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Wind energy resource assessment for five locations in Saudi Arabia
Renewable Energy 30 (2005) 1489–1499 www.elsevier.com/locate/renene
Wind energy resource assessment for five locations in Saudi Arabia Naif M. Al-Abbadi* Energy Research Institute, King Abdulaziz City for Science and Technology, KACST, P.O. Box 6086, Riyadh 11442, Saudi Arabia Received 13 August 2004; accepted 16 November 2004 Available online 18 December 2004
Abstract The analysis of recently collected wind data at five sites in Saudi Arabia namely, Dhulum, Arar, Yanbu, Gassim and Dhahran is presented. The five sites represent different geographically and climatologically conditions. The data collected over a period spanned between 1995 and 2002 with different collection periods for each site. Daily, monthly and frequency profiles of the wind speed at the sites showed that Dhulum and Arar sites have higher wind energy potential with annual wind speed average of 5.7 and 5.4 m/s and speeds higher than 5 m/s for 60 and 47% of the time, respectively. The two sites are candidates for remote area wind energy applications. The costal site’s, i.e. Yanbu and Dhahran wind speed data indicated that the two sites have lower annual wind speed averages and wind blows at speed higher than 5 m/s during afternoon hours. That makes the two sites candidates for grid connected wind systems for electrical load peak shaving. The data of Gassim site showed that the site has the lowest wind energy potential compared to the others. The annual energy produced by a Nordex N43 wind machine is estimated to be 1080, 990, 730, 454 and 833 MWh for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. The analysis showed that the estimated annual energy produced by the machine based on 10 min averaged data is 2.5% higher than the estimated energy based on 30 min averaged data. q 2004 Elsevier Ltd. All rights reserved. Keywords: Saudi Arabia; Wind data; Wind resources assessment; Wind power density; Wind rose; Wind energy
* Corresponding author. Tel.: C966 1 481 3487; fax: C966 1 481 3441. E-mail address: [email protected] 0960-1481/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.renene.2004.11.013
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1. Introduction Technological advances in windmill design and construction have made the production of electricity through wind power a highly efficient an economically viable process as well as the world’s fastest growing form of electricity production. For an economical utilization of wind energy wind resources at prospective sites must be investigated. For that purpose King Abdulaziz City for Science and Technology (KACST) has taken the initiative in regard to wind resource assessment in the Kingdom of Saudi Arabia. The wind resource assessment project aimed to record the wind data in different locations of the country to investigate its availability and assess the wind power for economical production of electricity specifically, in remote areas [1,2]. KACST preceded this effort by publishing the Saudi Arabian Wind Energy Atlas. The atlas was generated by a research project implemented under the framework of the Saudi Arabia–United States Joint Program for Cooperation in the field of Solar Energy (SOLERAS) [3]. Wind speed data collected at airport metrological stations was used in the atlas generation. This paper reports the analysis of recently collected wind data at five locations in Saudi Arabia. The locations are Dhulum, Arar, Yanbu, Gassim and Dhahran. The five locations represent different geographical and climatological conditions. The analysis of wind speed, direction, power density and energy at the five sites are presented.
2. Wind energy in Saudi Arabia The recent worldwide development of wind energy has encouraged the scientific and research community in Saudi Arabia to launch a series of investigations to study wind energy potential in the country. One of the earliest works was the development of the wind energy atlas for Saudi Arabia [3]. The atlas was based on wind data collected at 20 airport metrological stations for the period of 1970–1982. The atlas shows profiles of wind speed and power, analyzes the diurnal variation of mean speeds and frequency distribution of wind directions, and presents the contours of mean wind speeds. Most of the investigations which followed were based on the atlas data. In this paper a review of some of the related published works are presented. Radhwan [4] used meteorological data from the 20 weather stations of the atlas for 10 years to analyze wind pattern and characteristics in remote areas of Saudi Arabia. He found that the annual average wind velocity distribution and frequency of occurrences were significant factors in assessing the wind power potential of a certain site. The analysis of the data revealed that the potential of wind power was promising in the northern and coastal sites. Consequently, he recommended that small desalination units, irrigation pumps and electrical power generators could be powered by wind energy. Rehman et al. [5] presented an assessment of wind power cost per kWh of electricity produced using three types of wind electric conversion systems at the 20 locations. Hourly values of wind speed recorded for periods of 5.5–13 years (between 1970–1982, in most cases) were used for all 20 locations. Wind duration curves were developed and utilized to calculate the cost per kWh of electricity generated from three chosen wind machines.
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Rehman [6] presented a long-term wind data analysis in terms of annual, seasonal and diurnal variations at Yanbu, which is located on the west coast of Saudi Arabia. The wind speed and wind direction hourly data for a period of 14 years between 1970 and 1983 was used in the analysis. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 5.0 m/s and more were observed during the summer months of the year and noon hours (09:00–16:00 h) of the day. Wind energy calculations were performed using wind machines of different sizes. Shaahid and Elhadidy [7] analyzed hourly mean wind speed and solar radiation for the most of the period of 1987–1990 recorded at Dhahran and report the monthly variation of wind speed and solar radiation. They found that monthly average wind speeds were between 4.46 and 6.89 m/s and solar radiation varies from 3.46 to 7.43 kWh/m2. They reported the annual attainable wind potential per unit area of the wind stream is 543 kWh/ m2/year and the annual solar potential per unit area of the earth surface is 2.03 MWh/m2/ year. Alawaji [1] discussed a research program supported by the Energy Research Institute of the King Abdulaziz City for Science And Technology to study the potential of wind energy in Saudi Arabia. He presented a full description of the equipment, instruments, site specifications and other technical needs of the monitoring network to assess wind energy in Saudi Arabia. Similarly, Alabbadi et al. [2] presented preliminary analysis of 1 year wind data for three different sites of the network located in the central, northern and eastern region of Saudi Arabia. Statistical moments and frequency distribution were generated for the wind speed and direction parameters to analyze the wind energy characteristics and its availability. Also, the paper demonstrates the lessons learned from operating wind assessment stations installed in remote areas having different environmental characteristics. Sahin and Aksakal [8,9] investigated the wind energy potential for the north eastern and eastern region of Saudi Arabia based on a complete year data at coastal locations. Suitable Weibull distributions were generated and comparisons were made with the Rayleigh distributions of wind power densities. They considered two horizontal-axis type of conversion system operating at fixed rpm in order to determine the extractable wind power. Furthermore, they concluded that small-scale wind energy systems were suitable in the eastern part of Saudi Arabia for power generation and irrigation purposes.
3. Wind station sites and hardware Details of the location information of the five sites selected for the subject of this paper are shown in Table 1. A wind station generally comprises a tower, sensors and a data acquisition system. The tower is a steel tube having a length of 40 m. Wind speed sensors are installed at heights 40, 30 and 20 m. Each height has two sensors. In the case of one sensor failing, the other still operates, thus, ensuring continuous data collection. Wind direction sensors are also installed at two heights, 30 and 40 m. Two sensors are installed for the abovementioned reason. Other meteorological sensors measuring global solar
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Table 1 Wind stations location information Site
Latitude (deg N)
Longitude (deg E)
Elevation (m)
Data collection period
Arar Dhahran Dhulum Gassim Yanbu
30.8 26.1 22.74 26.3 23.9
41.3 50.1 42.18 43.97 38.3
550 3 1117 648 11
Jun 6, 1995–Dec 31,1998 Oct 4, 1995–Nov 30,2000 Nov 1, 1998–Oct 12,2002 Dec 5, 1995–Oct 24, 1998 Sep 17,1996–Oct 21,1999
radiation, ambient temperature, relative humidity and barometric pressure are also configured to the wind station [1]. The data acquisition system is a mini computer which can be programmed to have data averaging interval of a minimum of 1 min to a maximum of 1 h. The averaged data were stored in a data card and retrieved from the site periodically. The data acquisition system is powered by a two 6 V, 3.8 Ah battery charged by a 10 W amorphous silicon photovoltaic panel. For safety the tower is equipped with an obstruction light installed on top of it and powered by the utility grid or from a photovoltaic power system depending on the remoteness of the site [1].
4. Results and discussion The data acquisition systems in all stations were programmed to store data (averaging interval) every 30 min. This averaging interval was chosen to maximize data collection and minimize site visits; one site visit every 3 months for data retrieval and station hardware maintenance. To asses the effect of averaging interval on the energy production of a wind conversion system, 10-min and 30-min averages were used in Yanbu station for 1 year during the data collection period, i.e. July 1998–June 1999. The annual energy production calculated based on the two averaging intervals was compared. For the other analysis presented in the paper the 10-min data were reduced to 30-min averaging. 4.1. Overall monthly variation of wind speed and wind power density The overall monthly variation of mean wind speed and wind power density provides information on the availability of wind during different months of the year. The overall monthly maximum and mean values of half-hourly wind speed at 40 m height during the collection periods are summarized in Table 2. The table also shows the corresponding mean values of wind power densities. The table shows that Dhulum has the highest annual mean wind speed of 5.7 m/s followed by Arar with a value of 5.4 m/s. These two sites are quite remote and have isolated, scattered and low population areas which increase the economical feasibility of utilizing wind energy at these locations. Furthermore, the monthly means wind speed for Dhulum were 5.7 m/s or more for 10 months of the year reaching above 6.5 m/s for few months of the year. For Arar the monthly means were 5.4 m/s or more for 5 months and more than 5 m/s for 10 months of the year. At the two
Table 2 Overall monthly half-hourly wind speeds (m/s) and power density for the five stations during the collection periods at 40 m above the ground Dhulum
Arar
Wind speed (m/s)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
Max
Mean
17.4 22.7 23.9 19.6 20 15.1 23.7 17.2 16.6 16.5 16.4 17.3 23.7
6.1 6.6 6.7 5.9 5.7 5.8 6.5 5.8 5 5 5.7 5.8 5.7
Power density (W/m2) 197 249 278 197 176 165 226 166 114 109 175 178 186
Yanbu
Wind speed (m/s) Max
Mean
16.4 15.2 19.2 18.6 20.7 14.6 15 12.5 18.2 16.5 16.2 20.1 20.7
5.2 5.1 6.1 5.7 5.4 5.8 6.3 5.3 5 5.1 4.5 4.9 5.4
Power density (W/m2) 142 159 241 200 182 181 211 148 129 143 107 125 164
Gassim
Wind speed (m/s) Max
Mean
14.4 15.4 15.2 15.1 14.2 14.7 14.4 15.1 14.4 12.8 17.2 14.3 17.2
4.7 4.9 5.3 5.1 4.9 4.7 4.7 4.9 4.8 4.6 4.3 4 4.7
Power density (W/m2) 122 149 184 178 142 137 142 152 130 96 95 76 134
Dhahran
Wind speed (m/s) Max
Mean
12.9 13.5 15.3 17.5 22.7 11.5 12.3 11.1 10.9 11.4 11.5 12.3 22.7
4.3 4.8 4.9 4.9 4.3 4.3 4.3 4 3.9 4.1 3.9 4.1 4.3
Power density (W/m2) 78 104 125 125 91 72 73 57 55 66 63 68 81
Wind speed (m/s) Max
Mean
15.8 15.8 16.2 19.2 19.3 16.1 18.5 15 16.5 13.1 16.2 13.2 19.3
5.2 5.7 5.8 5.9 5.2 5.7 5.7 5.1 4.8 4.7 5 4.9 5.3
Power density (W/m2) 145 179 197 207 151 200 188 137 114 95 123 112 154
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sites the wind speed is higher during the summer months when electrical load is high at such hot arid climates. Wind speeds at Yanbu and Gassim sites behaved in lower figures with annual mean wind speeds of 4.7 and 4.3 m/s, respectively. While at the other site, i.e. Dhahran behaved in between of annual wind speed of 5.3 m/s. The annual mean wind power density are 186, 164, 134, 81, 154 w/m2 for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. 4.2. Diurnal variation of wind speed The overall diurnal variation of wind speed with time is important when assessing confidence about availability of wind during different hours of the day. The diurnal halfhourly mean values of wind speed are calculated using the entire data set for the five stations and results are summarized in Fig. 1. The five sites experienced different diurnal wind speed behavior that can be characterized in three behaviors. The costal sites, i.e. Yanbu and Dhahran experienced similar characteristic where wind speed peaks during the hour’s 13:00–18:00 h. That makes wind energy a potential tool for electrical peak shaving during the hours of air conditioning demand load. In Yanbu the wind speed stayed above 7 m/s for 4 h (17%) of the day, above 6 m/s for 6 h of the day (25%) and above 5 m/s for 9 h of the day (38%). In Dhahran wind speed stayed above 6 m/s for 5 h (21%) and above 5 m/s for 10 h (42%) during the day. Fig. 1 shows similar profiles for Gassim and Dhulum. These sites are located in the mid and mid-south of the country. At these sites the wind speed peaks twice, the highest peak occurs around midnight and the second occurs during late morning hours (8:00– 12:00). The data show that Dhulum has good wind energy potential as the wind speed stayed above 5 m/s almost during the entire day and above 6 m/s for nearly 6 h, i.e. 25% of the day.
Fig. 1. Diurnal profiles for the five sites at 40 m above the ground.
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Wind speed profile of the other site, i.e. Arar, showed peculiar behavior compared to the others. The wind speed peaks during night hours with values above 6 m/s. Even though, the lowest speed occurs at mid day, it stays above 5 m/s for nearly the entire day. 4.3. Wind speed frequency distribution and wind rose In order to obtain information about the number of hours during which the wind remained in a certain wind speed bin, the frequency distribution analysis was carried out for the half-hourly recorded data at 40 m above the ground for the five sites. The wind rose provides information about the occurrence of number of hours during which wind remained in a certain wind speed bin in a particular wind direction. In other words, a wind rose provides information on the relative wind speeds in different wind directions. The wind roses were constructed using the measurements of wind speeds and corresponding wind directions. Like wind speed, wind roses also vary from one location to the other and are known as a form of meteorological fingerprint. Hence, a close look at the wind rose and understanding its message correctly is extremely important for siting wind machines. So, if a large share of wind comes from a particular direction then the wind machines should be put against this direction. In order to construct wind roses and analyze the frequency distribution, all half hourly averaged values of wind speed and wind direction were used. Fig. 2 and Table 3 show the wind rose chart and percentage of time the wind speed stayed at the different speed pins for the five sites. All the half-hourly data recorded at height 40 m above ground was used for the generating of Fig. 2 and Table 3. Fig. 2 depicts that the wind blows predominately from southeast, northwest, north, north to northeast and north to northwest at Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. Table 3 shows that Dhulum site has the highest wind energy potential and wind blows at speed higher than 5 m/s for 60% and higher than 8 m/s for 21% of the time. At the sites of Arar, Dhahran and Yanbu, the wind speed blows higher than 5 m/s for 47, 42 and 40% of the time, respectively. The table shows that Gassim has the lowest wind energy potential among the other site with wind blowing at speed higher than 5 m/s for only 34% of the time. 4.4. Wind energy calculations The annual energy that can be generated at the five sites by a Nordex N43/600 wind machine was obtained using wind power curve of the machine [10] and 1 year wind duration data recorded at the sites. The technical data of the wind machine used is summarized in Table 4. Since the hub heights of the wind machine is 50 m, the half-hourly mean wind speed values were calculated at that height using 1/7th power law. Fig. 3 shows a comparison of the annual energy that can be generated using the Nordex N43. It shows that at Dhulum site, the calculated annual energy is about 1080 and 990 MWh at Arar. For Dhahran and Yanbu the annual energy are 833, 730 MWh, respectively, while at Gassim site the Nordex N43 will only produce about 454 MWh.
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Fig. 2. Wind rose charts for the five sites at 40 m above the ground.
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Table 3 Wind speed percent distribution at different speed pins at 40 m above the ground for the five sites Site Dhulum Arar Yanbu Gassim Dhahran
Wind speed pins O0–2.9
O2.9–4
O4–5
O5–6
O6–7
O7–8
O8.1
14 30 32 27 32
12 11 15 21 13
14 11 13 18 14
14 12 11 14 13
13 12 9 9 11
11 10 7 5 7
21 14 12 5 11
4.5. Wind energy comparison for 10-min and half-hourly average data As mentioned earlier, 1 year 10 min averaged data recorded at Yanbu site was used to estimate the percentage variation in the annual energy output of the wind energy machine for the 10-min and half-hourly average (of 10-min) data. The analysis showed that using 10-min data resulted in 2.5% more energy compared to the energy calculated from the half-hourly averaged data. Therefore, it can be stated that an increased output of wind energy can be expected from wind machines while in operation compared to the energy calculated using half-hourly or hourly data. Table 4 Technical data of wind machines from Nordex N43/600 Cut-in speed (m/s) Cut-out speed (m/s) Rated speed (m/s) Survival speed (m/s) Rated output (kW) Hub height (m) Rotor diameter (m)
3 25 13.5 70 600 50 43
Fig. 3. The annual wind energy produced by the Nordex N43 at the sites.
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5. Concluding remarks The paper discussed the analysis of wind energy potential at five sites in the Kingdom of Saudi Arabia. The data used in the calculation are published for the first time and collected for the purpose of studying the wind energy potential in these sites. The site of Dhulum has the highest wind energy potential compared to the other sites with annual wind speed average of 5.7 m/s and with wind speed higher than 5.0 m/s for about 60% of the time. The site of Arar is the second in wind energy potential with annual average wind speed of 5.4 m/s and with wind speed higher than 5.0 m/s for about 47% of the time. The two sites have isolated, scattered and low population areas that increase the economical feasibility of utilizing wind energy at these locations for remote area applications. The estimated energy that can be produced from a Nordex N43 is 1080 and 990 MWh at Dhulum and Arar, respectively. At the costal sites namely, Yanbu and Dhahran, the wind blows at speed higher that 5 m/s during afternoon hours peaking to 8 and 7 m/s at Yanbu and Dhahran, respectively. Hence, grid connected wind energy systems will be candidate tools for electrical load peak shaving at the two sites. Although, Gassim site has the lowest annual average wind speed but wind blows higher than 3 m/s for 73% of the time. Therefore, barely adequate potential for the use of wind machine with low rated wind speed is available at this site. The output of wind energy machine is expected to be higher while in operation compared to the energy calculated using half-hourly or hourly data.
Acknowledgements The author acknowledges the Energy Research Institute of the king Abdulaziz city for Science and Technology for the financial support of the wind energy resource assessment project.
References [1] Alawaji SH. Wind energy resource assessment in Saudi Arabia-I network design and description. Renew Energy 1996;7(4):319–28. [2] Al-Abbadi NM, Alawaji SH, Eugenio NN. Wind energy resource assessment in Saudi Arabia; a three year experience. Proceedings, annual conference of the American Wind Energy Association, Austin, TX; 1997 p. 533–41. [3] Al-Ansari JM, Bakhsh H, Madni KI. Wind energy atlas for the kingdom of Saudi Arabia. Riyadh, Saudi Arabia: KACST; 1986. [4] Radhwan AM. Wind energy applications in remote areas of Saudi Arabia. Int J Ambient Energy 1994;15(3): 123–30. [5] Rehman S, Halawani TO, Mohandes M. Wind power cost assessment at twenty locations in the Kingdom of Saudi Arabia. Renew Energy 2003;28:573–83. [6] Rehman S. Wind energy resources assessment for Yanbo, Saudi Arabia. Energy Convers Manage 2003; 14(13–14):2019–32.
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[7] Shaahid SM, Elhadidy MA. Wind and solar energy at Dhahran, Saudi Arabia. Renew Energy 1994;4(4): 441–5. [8] Sahin AZ, Aksakal A. Wind power energy potential at the north–eastern region of Saudi Arabia. Renew Energy 1998;4(1–4):435–40. [9] Sahin AZ, Aksakal A. Statistical analysis of wind energy potential at the eastern region of Saudi Arabia. Int J Energy Res 1999;23(10):909–17. [10] Nordex Publication, N43/600 kW technical description document, Rev. 2003; http://www.nordex-online. com/_e/produkte_und_service/index.htm1
Wind energy resource assessment for five locations in Saudi Arabia Naif M. Al-Abbadi* Energy Research Institute, King Abdulaziz City for Science and Technology, KACST, P.O. Box 6086, Riyadh 11442, Saudi Arabia Received 13 August 2004; accepted 16 November 2004 Available online 18 December 2004
Abstract The analysis of recently collected wind data at five sites in Saudi Arabia namely, Dhulum, Arar, Yanbu, Gassim and Dhahran is presented. The five sites represent different geographically and climatologically conditions. The data collected over a period spanned between 1995 and 2002 with different collection periods for each site. Daily, monthly and frequency profiles of the wind speed at the sites showed that Dhulum and Arar sites have higher wind energy potential with annual wind speed average of 5.7 and 5.4 m/s and speeds higher than 5 m/s for 60 and 47% of the time, respectively. The two sites are candidates for remote area wind energy applications. The costal site’s, i.e. Yanbu and Dhahran wind speed data indicated that the two sites have lower annual wind speed averages and wind blows at speed higher than 5 m/s during afternoon hours. That makes the two sites candidates for grid connected wind systems for electrical load peak shaving. The data of Gassim site showed that the site has the lowest wind energy potential compared to the others. The annual energy produced by a Nordex N43 wind machine is estimated to be 1080, 990, 730, 454 and 833 MWh for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. The analysis showed that the estimated annual energy produced by the machine based on 10 min averaged data is 2.5% higher than the estimated energy based on 30 min averaged data. q 2004 Elsevier Ltd. All rights reserved. Keywords: Saudi Arabia; Wind data; Wind resources assessment; Wind power density; Wind rose; Wind energy
* Corresponding author. Tel.: C966 1 481 3487; fax: C966 1 481 3441. E-mail address: [email protected] 0960-1481/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.renene.2004.11.013
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1. Introduction Technological advances in windmill design and construction have made the production of electricity through wind power a highly efficient an economically viable process as well as the world’s fastest growing form of electricity production. For an economical utilization of wind energy wind resources at prospective sites must be investigated. For that purpose King Abdulaziz City for Science and Technology (KACST) has taken the initiative in regard to wind resource assessment in the Kingdom of Saudi Arabia. The wind resource assessment project aimed to record the wind data in different locations of the country to investigate its availability and assess the wind power for economical production of electricity specifically, in remote areas [1,2]. KACST preceded this effort by publishing the Saudi Arabian Wind Energy Atlas. The atlas was generated by a research project implemented under the framework of the Saudi Arabia–United States Joint Program for Cooperation in the field of Solar Energy (SOLERAS) [3]. Wind speed data collected at airport metrological stations was used in the atlas generation. This paper reports the analysis of recently collected wind data at five locations in Saudi Arabia. The locations are Dhulum, Arar, Yanbu, Gassim and Dhahran. The five locations represent different geographical and climatological conditions. The analysis of wind speed, direction, power density and energy at the five sites are presented.
2. Wind energy in Saudi Arabia The recent worldwide development of wind energy has encouraged the scientific and research community in Saudi Arabia to launch a series of investigations to study wind energy potential in the country. One of the earliest works was the development of the wind energy atlas for Saudi Arabia [3]. The atlas was based on wind data collected at 20 airport metrological stations for the period of 1970–1982. The atlas shows profiles of wind speed and power, analyzes the diurnal variation of mean speeds and frequency distribution of wind directions, and presents the contours of mean wind speeds. Most of the investigations which followed were based on the atlas data. In this paper a review of some of the related published works are presented. Radhwan [4] used meteorological data from the 20 weather stations of the atlas for 10 years to analyze wind pattern and characteristics in remote areas of Saudi Arabia. He found that the annual average wind velocity distribution and frequency of occurrences were significant factors in assessing the wind power potential of a certain site. The analysis of the data revealed that the potential of wind power was promising in the northern and coastal sites. Consequently, he recommended that small desalination units, irrigation pumps and electrical power generators could be powered by wind energy. Rehman et al. [5] presented an assessment of wind power cost per kWh of electricity produced using three types of wind electric conversion systems at the 20 locations. Hourly values of wind speed recorded for periods of 5.5–13 years (between 1970–1982, in most cases) were used for all 20 locations. Wind duration curves were developed and utilized to calculate the cost per kWh of electricity generated from three chosen wind machines.
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Rehman [6] presented a long-term wind data analysis in terms of annual, seasonal and diurnal variations at Yanbu, which is located on the west coast of Saudi Arabia. The wind speed and wind direction hourly data for a period of 14 years between 1970 and 1983 was used in the analysis. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 5.0 m/s and more were observed during the summer months of the year and noon hours (09:00–16:00 h) of the day. Wind energy calculations were performed using wind machines of different sizes. Shaahid and Elhadidy [7] analyzed hourly mean wind speed and solar radiation for the most of the period of 1987–1990 recorded at Dhahran and report the monthly variation of wind speed and solar radiation. They found that monthly average wind speeds were between 4.46 and 6.89 m/s and solar radiation varies from 3.46 to 7.43 kWh/m2. They reported the annual attainable wind potential per unit area of the wind stream is 543 kWh/ m2/year and the annual solar potential per unit area of the earth surface is 2.03 MWh/m2/ year. Alawaji [1] discussed a research program supported by the Energy Research Institute of the King Abdulaziz City for Science And Technology to study the potential of wind energy in Saudi Arabia. He presented a full description of the equipment, instruments, site specifications and other technical needs of the monitoring network to assess wind energy in Saudi Arabia. Similarly, Alabbadi et al. [2] presented preliminary analysis of 1 year wind data for three different sites of the network located in the central, northern and eastern region of Saudi Arabia. Statistical moments and frequency distribution were generated for the wind speed and direction parameters to analyze the wind energy characteristics and its availability. Also, the paper demonstrates the lessons learned from operating wind assessment stations installed in remote areas having different environmental characteristics. Sahin and Aksakal [8,9] investigated the wind energy potential for the north eastern and eastern region of Saudi Arabia based on a complete year data at coastal locations. Suitable Weibull distributions were generated and comparisons were made with the Rayleigh distributions of wind power densities. They considered two horizontal-axis type of conversion system operating at fixed rpm in order to determine the extractable wind power. Furthermore, they concluded that small-scale wind energy systems were suitable in the eastern part of Saudi Arabia for power generation and irrigation purposes.
3. Wind station sites and hardware Details of the location information of the five sites selected for the subject of this paper are shown in Table 1. A wind station generally comprises a tower, sensors and a data acquisition system. The tower is a steel tube having a length of 40 m. Wind speed sensors are installed at heights 40, 30 and 20 m. Each height has two sensors. In the case of one sensor failing, the other still operates, thus, ensuring continuous data collection. Wind direction sensors are also installed at two heights, 30 and 40 m. Two sensors are installed for the abovementioned reason. Other meteorological sensors measuring global solar
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Table 1 Wind stations location information Site
Latitude (deg N)
Longitude (deg E)
Elevation (m)
Data collection period
Arar Dhahran Dhulum Gassim Yanbu
30.8 26.1 22.74 26.3 23.9
41.3 50.1 42.18 43.97 38.3
550 3 1117 648 11
Jun 6, 1995–Dec 31,1998 Oct 4, 1995–Nov 30,2000 Nov 1, 1998–Oct 12,2002 Dec 5, 1995–Oct 24, 1998 Sep 17,1996–Oct 21,1999
radiation, ambient temperature, relative humidity and barometric pressure are also configured to the wind station [1]. The data acquisition system is a mini computer which can be programmed to have data averaging interval of a minimum of 1 min to a maximum of 1 h. The averaged data were stored in a data card and retrieved from the site periodically. The data acquisition system is powered by a two 6 V, 3.8 Ah battery charged by a 10 W amorphous silicon photovoltaic panel. For safety the tower is equipped with an obstruction light installed on top of it and powered by the utility grid or from a photovoltaic power system depending on the remoteness of the site [1].
4. Results and discussion The data acquisition systems in all stations were programmed to store data (averaging interval) every 30 min. This averaging interval was chosen to maximize data collection and minimize site visits; one site visit every 3 months for data retrieval and station hardware maintenance. To asses the effect of averaging interval on the energy production of a wind conversion system, 10-min and 30-min averages were used in Yanbu station for 1 year during the data collection period, i.e. July 1998–June 1999. The annual energy production calculated based on the two averaging intervals was compared. For the other analysis presented in the paper the 10-min data were reduced to 30-min averaging. 4.1. Overall monthly variation of wind speed and wind power density The overall monthly variation of mean wind speed and wind power density provides information on the availability of wind during different months of the year. The overall monthly maximum and mean values of half-hourly wind speed at 40 m height during the collection periods are summarized in Table 2. The table also shows the corresponding mean values of wind power densities. The table shows that Dhulum has the highest annual mean wind speed of 5.7 m/s followed by Arar with a value of 5.4 m/s. These two sites are quite remote and have isolated, scattered and low population areas which increase the economical feasibility of utilizing wind energy at these locations. Furthermore, the monthly means wind speed for Dhulum were 5.7 m/s or more for 10 months of the year reaching above 6.5 m/s for few months of the year. For Arar the monthly means were 5.4 m/s or more for 5 months and more than 5 m/s for 10 months of the year. At the two
Table 2 Overall monthly half-hourly wind speeds (m/s) and power density for the five stations during the collection periods at 40 m above the ground Dhulum
Arar
Wind speed (m/s)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
Max
Mean
17.4 22.7 23.9 19.6 20 15.1 23.7 17.2 16.6 16.5 16.4 17.3 23.7
6.1 6.6 6.7 5.9 5.7 5.8 6.5 5.8 5 5 5.7 5.8 5.7
Power density (W/m2) 197 249 278 197 176 165 226 166 114 109 175 178 186
Yanbu
Wind speed (m/s) Max
Mean
16.4 15.2 19.2 18.6 20.7 14.6 15 12.5 18.2 16.5 16.2 20.1 20.7
5.2 5.1 6.1 5.7 5.4 5.8 6.3 5.3 5 5.1 4.5 4.9 5.4
Power density (W/m2) 142 159 241 200 182 181 211 148 129 143 107 125 164
Gassim
Wind speed (m/s) Max
Mean
14.4 15.4 15.2 15.1 14.2 14.7 14.4 15.1 14.4 12.8 17.2 14.3 17.2
4.7 4.9 5.3 5.1 4.9 4.7 4.7 4.9 4.8 4.6 4.3 4 4.7
Power density (W/m2) 122 149 184 178 142 137 142 152 130 96 95 76 134
Dhahran
Wind speed (m/s) Max
Mean
12.9 13.5 15.3 17.5 22.7 11.5 12.3 11.1 10.9 11.4 11.5 12.3 22.7
4.3 4.8 4.9 4.9 4.3 4.3 4.3 4 3.9 4.1 3.9 4.1 4.3
Power density (W/m2) 78 104 125 125 91 72 73 57 55 66 63 68 81
Wind speed (m/s) Max
Mean
15.8 15.8 16.2 19.2 19.3 16.1 18.5 15 16.5 13.1 16.2 13.2 19.3
5.2 5.7 5.8 5.9 5.2 5.7 5.7 5.1 4.8 4.7 5 4.9 5.3
Power density (W/m2) 145 179 197 207 151 200 188 137 114 95 123 112 154
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sites the wind speed is higher during the summer months when electrical load is high at such hot arid climates. Wind speeds at Yanbu and Gassim sites behaved in lower figures with annual mean wind speeds of 4.7 and 4.3 m/s, respectively. While at the other site, i.e. Dhahran behaved in between of annual wind speed of 5.3 m/s. The annual mean wind power density are 186, 164, 134, 81, 154 w/m2 for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. 4.2. Diurnal variation of wind speed The overall diurnal variation of wind speed with time is important when assessing confidence about availability of wind during different hours of the day. The diurnal halfhourly mean values of wind speed are calculated using the entire data set for the five stations and results are summarized in Fig. 1. The five sites experienced different diurnal wind speed behavior that can be characterized in three behaviors. The costal sites, i.e. Yanbu and Dhahran experienced similar characteristic where wind speed peaks during the hour’s 13:00–18:00 h. That makes wind energy a potential tool for electrical peak shaving during the hours of air conditioning demand load. In Yanbu the wind speed stayed above 7 m/s for 4 h (17%) of the day, above 6 m/s for 6 h of the day (25%) and above 5 m/s for 9 h of the day (38%). In Dhahran wind speed stayed above 6 m/s for 5 h (21%) and above 5 m/s for 10 h (42%) during the day. Fig. 1 shows similar profiles for Gassim and Dhulum. These sites are located in the mid and mid-south of the country. At these sites the wind speed peaks twice, the highest peak occurs around midnight and the second occurs during late morning hours (8:00– 12:00). The data show that Dhulum has good wind energy potential as the wind speed stayed above 5 m/s almost during the entire day and above 6 m/s for nearly 6 h, i.e. 25% of the day.
Fig. 1. Diurnal profiles for the five sites at 40 m above the ground.
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Wind speed profile of the other site, i.e. Arar, showed peculiar behavior compared to the others. The wind speed peaks during night hours with values above 6 m/s. Even though, the lowest speed occurs at mid day, it stays above 5 m/s for nearly the entire day. 4.3. Wind speed frequency distribution and wind rose In order to obtain information about the number of hours during which the wind remained in a certain wind speed bin, the frequency distribution analysis was carried out for the half-hourly recorded data at 40 m above the ground for the five sites. The wind rose provides information about the occurrence of number of hours during which wind remained in a certain wind speed bin in a particular wind direction. In other words, a wind rose provides information on the relative wind speeds in different wind directions. The wind roses were constructed using the measurements of wind speeds and corresponding wind directions. Like wind speed, wind roses also vary from one location to the other and are known as a form of meteorological fingerprint. Hence, a close look at the wind rose and understanding its message correctly is extremely important for siting wind machines. So, if a large share of wind comes from a particular direction then the wind machines should be put against this direction. In order to construct wind roses and analyze the frequency distribution, all half hourly averaged values of wind speed and wind direction were used. Fig. 2 and Table 3 show the wind rose chart and percentage of time the wind speed stayed at the different speed pins for the five sites. All the half-hourly data recorded at height 40 m above ground was used for the generating of Fig. 2 and Table 3. Fig. 2 depicts that the wind blows predominately from southeast, northwest, north, north to northeast and north to northwest at Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. Table 3 shows that Dhulum site has the highest wind energy potential and wind blows at speed higher than 5 m/s for 60% and higher than 8 m/s for 21% of the time. At the sites of Arar, Dhahran and Yanbu, the wind speed blows higher than 5 m/s for 47, 42 and 40% of the time, respectively. The table shows that Gassim has the lowest wind energy potential among the other site with wind blowing at speed higher than 5 m/s for only 34% of the time. 4.4. Wind energy calculations The annual energy that can be generated at the five sites by a Nordex N43/600 wind machine was obtained using wind power curve of the machine [10] and 1 year wind duration data recorded at the sites. The technical data of the wind machine used is summarized in Table 4. Since the hub heights of the wind machine is 50 m, the half-hourly mean wind speed values were calculated at that height using 1/7th power law. Fig. 3 shows a comparison of the annual energy that can be generated using the Nordex N43. It shows that at Dhulum site, the calculated annual energy is about 1080 and 990 MWh at Arar. For Dhahran and Yanbu the annual energy are 833, 730 MWh, respectively, while at Gassim site the Nordex N43 will only produce about 454 MWh.
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Fig. 2. Wind rose charts for the five sites at 40 m above the ground.
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Table 3 Wind speed percent distribution at different speed pins at 40 m above the ground for the five sites Site Dhulum Arar Yanbu Gassim Dhahran
Wind speed pins O0–2.9
O2.9–4
O4–5
O5–6
O6–7
O7–8
O8.1
14 30 32 27 32
12 11 15 21 13
14 11 13 18 14
14 12 11 14 13
13 12 9 9 11
11 10 7 5 7
21 14 12 5 11
4.5. Wind energy comparison for 10-min and half-hourly average data As mentioned earlier, 1 year 10 min averaged data recorded at Yanbu site was used to estimate the percentage variation in the annual energy output of the wind energy machine for the 10-min and half-hourly average (of 10-min) data. The analysis showed that using 10-min data resulted in 2.5% more energy compared to the energy calculated from the half-hourly averaged data. Therefore, it can be stated that an increased output of wind energy can be expected from wind machines while in operation compared to the energy calculated using half-hourly or hourly data. Table 4 Technical data of wind machines from Nordex N43/600 Cut-in speed (m/s) Cut-out speed (m/s) Rated speed (m/s) Survival speed (m/s) Rated output (kW) Hub height (m) Rotor diameter (m)
3 25 13.5 70 600 50 43
Fig. 3. The annual wind energy produced by the Nordex N43 at the sites.
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5. Concluding remarks The paper discussed the analysis of wind energy potential at five sites in the Kingdom of Saudi Arabia. The data used in the calculation are published for the first time and collected for the purpose of studying the wind energy potential in these sites. The site of Dhulum has the highest wind energy potential compared to the other sites with annual wind speed average of 5.7 m/s and with wind speed higher than 5.0 m/s for about 60% of the time. The site of Arar is the second in wind energy potential with annual average wind speed of 5.4 m/s and with wind speed higher than 5.0 m/s for about 47% of the time. The two sites have isolated, scattered and low population areas that increase the economical feasibility of utilizing wind energy at these locations for remote area applications. The estimated energy that can be produced from a Nordex N43 is 1080 and 990 MWh at Dhulum and Arar, respectively. At the costal sites namely, Yanbu and Dhahran, the wind blows at speed higher that 5 m/s during afternoon hours peaking to 8 and 7 m/s at Yanbu and Dhahran, respectively. Hence, grid connected wind energy systems will be candidate tools for electrical load peak shaving at the two sites. Although, Gassim site has the lowest annual average wind speed but wind blows higher than 3 m/s for 73% of the time. Therefore, barely adequate potential for the use of wind machine with low rated wind speed is available at this site. The output of wind energy machine is expected to be higher while in operation compared to the energy calculated using half-hourly or hourly data.
Acknowledgements The author acknowledges the Energy Research Institute of the king Abdulaziz city for Science and Technology for the financial support of the wind energy resource assessment project.
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