Optimization and Generation of Electrical Energy using Wind Flow in Rural Area of Bangladesh

Md. Sanwar Hossain, Bipul Kumar Raha, Dipankar Paul and Md. Ershadul Haque Department of EEE, Bangladesh University of Business and Technology, Dhaka, Bangladesh Operation and Maintenance, WÄRTSILÄ Bangladesh Limited, Bangladesh Operation and Maintenance, Huawei Technology Ltd., Bangladesh Department of Electrical, Electronics and System Engineering, Universiti Kebangsaan Malaysia (UKM), Selangor, 43600, Malaysia


INTRODUCTION
Airflows can be used to run wind turbines.Modern wind turbines range is from around 600 kW to 5 MW of rated power, although turbines with rated output of 1.5-3 MW have become the most common for commercial use; the power output of a turbine is a function of the cube of the wind speed, so as wind speed increases, power output increases dramatically (Muller et al., 2000).Areas where winds are stronger and more constant, such as offshore and high altitude sites are preferred locations for wind farms.Since wind speed is not constant, a wind farm's annual energy production is never as much as the sum of the generator nameplate ratings multiplied by the total hours in a year.The ratio of actual productivity in a year to this theoretical maximum is called the capacity factor.Typical capacity factors are 20-40%, with values at the upper end of the range in particularly favorable sites (Boccard, 2009).For example, a 1 megawatt turbine with a capacity factor of 35% not produce 8,760 MW-h in a year, but produce only 0.35×24×365 = 3,066 MWh, averaging to 0.35 MW.In the case of wind power intermittency is one of the frequently cited disadvantages, because the wind doesn't blow all the time.Wind projects can't produce a steady stream of energy for 24 h; hence they are regarded as "intermittent" power sources.Here the solution is the hybrid project.Hybrid power systems are combinations of two or more energy conversion devices (e.g., electricity generators or storage devices), or two or more fuels for the same device (Canales and Beluco, 2014).This integrated power systems overcome the limitations that may be inherent in either.Examples of hybrid power systems include: • Wind generation combined with diesel generation • Photovoltaic generation combined with battery storage or diesel generation • Fuel cell generation combined with micro-turbine generation The objective of these hybrid power systems is to generate and optimize electrical energy using wind flow in rural area of Bangladesh.

METHODOLOGY
The wind turbine shown in Fig. 1 captures the wind's kinetic energy in a rotor consisting of two or more blades mechanically coupled to an electrical generator.The turbine is mounted on a tall tower to enhance the energy capture.Numerous wind turbines are installed at one site to build a wind farm of the desired power production capacity.Obviously, sites with steady high wind produce more energy over the year.Two distinctly different configurations are available for the turbine design, the horizontal axis configuration and the vertical axis configuration (Tong, 2010).However, most modern wind turbines use horizontal-axis design (Okeniyi et al., 2014).The power extracted by the blades is customarily expressed as a fraction of the upstream wind power as follows (Burton et al., 2011): where, ρ is air density (kg/m), A is area swept by the rotor blades (m 2 ), V is velocity of the air, m/sec 2 and C p is the fraction of the upstream wind power, which is captured by the rotor blades.The theoretical maximum value of C p is 0.59 (Kumar et al., 2013).In practical designs, the maximum achievable C p is below 0.5 for high-speed, two-blade turbines and between 0.2 and 0.4 for slow speed turbines with more blades (Table 1).
The LGED (Local Government Engineering Department) provided us the data for 6 regions named Kuaktata, Kutubdia, Sitakunda, Khagrachori, Nawga and Pakshi.We have analyzed the three regions Kuaktata, Kutubdia and Sitakunda data with the help of the software named WINDOGRAPHER (Windographer, 2014).

RESULTS AND DISCUSSION
At first, we have found out the Weibull probability distribution function 'h' with two parameters, the shape parameter 'k' and the scale parameter 'c' (Odo et al., 2012).At most sites the wind speed has the Weibull distribution with k = 2, which is specifically known as the Rayleigh distribution.Here, at Kuakata at 30 m height, the value of the shape parameter 'k' is 2.003 and the scale parameter 'c' is 4.68 m/sec and the mean wind speed at Kuakata at 30 m height is 4.14 m/sec i.e., most of the time the wind speed is 4.14 m/sec.The mean wind power density found at the Kuakata at 30 m height is 85 W/m 2 and the mean energy content is 745 kW/m 2 /year and the energy pattern factor is 1.958.On the other hand the mean wind speed, wind power density and mean energy content at the Kutubdia are,  -----------------------------------------Kutubdia  ------------------------------------------Sitakunda  ------------------------------ Wind shear analysis provides the wind speed at any height (Pope et al., 2010).The wind shear profiles of Kuakata, Kutubdia and Sitakunda are shown in Fig. 2 to 4, respectively.From the figures it is seen at 50 m height the wind speed of Kuakata is 5.41 m/sec, the wind speed of Kutubdia is 5.41 m/sec and the wind speed of Sitakunda is 4.48 m/sec.The value of power law exponent at 50 m height at Kuakata is 0.687, at Kutubdia is 0.488 and at Sitakunda is 0.478.

Wind profile of selected location:
The wind profile of any location represents all the necessary graph of a wind regime.The wind profile of selected location Kuakata are: • Power density Monthly wind speed profile of Fig. 5 mainly shows the wind speed at a certain location for 12 months i.e., whole year and the wind speed are shown according to day time of 24 h.There are 12 graphs for 12 months.From this profile, we can easily understand how wind speed varied with different months.
Daily wind speed profile mainly shows the wind speed variation of a certain location with the single day (Fig. 6).
Seasonal wind speed profile includes the wind speed variation of a region during a season i.e., from January to December (Fig. 7).
The probability distribution function of Fig. 8 gives the probability that the wind speed will take a value.Here, it is expressed using a frequency histogram, which gives the frequency with which the wind speed falls within certain ranges (Alam and Azad, 2014).
Figure 9 monthly average power density shows that at the starting of the year i.e., in January the wind power density is low and it continues to march.From April, the speed starts to increase and at June, July and August, there is so much density.After that, it continues to decline and the rest of the year, there is no significant density.

Wind turbine analysis:
A wind turbine needs five types of data for calculating its output power, these are: • Annemeter height where the mean speed is found Here we have analyzed different ratings turbine from MW range to few kW.Here, we use five different ratings turbine these are: Figure 10 compares the output power of different turbine according to percentage of rated power.From the figure it is seen that for a particular wind speed we will get a higher output for the turbine Entegrity eW-50 Hz and Fuhrländer FL 30.
The output of Fuhrländer FL30 and Southwest Skystream 3.7 are decreases with high wind speed but no change in the output of Enercon E33 and Suzlon S.62/1000 (Windpower, 2014).results are essential to find the optimum system and sensitivity analysis through which we can choose our expected system (Bataineh et al., 2014).

Hybrid power system:
Cash flow summary: HOMER simulates the operation of a system by making energy balance calculations for each of the 8,760 h in a year.This section describes how to enter cost data for diesel generators, wind turbines and batteries.For example cash flow summary tells that installing a spatial type of wind turbine in the system initial capital is costs $30000, replacing the wind turbine cost is $10422 and operation and  2008).Figure 12 shows the lifecycle cost of the system, accounting for the capital, replacement, operation and maintenance, fuel and interest costs.Here we can view hourly energy flows for each component as well as annual cost and performance summaries.
Energy sharing: Figure 13 represents the monthly average energy production by wind turbine and diesel generator.Such as, from April to September when wind blows at a high speed then the wind turbine produces more energy.Average annually electricity production from the hybrid system is 44,467 kWh/year in which 36% electricity comes from a wind source and 64% Optimization and sensitivity analysis: Sensitivity results of hybrid power system display the operating cost variation with the variation of wind speed and diesel price.From the result shown in Fig. 14 and 15 it is seen that when the wind speed increases operating cost decreases.It is also seen that the wind and diesel system is more cost effective than the system with no wind turbine.For example, when the wind speed is 4.2 m/sec and the price of diesel price is $ 0.70/L, then the operating cost of the only diesel system is $ 28,044.At the same time when the wind speed is 4.6 m/sec and the price of diesel price is $ 0.70/L, then the operating cost of the wind and diesel system is $ 24,865.

CONCLUSION
Whole world is suffering from power crisis.This crisis is likely to be more severe if we mere depend on available mineral power resources.It is the high time we sought for alternative means.Renewable energy can be converted to electrical energy through proper means which is gainful.All of the analyses have presented here is helpful to obtain an optimum wind power system.Substantial amount of electrical energy can be produced from available wind power of coastal area.Basically this analysis provides a simulation based technical process and financial comparison of using wind energy to meet our present and future electrical energy demand.The system proposed here can be further optimized through the use of solar energy along with wind turbine.Such hybrid power system is suitable for low cost high profit production.

Fig. 5 :
Fig. 5: Monthly wind speed profile • Monthly wind speed profile • Daily wind speed profile Figure 11 is a hybrid power system which is considered for simulation.Simulation

Fig
Fig. 12: Cost at different sector

Table 1 :
Wind speed sensor summary of different locations