INTRODUCTION

From the past ten years, the usage and supply of fossil fuels are decreasing due to their harmful impact on the environment, which on the other hand, increases the demand for renewable energy sources [1].Support for the usage of renewable energy sources has been increased, not because of the enhancement of power efficiency, but due to maintaining the criteria of climate goals [2] and consequently intensify the dependency of the renewable energy source as a means to mitigate the traditional way to generate energy on the environment. Electricity not only becomes an indispensable factor for the growth and improvement of human society but also plays a vital role in the industrial sector for economic and product development [3].Due to this reason power becomes a source that it should be accessible to every other corner of the world. One way to generate electricity is to use wind as a renewable energy source and utilize it through wind turbine which can convert the kinetic energy present in the wind to meaningful electricity [4]. Another way is the usage of the photovoltaic cell, where electricity production is executed by converting the solar radiation through the process of the photoelectric effect. Despite greater performance and cost-effectiveness of photovoltaic panel technology, the usage of wind energy has reached a greater extent in the last few years. For instance, in 2017, 34% of the increase in wind power installation has been observed in Europe as compared to 2016[5]. Due to an increase in demand, wind turbine technology has become a prominent area for doing research. Various control techniques have been executed to enhance the power output and control the structural damage due to aeroelasticity. Apart from this, various research has been focused on intensifying the use of wind turbines in a turbulence environment. Bahaj et al. proposed that, as an alternative to traditional energy supply, micro-generation technology is also providing power to the user’s home or buildings [6].Miller et al. [7] analyses different numerical techniques implemented in the wind energy industry which incorporate the significant territories for research, such as micro-scale siting, wind modeling and forecast, blade optimization, flow modeling and support structure investigation. The prediction of blade aerodynamics is required for the performance of the turbine, and two significant strategies for numerical prediction has been considered, and they are blade element momentum theory and computational fluid dynamics. A few investigations that have been done by utilizing these strategies for the prediction of turbine performance are incorporated as follows: Lanzafame and Messina [8] used the code based on BEM and utilized it to operate HAWT to its maximum power coefficients. They observed that there is an optimum rotational velocity which gives maximum power for a given streamline velocity. The dynamic stall model has been implemented in modified BEM theory by Dai et al. [9] to predict the forces on large scale wind turbines. It was inferred that this dynamic model is best suited for engineering purposes. Vaz et al. [10] utilizes BEM and develop a mathematical model for the design of a horizontal axis wind turbine blade. Various researchers have used the CFD technique to simulate the NREL turbines by solving Navier stokes equations. As CFD is capable of simulating the complete flow field, the results obtained from these methods are more accurate than the BEM method. CFD simulation of the NREL phase II turbine has been done by Duque et al. [11], and both NREL phase II and NREL phase III turbines simulation is executed by Xu and Sankar [12]. However, the numerical investigation of NREL phase VI turbine using CFD is simulated by Xu and Sankar [13], Johansen et al. [14], Duque et al. [15] and Sezer-Uzol and Long [16].Thumthae and Chitsomboon [17] used the blade of no twist for getting the optimal angle of attack for different wind speed by performing the numerical simulation. The operating conditions considered for this simulation includes pitch angles 1°, 3°, 50, 7° and 12° for the wind speed of 7.2, 8.0, 9.0 and 10.5 m/s. The results obtained from CFD Analysis were validated against the NREL experimental results. Mo and Lee [18] investigated small-sized wind turbines of NREL phase VI to understand its aerodynamic behavior by using the CFD technique, and they considered five different wind velocity in the range of 7 m/s and 25 m/s with a global pitch angle of 5°. SST k-w model was considered for turbulence modeling. They observed stall near the root of the blade at 7 m/s. Li et al. [19] use incompressible dynamic overset code CFD ShipIowa v4.5 to carry out the numerical investigation on the performance full-scale NREL phase VI turbine. The study was accomplished by fixing the pitch angle of blade as 3° and varying the wind velocities to 5. 10. 15 and 25 m/s, and changing the pitch angles from 15° to 40° at a fixed wind speed of 15 m/s. simulation was completed by taking the rotational speed of 72 rpm and using turbulence model as detached eddy simulation. Various performance parameters like power, thrust and pressure variation around airfoil were validated with the experimental results. In this way, it is seen that the pitch angle has an impact on the turbine performance, and for maximum power, it is necessary to observe the best pitch angle for given wind speed and rotor speed. The target of the present work is to analyze the impact of a pitch angle on the performance and aerodynamics of a horizontal axis wind turbine, NREL Phase VI at various wind speeds. In the present investigation, the impact of pitch angle in the horizontal axis wind turbine blade is identified along with the S809 airfoil analysis. This investigation can give data to the researcher to design and optimize the blade effectively by identifying the optimum pitch angle for the corresponding velocity.
This paper is structured as follows. Section 2 presents the governing equations; the next methodology is present in section 3 comprising two components, i.e., wind turbine model, and CFD modeling, Results, and discussions are presented in Section 3, followed by a conclusion in Section 4.