%0 Journal Article
%T Evaluation of the feasibility of wind energy utilization in Sistan and Baluchestan Province
%J Physical Geography Research
%I University of Tehran
%Z 2008-630X
%A Kahkha Moghaddam, Parisa
%A Delbari, Masoomeh
%D 2017
%\ 09/23/2017
%V 49
%N 3
%P 441-455
%! Evaluation of the feasibility of wind energy utilization in Sistan and Baluchestan Province
%K Trend Analysis
%K Weibull distribution
%K wind energy potential
%K wind power density
%R 10.22059/jphgr.2017.218706.1006952
%X 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.
%U https://jphgr.ut.ac.ir/article_65428_dfc75a9cb8c5c3cf5fd9dff7643b1574.pdf