Evaluation of the feasibility of wind energy utilization in Sistan and Baluchestan Province

Document Type : Full length article

Authors

1 Assistant professor of water engineering, Faculty of Water and Soil, University of Zabol, Iran

2 Associate professor of Water engineering, Faculty of Water and Soil, University of Zabol, Iran

Abstract

Introduction
Energy is one of the most important demands in development of human societies. As world population continues to grow and the limited and non-renewable resources of fossil fuels begin to diminish, countries must take action to facilitate a greater use of renewable energy resources such as geothermal and wind energies. Iran has a high wind energy potential, but except in a few specific regions such as Binalud and Manjil, the use and exploitation of such clean renewable source is still not addressed enough. Wind speed in Sistan and Baluchistan province especially in the cities like Zabol is very high and sometimes it goes near 120 km/h. Thus, the purpose of this study is to investigate the feasibility of wind harvesting in synoptic stations of Sistan and Baluchestan province. Moreover, the trend analysis of wind data is to be investigated in this paper.
Materials and methods
This study is based on wind data in 8 synoptic stations, for a period of 10 years (2005-2014). The analysis is based on 3 hours interval wind speed data measured in 10 m height above ground surface.
The most widely used model to describe the wind speed distribution is the Weibull two- parameter. These two parameters include k and c: the first is the shape parameter and the second is the scale parameter. There are several methods to calculate these parameters. In this paper, these two parameters have been determined through the Maximum Likelihood (ML) technique. The Weibull distribution function is expressed mathematically as:




 

(1)





Where f (v) is the probability density function, k is the shape parameter, c is the scale parameter (m/s), and v is the wind speed (m/s). The probability of having a wind speed between two values of interest V1 and V2 is given by the equation




 

 
(2)





The maximum likelihood method estimates the parameter k by solving the following equation iteratively:




 

(3)





Where n is the number of wind observations and Vi is the observed wind speed value for the i observation. Parameter c can be expressed using the values of shape parameter (k) as follows:




 

(4)





Given k and c, the most probable wind speed (Vmp) and optimal wind speed (Vop) are calculated for every synoptic station. Wind energy density and wind power density are also calculated for the selected stations.
Moreover, the trend analysis are performed for monthly and annual wind speed data for a period of about 25-40 years up to 2014 using Mann Kendal test and Thiel Sen's estimator.  
Results and discussion
Monthly mean and standard deviation of wind speed data have been calculated for the selected stations during 2005-2014. The results have indicated that the monthly variation (2 to 5 m/s) of mean wind speed for all the years is similar as the highest and lowest mean wind speed was happened in winter and autumn, respectively.
The wind speed characteristics required to evaluate the feasibility of wind energy utilization have been calculated for the selected stations. The results have also represented that the maximum wind power density has been observed for Zabol with the values of 257.227 W/m2 and 512.713 W/m2 in 10 m and 50 m high, respectively. The lowest wind power density has been observed in Iranshahr with the values of 40.196 W/m2 and 80.12 W/m2 in 10 m and 50 m high, respectively. Comparing these data and the data calculated for other stations with the standard classification criteria indicated that Zabol, Zahak and Konarak are the most suitable sites for wind turbines installation. Moreover, Zabol has the maximum probability of having the wind speed of 3 to 25 m/s, i.e. 0.71 and 0.82 for 10 m and 50 m high, respectively. Therefore, given a wind turbine installed in 50 m high, the probability of blowing wind with the speed of 3 to 25 m/s, is about 0.82 multiply by total hours of wind existence during a year (82*7566 hrs/year), i.e. 5822 hrs/year.
The results of the trend analysis by Mann-Kandal test have also revealed that there is either an increasing trend or decreasing trend in the selected stations; however, increasing trends (e.g. Zabol, Iranshahr, Zahedan and Konarak) were more often. Wind speed in Zabol has shown a positive trend for all months (except September). However, the trend was significant in 41.6 percent of times. In annual basis, wind speed in Zabol has positively increased at a significance level of 5%. Wind speed in Iranshahr has shown a significant positive trend in both monthly (except April) and annual scale. Overall, annual wind speed has a positive trend in half the stations considered and a negative trend in others.
Conclusion
According to the findings achieved in this study, wind speed is lower in the last months of the year for all stations in Sistan and Baluchistan province. The highest variation of wind speed has been observed for Zabol. Based on trend analysis, some significant positive trends of annual and monthly wind speed has been observed in Iranshahr, Zabol, Zahedan, and Konarak in descending order. According to the results, the highest wind power density in the height of 50 m has been seen for Zabol (513 W/m2) and Zahak (434 W/m2) and the lowest for Iranshahr (80 W/m2). Overall, based on wind speed existence and its annual continuity, three stations of Zabol, Zahak and Konarak has been realized to be appropriate for installing wind turbines.

Keywords

Main Subjects


انتظاری، ع. و اسدی، م. (1394). توان‏سنجی نیروگاه‏های بادی در استان سیستان و بلوچستان با روش فازی- ای. اچ. پی.، فصل‏نامة تحقیقات جغرافیایی، 30(30): 67ـ84.
امیدوار، ک. و دهقان طزرجانی، م. (1391). پتانسیل‏سنجی و برآورد مشخصه‏های نیروی باد برای تولید انرژی در ایستگاه‏های همدیدی استان یزد، فصل‏نامة تحقیقات جغرافیایی، 27(2): 149ـ168.
دلبری، م.؛ کهخامقدم، پ.؛ محمدی، ا. و احمدی، ت. (1395). برآورد الگوی پراکنش مکانی سرعت باد برای پتانسیل‏یابی تولید انرژی بادی در ایران، پژوهش‏های جغرافیای طبیعی، 48(2): 265ـ285.
رفاهی، ح. (1385). فرسایش بادی و کنترل آن، تهران: انتشارات دانشگاه تهران.
قهرمان، ن. و قره‏خانی، ا. (1389). بررسی روند تغییرات زمانی سرعت باد در گسترة اقلیمی ایران، مجلة آبیاری و زهکشی ایران، 4(1):31ـ43.
گندم‏کار، ا. (1388). ارزیابی انرژی پتانسیل باد در کشور ایران. مجلة جغرافیا و برنامه‏ریزی محیطی، 36(4):85ـ100.
محمدی، ح.؛ رستمی جلیلیان، ش،؛ تقوی، ف. و  شمسی‏پور، ع.ا. (1391). پتانسیل‏سنجی انرژی باد در استان کرمانشاه، پژوهش‏های جغرافیای طبیعی، 44(2): 19ـ32.
Adokoga, L.O. and Adewale, A.A. (1992). Wind energy potential of Nigeria, Renewable Energy, Vol. 2.
Alamdari, P.; Nematollahi, O. and Mirhosseini, M. (2012). Assessment of WindEnergy in Iran: A Review, Renewableand Sustainable Energy Reviews, 16(1): 836-860.
Al-Nassar, W. and et al. (2005). Potential wind power generation in the State of Kuwait, Renewable Energy, 30: 2149-2161.
Bagiorgas, H.S. and et al. (2007). Electricity generation using wind energy conversion systems in the area of Western Greece, Energy Conversion and Management, Vol. 48.
Celluraa, M.; Cirrincioneb, G.; Marvugliaa, A.; Miraouic, A. (2008). Wind speed spatial estimation for energy planning in Sicily: Introduction and statistical analysis, Renewable Energy, 33: 1237-1250.
Chang, T.J.; Wu, Y.T.; Hsu, H.Y.; Chu, C.R. and Liao, C.M. (2002). Assessment of wind characteristics and wind turbine characteristics in Taiwan, Renewable Energy, 28: 851-871.
Daniel, AR. and Chen, AA. (1991). Stochastic simulation and forecasting of hourly average wind speed sequences in Jamaica, Sol Energy, 46: 1-11.
Delbari, M.; Kahkhamoghadam, P.; Mohamadi, E. and Ahmadi, T. (2016). Estimating the spatial distribution pattern of wind speed for assessment of wind energy potential in Iran, Physical Geography research Quarterly, 48(2): 265-285. (In Persian)
Entezari, A. and Asadi, M. (2015). The feasibility of wind power plant in Sistan and Baluchistan province by fuzzy method, Geographical Research Quarterly, 30(30): 67-84. (In Persian)
Ernest, W. P. and Hennessey, J. P. J. (1978). On the use of power laws for estimates of wind power potential, J. Appl, Meteorology. Vol. 17.
Eskin, N.; Artar, H. and Tolun, S. (2008). Wind energy potential of Go¨ kc-eada Island in Turkey, Renewable and Sustainable Energy Reviews, 12: 839-851.
Gandomkar, A. (2008). Wind energy potential estimation in Iran, Geography and Environmental Planning, 36(4): 85-100. (In Persian)
Ghahreman, N. and Gharekhani, A. (2010). Trend analysis of mean wind speed in differentclimatic regions of Iran, Iranian Journal Irrigation and drainage, 4(1): 31-34. (In Persian)
Gilbert, R.O. (1987). Statistical methods for environmental pollution monitoring, John Wiley and Sons. New York.
Hollander, M.; Wolfe, D.A. and Chicken, E. (2013). Nonparametric statistical methods, Third Edition. John Wiley and Sons. New York.
Kendall, M.G. 1975. Rank Correlation Methods, 4th edition, Charles Griffin, London.
Keyhani, A.; Ghasemi-Varnamkhasti, M.; Khanali, M. and Abbaszadeh, R. (2010). Anassessment of wind energy potential as a power generation source in the capital of Iran, Tehran, J. Energy, 35: 188-201.
Manwell JF; McGowan JG and Rogers AL. (2002). Wind energy explained: theory, designand application, Amherst, USA: John Wiley & Sons, 689.
Mohammadi, H.; Rostami Jalilian, SH.; Taghavi, F. and Shamsipour, A.A. (2012). Evaluation of energy potential in Kermanshah province,Physical Geography research Quarterly, 80(2): 19-32.(In Persian).
Mostafaeipour, A.; Jadidi, M.; Mohamadi, K.  and Sedaghat, A. (2014). An analysis wind energy potential and economic evaluation in Zahedan, Iran, Renewable and Sustainable Energy Reviews, 30: 641-650.
Omidvar, K. and Dehghantarjani, M. (2012). Evaluation and estimating features of wind power for energy production synoptic stations in Yazd province, Geographical Research Quarterly, 27(2): 149-168. (In Persian)
Rahmani, K.; Kasaeian, A.; Fakoor, M.; Kosari, A. and Alavi, SB. (2014). Wind power assessment and site matching of wind turbines in Lootak of Zabol, International journal of renewable energy research, 4(4).
Refahi, H. (2006). Wind erosion and conservation, Tehran University Press, 320.(IN Persian).
Sen, P.K. (1968). On a class of aligned rank order tests in two-way layouts, The Annals of Mathematical Statistics, 1115-1124.
Saeidi, D.; Mirhosseini, M.; Sedaghat, A. and Mostafaeipour, A. (2011). Feasibility Study ofWind Energy Potential inTwo Provinces of Iran: North and South Khorasan, Renewable and Sustainable Energy Reviews, 15(8): 3558-3569.
Stevens, M.J.M, and Smulders P.T. (1979). The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes, Wind Eng, 3(2):132-145.
Tackle, ES. and Brown, JM. (1978). Note onthe use of Weibull statistics to characterize wind speed data, J. Appl Meteorol, 17: 556-559.
Weisser, D. (2003). A wind energy analysis of Granada: an estimation using the Weibull density, Renewable Energy, 28: 1803-1812.
Yue, S.; Pilon, P. and Cavadias, G. (2002). Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series, Journal of hydrology, 259(1): 254-271.