Bioenergy
M. Nowroozipour; R. Tabatabaei koloor; A. Motevali
Abstract
IntroductionThe world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly ...
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IntroductionThe world’s growing population has led to an inevitable increase in energy demand, and this, in addition to the depletion of non-renewable energy sources, can lead to several environmental issues. Wind power has proven to be a reliable and sustainable source of electricity, particularly in light of the pressing need to mitigate environmental impact and promote the use of renewable energy. The purpose of this research is to investigate and compare the environmental effects of electricity production from two wind power plants, Aqkand and Kahak, using wind turbines with a capacity of 2.5 megawatts for a period of three different lifetimes (20, 25, and 30 years).Materials and MethodsThe present study investigates the environmental effects of electricity generation during the life cycle of wind farms (Kahak and Aqkand) during the construction and operation of these power plants and the cumulative exergy demand index. The specifications of the wind turbines used in the current research are: turbine capacity of 2.5 MW, rotor diameter of 103 meters, rotor weight of 56 tonnes, three blades, each blade is 50.3 meters long and weighs 34.8 tonnes. The turbines are manufactured by Mapna and used in dry conditions. A functional unit of one kilowatt of electricity was selected and the data were analyzed in SIMAPRO software using IMPACT2002+ method with 15 midpoint indicators and four final indicators.Results and DiscussionThe results showed that the stage of raw materials and production has the highest impact on the creation of midpoint indicators, which is due to extraction, manufacturing, and production of parts such as steel casting using non-renewable energy and activities such as high-temperature welding. The total environmental index of Aqkand and Kahak wind power plants for 1 kWh of generated electricity was 5.84 and 4.45 μPt respectively, more than half of which belongs to the damage to human health category. The investigation of the ionizing radiation index showed that the use of diesel fuel in the installation phase resulted in the highest amount of emissions in both of the power plants, so the share of pollutant emissions in the raw materials and production phase is more than 40%, and in the installation phase due to diesel fuel consumption was more than 48%. The investigation of the eutrophication index showed that the raw materials and production stage accounted for more than 95% of the damage to the ecosystem quality category, and in the meantime, copper and electrical components had the highest amount of contribution to the raw materials and production stage. Additionally, diesel fuel accounted for the largest part of the result in the installation stage, and the transportation and maintenance stage included less than 1% of this result. The investigation of the renewable energy consumption index showed that the stage of raw materials and turbine production in the Aqkand power plant with a share of 68% and the Kahak power plant with a share of 70% had the greatest effect on the category of resource damage. Also, the installation and commissioning phase was the second most effective factor in the category of resource damage due to the use of diesel fuel. The study of the cumulative exergy demand index showed that non-renewable-fossil resources had the largest share in exergy demand (0.15 MJ) to produce one kilowatt of electricity generated from power plants.ConclusionIn this study, the results showed that in both plants, about 70% of various respiratory effects, 60% of human health issues, and 25% of acidification and global warming are caused in the raw materials and manufacturing phase. Furthermore, the installation phase is responsible for 17% and 16% of climate change in the Aqkand and Kahak power plants respectively, and between 14% and 26% of other environmental factors.
A. Omidi; R. Alimardani; M. Khanali
Abstract
Introduction Geographical location and climatic conditions are the important factors affecting the wind energy potential of each region. Iran is a vast country with different climates and the exploitation of its wind energy needs to study and research on the meteorological data. In the study area during ...
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Introduction Geographical location and climatic conditions are the important factors affecting the wind energy potential of each region. Iran is a vast country with different climates and the exploitation of its wind energy needs to study and research on the meteorological data. In the study area during the warm season and the hottest hours of the day, coinciding with peak electricity consumption in the region and the country, wind blowing continuously carried out. The surpassed consumption over production of electricity in summer and vice versa in winter is considered as one of the country's problems. The aim of this study was to investigate the parameters of the wind energy and the feasibility of wind potential (in study area) in the warm season in particular and other seasons to supply the needed electrical power of area, avoid of unwanted blackouts, development of wind energy as an important renewable energy, attraction of investors, and policymakers to build wind farms in the study area. Materials and Methods This study was conducted in the Dehloran city, located in the southern part of Ilam province. The region has a temperate winter and very hot and dry summer. The important criteria for construction of wind power plants and using of its energy are wind power density and the annual wind speed average. For this reason and analysis, and statistical analyzes, wind data includes three-hour direction and speed were obtained from the meteorological organization and during 2004 to 2013. The average of annual, monthly and daily wind speed and their standard deviation were calculated. Based on the commercial turbines in the country, and the rotor blades are at altitudes up to about 80 meters, the wind speed at altitudes of 40, 60 and 80 meters was calculated. To evaluate the potential of wind speed the Rayleigh and Weibull distribution functions were used and their parameters were calculated. The wind energy potential using the available data and the Weibull and Rayleigh functions were calculated. Results and Discussion Based on the results of the ten-year data, average of wind speed had relatively slight variation, with the highest and the lowest value of 3.6 and 3.25 m s-1 in 2007 and 2010, respectively. The annual average was about 6 m s-1 in height of 50 meters that seems appropriate. The highest and the lowest monthly average values were 4.62 m s-1 and 2.24 m s-1 in June 2005 and November 2006, respectively. Generally, the warm months had significantly higher wind speed than that of cold months. The Weibull distribution function parameters, k and c were calculated. Minimum and maximum amount of k were 1 and 1.828, in December 2006 and May 2011, respectively. The minimum and maximum amount of c was 2.37 and 5.69 in November 2004 and June 2013, respectively. The highest value of wind power density was 312 w m-2 in June. The lowest power density was observed in November. Therefore, we can say that the wind energy potential of the region has coincident with peak electricity consumption in the warm months. The most frequent and the least frequent wind direction were the southeast and northeast, respectively. Conclusion Daily evaluation of wind speed during different months, seasons and years showed a significant change during the day that represented the high value of the wind speed in noon and afternoon. The highest value of monthly wind energy density was for the warm season. The lowest and highest power density was in November and June, respectively. Therefore, we can say that the peak of wind energy potential of the region has a coincident with the country's peak power consumption in warm months. With considering that the study area has a warm climate and high consumption of energy in the hot days of a year and the probability of unwanted blackout of electricity in warm months, and the long hours of the wind blowing in the mentioned times, construction of wind farm in these areas can be reasonable.
F. Keyhani Nasab; T. Mesri Gundoshmian; Sh. Zargar Ershadi
Abstract
Introduction Considering the low cost of the wind power production and its relatively good compatibility with the environment, wind farms have shown extensive growth in the past few years. Considering the importance of using the wind power and its advantages, the careful planning is needed to identify ...
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Introduction Considering the low cost of the wind power production and its relatively good compatibility with the environment, wind farms have shown extensive growth in the past few years. Considering the importance of using the wind power and its advantages, the careful planning is needed to identify the available generation potentials in a region or a country to facilitate its increased use. By the end of 2009, the capacity of wind turbines installed in the wind farms of Iran was 92 MW, which demonstrates the significant potential for additional wind farms in the country and suggests investments in the wind power industry are likely cost effective. The main purpose of this research is to assess the potential of wind power for the city of Pars Abad in northwestern Iran. Materials and Methods In order to measure wind power density and wind energy potential, wind speed data collected every 3 hours at a height of 30 m above the ground for 11 consecutive years are analyzed; the data are provided by the Iranian Meteorological Organization and are used in the assessment of electricity production potential in the area chosen for the wind turbines installation. To determine the wind energy potential at a site and estimate the energy output from this site, statistical functions like probability functions are used. There are many probability functions but the Weibull distribution function is usually considered the most useful function for wind speed data analysis due to its simplicity and good accuracy. The Weibull probability density function is defined with two parameters of k and c as follows: (1) f (v) = k/(c ) 〖( v/c )〗^(k-1) exp (- 〖( v/c )〗^k ) After calculating the Weibull function parameters, status of a location for wind energy potential can be assessed. A good way to assess the available wind resources is by calculation of the wind power density. This parameter indicates how much energy can be converted to electricity at a site and can be calculated as follows: (2) P/A=1/2 ρc^3 Г ( (k+3)/k) Wind energy density expresses the wind power density for a given time period T.The wind energy density for a definite site and in a given time period (one month or one year) (T) can be calculated as: (3) E/A=1/2 ρc^3 Г ((k+3)/k) T Results and Discussion In this study, wind speed data collected in Parsabad, Iran, over a ten-year period (2005-2015) are analyzed, and the Weibull distribution parameters c and k, average wind speed, and average wind power and wind energy densities are determined. According to Table 1, the minimum and maximum standard deviations of the average monthly indicators during 11 years in November and July are 0.63 and 2.51, respectively, and the minimum and maximum wind speeds of the average monthly indicators during 11 years in November and June are 2.09 ms-1 and 4.87 ms-1, respectively. The average annual Weibull scale parameter (c) is 3.84 while the average annual Weibull shape parameter (k) is 2.61. The average annual wind power density (P/A) during 11 years is 45 Wm-2, while the average annual wind energy density (E/A) during 11 years is 389 kWhm-2/year. Pars Abad in terms of generation potential of wind energy and based on quantitative classification for wind resource is located in weak to average region. Conclusion Pars Abad with an average wind power density of 45 Wm-2 and average wind speed of 3.41 ms-1 is not a good candidate for wind power plants and it is just suitable for off-grid electrical and mechanical applications such as charging batteries and pumping water for agricultural and livestock uses.
M. Jalalvand; H. Bakhoda; M. Almassi
Abstract
In order to restrain the potential of wind energy, the first step is to determine the wind energy potential. In this study the wind data was used from the three-hour frequency recording of 10-year period (2002-2011). To predict the occurrence probability of each wind speed, the two-parameter Weibull ...
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In order to restrain the potential of wind energy, the first step is to determine the wind energy potential. In this study the wind data was used from the three-hour frequency recording of 10-year period (2002-2011). To predict the occurrence probability of each wind speed, the two-parameter Weibull function was used. The goodness of fit test by Chi-Square test showed that the wind speed distribution is not represented by the typical two- parameter Weibull function for all the months. Weibull probability density function has a good fit for eleven months, but for the 9th month of the year (September), it is not fitted. Thus, four-parameter Weibull probability function has been developed to analyze the wind speed frequency distribution in that region for the mentioned months. The electrical energy consumption of agricultural water wells in the region was also calculated for the desired periods of the year. Energy demand and energy supply were matched. Data analysis was performed using SPSS 18.0.0, MATLAB 7.13.0.564 and WIDOGRAPHER 3.0.2. The results show that in Broujerd, to exploit the wind energy at all times of the year, it is necessary to have at least 39 turbines of 2300 kW with 99 meters tower. If the desired turbines are used, there will be extra energy and also, agriculture will be continued towards sustainable development.
