COMPUTATIONAL ANALYSIS OF FLUID STRUCTURE INTERACTION (FSI) IN HORIZONTAL AXIS WIND TURBINES (HAWTS)

Abstract

Wind power plays a crucial role in the worldwide shift towards sustainable and renewable sources of energy. Wind turbine power generation performances made them a widely adopted method for electricity production, playing a crucial role in the world’s energy resources. Accordingly, optimizing the wind turbine blade’s design is essential for increasing wind turbine performance and reducing expenses. The main aim of this capstone project is to analyze the Fluid Structure Interaction of the HAWTs and to achieve the most effective design of the turbine, in terms of power generation performance and resource requirement by optimizing the blades using low fidelity methods. In engineering and scientific studies, low-fidelity and high-fidelity simulation and optimization have become common concepts, especially in the field of wind turbine design and analysis. These concepts are essential in order to study computational structure and controlling the resource demand, as well as improving the operation of the turbines. This paper focuses on applying low-fidelity optimization techniques with QBlade, which is a commonly used open-source software for creating aerodynamic simulations of horizontal axis wind turbines. A low-fidelity simulation can involve simplified fluid dynamics calculations and simplified structural models, in the context of wind turbine design, in order to forecast the turbine’s effectiveness. Compared to the high-fidelity simulations, low fidelity simulations are economically and computationally reasonable. It means that, in the process of optimization of design parameters of the wind turbine more design alternatives are available in order to reach the most effective parameters. Computational Analysis of Fluid-Structure Interaction (FSI) within Horizontal Axis Wind Turbines (HAWTs) will be studied on the NREL 5MW and NREL Phase VI turbine. In order to get the optimization results of these wind turbine blades, low fidelity optimization methods, such as Betz and Schmitz theories will be used.