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.