < V >3 (12) that gives the mean of the wind speed cubed for the Rayleigh approximation.
438
A.Z. ~AHIN and A. AKSAKAL 0.2 0.18
.
.
.
.
.
0.16
=- ffM-eTr
o 14
• WEIBULL
i
0.12 0.1
0.08
0.06 0.04 0.02
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Wind Speed (m/s)
Fig. 1. The relative probability distribution of wind.
Table 2: The characteristics of the wind energy conversion systems.
Cut-in speed, Vo (m/s) Rated speed, V~ (m/s) Cut-out speed, V~ (m/s)
Rated power, PT 100 kW 200 kW 3.6 4.25 8 10 26.8 17.9
WIND ENERGY CONVERSION Two horizontal axis type small wind energy conversion systems which operate at fixed rpm are considered in this study. These are rated as 100 kW and 200 kW and their characteristics are given in Table 2. These wind energy conversion systems correspond to those of NASA 1O0 kW and US Department of Energy's Mod-OA wind machines respectively. Power output approximation of this wind energy conversion system involves a quadratic modelling that approximates the output between cut-in and rated wind speeds as P(V) = A + BV + CV 2
(13)
where A,B, and C are constants. These are evaluated by solving the followind set of equations. A + BVo + CV~ = 0 A + BV~ + C V ) = Pr A +
+ CV: :
V,J P"
(14)
Wind power energy potential
439
Table 3: Mean power output of the wind energy conversion system.
Experiment Weibull Rayleigh
Rated power = 100 kW Mean Power % Rated < P > (kW) Power % error 34.08 34.08 32.90 32.90 3.46 37.43 37.43 9.83
where V~ = (V0 + V~)/2 and V0, V~ and
Pr are
Rated power = 200 kW Mean Power % Rated < P > (kW) Power % error 41.76 20.88 36.52 18.26 12.55 49.44 24.72 18.39
cut-in speed, rated speed and rated power respectively.
The mean power output, < P >, for the wind energy conversion system may be calculated using < P >=
P(V)f(V)dV
(15)
where f(V) is the wind speed probability distribution and V~ is the cut-out speed. Table 3 shows the mean power output of the above mentioned energy conversion systems for the experimental and the two approximate analytical models of wind speed probability distributions. It is found that the error in calculating the mean power output by using a 100 kW wind energy conversion system is less than 10 % in both cases. Weibull distribution yields lower errors, indicating that the Weibull approximation is a better approximation than Rayleigh approximation. Table 3 shows that smaller wind energy conversion system operates more efficiently, since % rated power output for 100 kW wind energy conversion system is much higher than that for 200 kW. This is because the smaller wind energy conversion system would operate for a longer period due to its lower cut-in speed. Monthly variation of wind power densities for the Dhahran site is studied (Sahin, 1994) and it is observed that the wind power density is higher during the summer months. Therefore, use of wind energy in this site appears to be appropriate in generation of electrical energy for space cooling. Figure 2 shows the directional characteristics of the wind in the northeastern Saudi Arabia. Both average wind speed (m/s) and occurance time (%) are high in the directions of North-West and NorthNorth-West. These are prevailing wind directions.
CONCLUSIONS The conclusions derived from this study can be summarized as follows: 1- Wind characteristics at a costal location in the northeastern part of Saudi Arabia were investigated and models were developed using Weibull and Rayleigh wind probability distributions. 2- Weibull approximation is found to be a better approximation than that of Rayleigb model. The error is obtained to be less than 10 per cent of the full rated power density level of a 100 kW wind energy conversion system using both Weibull and Rayleigh models. 3- Smaller wind energy conversion systems are more efficient for the wind conditions in this location. Wind power density available is higher during the summer months and the prevailing wind directions are North-West and North-North-West directions.
440
A.Z. SAHIN and A. AKSAKAL 18
!
7
l
~ Occurance (%) _ _ _ _ + A v e r a gspeed e (m/s)
]1 I
16 14
6
12 &
{D "u
5
A
10
._= o
o o
6
o
2
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Wind Direction Fig. 2. Directional characteristics of the wind.
ACKNOWLEDGMENT The authors acknowledge the support of King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia for this work.
REFERENCES A1-Ansari, J. M., H. Bakhsh and I.K. Madni (1986). Wind Energy Atlas for the Kingdom of Saudi Arabia. KACST Report, Saudi Arabia. A1-Sulaiman F. A. and F.A. Jamjoum (1992). Applications of Wind Power on the East Coast of Saudi Arabia. Renewable Energy, 2, 47-55. E1-Shobokshy, M. S. and R.E. E1-Zayat (1991). Assessment of Electricity Generation by Wind Power in the Kingdom of Saudi Arabia. Int. J. of Ambient Energy, 12, 39-50. Keoppl, G. W. (1982). Putnam's Power from the Wind. Van Nostrand Reinhold, New York. Nasser, A. E. M. (1981). Utilization of Wind/Solar Energy in Generating Electricity in Saudi Arabia. In: Proc. of 16th Intersociety Energy Conversion Engineering Conference Atlanta, 2060-2063. Sahin, A. Z. (1994). Determination of Wind Energy Potential for Saudi Arabia. In: Proc. of World Renewable Energy Congress-III. Reading, UK. Sahin, A.Z. (1995). Estimation of Potential Power Output From Wind Energy Conversion System in Saudi Arabia. In: P~vc. of the Fourth Saudi Engineering Conference, Jeddah, Saudi Arabia. Sahin, A. Z. and B. S. Yilbas (1994). Study into Determination of Wind Power Energy Potential for the Eastern Province in Saudi Arabia. In: Proc. of Second Saudi Symposium on Energy, Utilization and Conservation. Dhahran, Saudi Arabia. Wortman, A. J. (1983). Introduction to Wind Turbine Engineering, Butterworths, Boston.