Analysis of Wind Energy Potential and Optimum Wind Blade Design for Jamshoro Wind Corridor

Pakistan is facing energy crisis since last decade. This crisis can be effectively handled by utilizing alternative energy resources. Pakistan has a huge wind energy potential of about 50,000MW. The contribution of costal area of Sindh, Pakistan in the total wind energy potential is about 43000MW. The Jamshoro wind corridor has the highest wind potential of all coastal areas of Sindh. In this paper a wind blade design has been developed and optimized for Jamshoro wind corridor. The theoretical blade design include the airfoil selection, appropriate chord length selection and optimization of twist angle. The designed blade has been analyzed using Q-blade. Considering the Jamshorowind conditions, blade of around 43 meters have been designed and optimized theoretically. Then the theoretical design is also been checked and verified in Q-blade. Theoretical optimization includes using different combinations of NACA profiles and using exhaustive iterative method to get optimized twist angle. This ensures the design with maximum power output with respect to wind speed of Jamshoro. For low wind speeds, theoretical results and simulated results in Q-blade were almost same but for high wind speeds, results were significantly different due to limitation of iterations in theoretical design.


INTRODUCTION
end the power crisis of Pakistan but also reduces the generation cost of electricity in Pakistan but unfortunately this potential has never been exploited before.
The monthly wind speed as well as wind power density for different stations in Sindh has been plotted in Fig. 1(a-b) [3]. Amongst those stations, Jamshoro having the mean wind speed of 8.5m/s and wind power density of 770W/m 2 can be classified as excellent site for wind power generation according to classification of Pak Metrological Department [3]. T he shortfall of Pakistan energy has reached a level of 4406 MW [1]. This shortfall can be covered by using renewable resources including wind, solar, hydel, biofuel and geothermal energies. The estimated wind energy potential of Pakistan is 50,000MW [2]. Alone from the coastal areas of Pakistan, 43,000 MW electricity can be produced [3].It was further estimated that of the total coastal area of Sindh, about 9700 Km 2 area can be used to generate 11,000 MW electricity through wind turbines. This much electricity can not only The main focus of this paper is to design an optimum wind blade for the Jamshoro wind corridor that can produce maximum power output and this can only be achieved when it can harness maximum wind energy. Fig. 2 shows steps to design an optimum wind blade. Equations used for optimization of twist angle and chord length distributions are have been deduced from BEM (Blade Element Momentum) theory [4]. Different blade profiles have been analyzed and then combination of best blade profiles have been used and then verified in Q-blade.

BLADE DESIGN PROCEDURE
Following are the steps for designing the wind turbine blade [5]: (1) Power output from wind turbine can be calculated as follows: Where P is the power output, C p is performance coefficient,η is the mechanical and electrical efficiencies, R is the tip radius, V is the wind velocity. (2) The value of Power Coefficient (C p ) is being set by Betz limit which sets an upper limit of 0.59 of the theoretically achievable energy from the available wind energy. Normally power coefficient (C p ) = 0.4 [6][7].
(3) η can be assumed around 0.9 because it accounts to losses occurred in mechanical components e.g. generator, gearbox etc. of wind turbine [8].
(5) Number of blades is to be selected from Table 1 [11]. It has the vital role in maintaining the geometrical stability of the blade.
After selecting airfoils, aerodynamic conditions for each airfoil will be selected. It is common to consider 80% of the C L (airfoil lift coefficient)for calculating optimized twist angle for each section [12].
(8) After selecting airfoil aerodynamic conditions, blade is divided into 10-20 sections [13]. Each section has got its own airfoil so individual section can be optimized.
(9) Chord width, twist angle and Reynolds number are calculated according to following equations.
The Reynolds Number is given as: The Twist Angle is: Iterative process is being adopted for twist angle.
Following are the steps.
Make an initial guess of axial induction factor (a) and a / . Calculate solidity (σ') and β.
(b) Choose appropriate C L and C D for the angle of incidence.
(c) Calculate a and a / again until Δa and Δa / converges.

WIND TURBINE BLADE DESIGN FOR JAMSHORO
The input parameters for the blade design for Jamshoro are presented in the following section. These parameters will be used to compute theoretical design. Later, simulations in Q-blade will be performed to validate the design.

Input Parameters
In July Jamshoro has got the highest wind speed of 13.9m/ s and in January lowest wind speed of 5m/s. keeping in view the above conditions, following parameters were selected for the design: (1) Power Coefficient (C p ) = 0.4 [14][15].

THEORETICAL DESIGN VERIFICATION USING Q-BLADE
While simulating the blade design in Q-Blade software, first of all NACA profiles were declared as shown in Speed graph in Q-blade simulation is shown in Fig. 6.
The theoretical calculation revealed a power output value of 161.9 KW at 5m/s wind speed. The Q-blade simulation results give slightly higher power output of 163KW. Also simulated power output for 13.9m/s wind speed is 4MW but theoretical power output is 3.48MW. The power difference between theoretical and simulated design is small for minimum wind speed of 5m/s. On the other hand, the power difference between theoretical and simulated design is significant for maximum wind   Fig. 7.
The blade designed for the Jamshoro wind corridor has been optimized according to the wind speed data presented in Fig. 1. However, if the wind speed become higher than the maximum observed speed of 13.9 m/s, the corresponding Reynolds number will be higher. In such case the blade should be redesigned.
The Reynolds number is given by Equation (3). This equation implies that for higher Reynolds number the cord length should by decreased accordingly, resulting in dull blade. The variation of chord length with wind energy is illustrated in Fig. 8. It has been shown that chord length decrease linearly with wind velocity.

CONCLUSIONS
Wind blade was designed in accordance with BEM theoryfor wind conditions of Jamshoro. Also basic parameters for wind blade design were identified and analyzed and then using those parameters, theoretical design was prepared and then verified with Q-blade. The theoretical results reveal that for minimum wind speed equal to 5m/s (in January), the power is equal to 161.9KW.
For the high wind speed equal to13.9m/s (in July) the power is 3.48MW. The Q-blade analysis showed that for minimum wind speed of 5m/s power is 163KW. For high wind speed equal to 13.9m/s, the power is 4MW. The power difference between theoretical and simulated design is small for minimum wind speed of 5m/s, In case of maximum wind speed, the difference between theoretical and simulated design is more because Q-blade uses BEM theory for optimization of the wind blade. It has changed the power coefficient to 0.47 that results in higher coefficients.
The design presented in this paper can be validated with HARP which is a MATLAB optimization toolbox. Similarly the optimization can be performed with respect to efficiency using optimization function and optimization algorithms for achieving maximum efficiency. However the efficiency optimization should be performed such that the cost of design is unaffected.