# Introduction ind is the flow of gases on a large scale. On the surface of the Earth, wind consists of the bulk movement of air. In outer space, solar wind is the movement of gases or charged particles from the sun through space, while planetary wind is the outgassing of light chemical elements from a planet's atmosphere into space. There are different places of Bangladesh where there are strong wind is available. But we select only one site for this work. # II. Site Selection Sitakunda is one of most important the places of Bangladesh where there is a possibility of production of wind energy. The geographical position of sitakunda is 22°35.68' North Latitude 91°42.52'East Longitude. [1] Twenty years monthly wind speed of sitakunda is given below. Author ? ? ?: Department of Electrical and Electronic engineering, Pabna University of Science and Technology, Pabna, Bangladesh. e-mails: ahsan.pstu@gmail.com, mijansinha51@gmail.com, motahertex@yahoo.com # III. Weibull Distribution Weibull distribution function which has recently been proposed by some researchers. This is due to its greater flexibility and simplicity, as well as good agreement with experimental data. In other words, this analytical distribution for fitting wind speed data is generally accepted for energy assessment analyses and wind load studies. [2] Weibull distribution function is written for wind speed [3][4] ?? (??) = ? ?? ?? ? ? ?? ?? ? ???1 ?????? ?? ? ?? ?? ? ?? ? (1) Where Q(v) is the probability of observing wind speed v, k the dimensionless Weibull shape parameter (or factor), and c reference value in the units of wind speed (so-called: Weibull scale parameter). The k values range from 1.55 to 3.10 for most wind conditions. The generalized cumulative distribution function is [4] ?? ?? =cÎ?"(1 + 1 ?? ) Where gamma function is Î?"( ) Weibull distribution is a good statistical tool for analyzing wind speed. It shows the power probability and weibull distribution of a site. Two important parameters Weibull's shape factor k and Weibull's scale factor c have been obtained from the data. The power probability, weibull distribution, shape factor and scale factor helps to determine the characterristics of wind wave and potential of wind power. We know, the cumulative distribution function is given as Q(v) = 1 ? exp [? ? v c ? k ] Rearranging and taking ln two times we gets We get the value of scale factor c=3.97 and the value of shape factor k=1.86 which is the appropriate value for most wind conditions. Now, we draw a curve of probability and weibull distribution versus wind speed. The curve is shown below. Histogram represents 20 years of monthly mean wind data at sitakunda plotted together with the weibull probability distribution. This figure illustrates that the weibull distribution is a good representation of the wind resources of a site. The imperfectness of the weibull distribution compared with the histogram may be a significant source of error. IV. # Power Calculation Here, we calculate theoretically available power for twenty years from 1988 to 2007 for yearly speed. The SI unit for magnetic field strength H is A/m. However, if you wish to use units of T, either refer to magnetic flux density B or magnetic field strength symbolized as µ0H. Use the center dot to separate compound units, e.g., "A . m 2 Table shows the power which is produced over twenty years at sitakunda. Wind speed varies from 3 m/s to 7 m/s and power varies 16 kw to 457 kw. This power is obtained from one turbine. So if we place a few numbers of wind or make a wind farm we get certain MW power from them. This power is supplied to the remote areas. This helps the people of the remote areas is on the under of electricity. If we want to cover a larger area which is greater than the area covered by the wind farm, we need more power .So for this reason, we here design a new combined power system. This power system consists of wind, hydrogen and solar. The combination of this will produce large power. The combination is make in such a way that if one parts of this system is falls there is a continuity of supply. Global Journal of Researches in Engineering ( ) V. # Proposed System The combined power system shown in below: When wind blows, turbine rotates and power is generated. This power is supplied to electric load. But when speed of wind is high, more power is generated. If this power is larger than the load which is connected, excess power is goes to eletrolyzer. An electrolyzer is an electrochemical apparatus which is used to perform electrolysis. Here, electrolyzer is used to splitting water into hydrogen and oxygen. The hydrogen is stored in hydrogen storage tank. The battery is used to smooth the turbulent wind power to protect the electrolyzer from wear due to rapid and large wind power variations. This hydrogen then passed to fuel cell where it used as fuel. Now, we get dc power from fuel cell which is converted to ac. This ac power is supplied to the electric load. A solar panel is connected whose electricity is goes to electrolyzer or to the point where fuel cell out is obtained. The hydrogen which is obtained from electrolyzer is also used for mobile applications when more power is not needed i.e from fuel cell. # VI. Conclusion In future, wind energy will be the most cost effective source of electrical power. Most probably it reached this state. The major technology developments enabling wind power commercialization have already been made. This paper analyze the characteristics of wind and power probability of wind at sitakunda. This site is able to produce huge power. This papers also introduce a new power production model. If it is possible to implement with proper knowledge, equipment and sincere to proper maintenance of the ground equipments (especially from flood water), it takes a great role to improve power crisis of Bangladesh. There is huge power crisis in Bangladesh. Only 50% people get electricity. So there many remote areas in Bangladesh specially hilly area where this power production system is very suitable. Here, we proposed this system theoretically. There are many equipments associated this model such as electrolyzer, battery, hydrogen storage tank, controlling device and fuel cell. The final power output depend on the performance of all this device. So sizing of fuel cell, battery and electrolyzer is very important. In future we size all of this equipment so that optimum output is obtained. 5![??(??) = 1 ? exp ?? of the parameters of the Weibull distribution requires a good fit of Equation (2) to the recorded discrete cumulative frequency distribution. Taking the natural logarithm of both Sides of Equation (2) twice, gives ln{? ln[1 ? ??(??)]} = ??????(??) ? ??????(??) So, a plot of ln {? ln[1 ? ??(??)]} versus lnv presents a straight line. The k is the gradient of the line and the intercept with the y-axis is -k lnc.The relation between k and c for wind speed ?? ?? is[2] ](image-2.png "[ 5 ]") 1![Figure 7.1 : Curve of ln {? ln[1 ? ??(??)]} versus lnv](image-3.png "ln{? ln[ 1 ?") 72![Figure 7.2 : Histogram for monthly mean speed with probability and weibull distribution of wind speed](image-4.png "Figure 7 . 2 :") 131![For 1988, speed, v=7.12, Cp=.410 Pavail = × 1.23 × 5026 × .410 × 7.12 3 = 457.426 Kw](image-5.png "1 2 ?A Cp v 3 = 1 2") 73![Figure 7.3 : Power for corresponding wind speed that obtained in sitakunda](image-6.png "Figure 7 . 3 :") 74![Figure 7.4 : Proposed power system consisting of wind, hydrogen and solar](image-7.png "Figure 7 . 4 :") 71W( ) F Volume XIV Issue IV Version IEAR 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999JAN 5.88 5.46 5.04 5.32 6.16 5.74 4.62 3.08 3.36 4.62 3.08 3.22FEB 6.58 7.43 3.64 7.15 7.29 8.13 4.48 4.06 3.78 5.6 4.2 2.94MAR 6.16 8.27 6.3 6.73 7.43 5.6 5.74 4.62 5.6 7.01 5.46 6.73APR 8.13 8.41 7.57 6.44 8.27 5.32 4.62 5.04 6.16 5.88 5.46 6.02MAY 10.65 6.44 6.44 9.39 5.88 6.44 4.34 6.44 7.85 7.29 6.44 5.6JUN 7.29 5.6 7.43 6.87 4.62 6.02 5.46 4.34 4.76 7.15 5.04 6.73JUL 7.99 4.34 7.29 6.58 5.6 5.32 4.06 3.92 5.04 4.76 4.76 5.18AUG 6.87 4.48 6.16 5.46 3.78 4.62 4.62 3.92 3.5 5.32 4.48 4.62SEP 6.02 3.92 5.32 5.04 4.9 3.92 4.2 4.62 3.22 4.2 4.06 4.62OCT 9.11 3.78 9.11 5.18 4.76 3.22 3.22 3.08 9.81 2.8 4.2 3.64NOV 5.18 2.94 8.69 3.22 3.36 3.08 2.94 4.06 2.8 2.8 2.24 2.8DEC 5.6 2.8 3.78 3.5 3.78 4.2 2.8 2.24 3.92 3.5 2.66 3.64Global Journal of Researches in Engineering20003.643.646.025.65.324.486.164.484.063.642.522.9420012.663.082.385.883.925.744.065.745.183.361.962.5220022.83.363.785.045.743.924.064.343.223.57.432.2420032.943.362.84.94.765.046.444.062.82.661.541.8220041.823.086.167.854.485.746.448.557.158.422.663.08 © 2014 Global Journals Inc. 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