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MS - Horizontal axis wind turbine modelling and data analysis by multilinear regression

MS - Horizontal axis wind turbine modelling and data analysis by multilinear regression

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Abstract. The modelling of each horizontal axis wind turbine (HAWT) differs due to variation in operating conditions, dynamic parameters, and components. Thus, the choice of profiles also varies for specific applications. So for the better choice of profiles, the wind turbine performance is analysed for different parameters and working conditions. The efficiency of HAWTs mainly depends on the blade, which in turn is related to the profile of the blade, blade orientation, and tip size. Hence, the main aim of the present work is to evaluate the performance of HAWTs for three different blade tip sizes and six different blade twist angles for three major NACA (National Advisory Committee for Aeronautics) airfoils. A statistical analysis is also carried out to find the influence of different performance parameters such as drag, lift, vorticity, and normal force. The static design parameters are considered based on the available literature. A three-bladed offshore HAWT is adopted as the research object in the study. Data visualization using star glyphs and sunray plots is performed, along with multilinear regression analysis. From the multilinear regression analysis and reliable empirical correlations, it is known that drag coefficient and lift coefficient parameters have less significance in contrast to the other parameters which have more significance in the regression model. The different results obtained in terms of parametric coefficients provide an effective way to generate appropriate airfoil profiles for given HAWTs. Thus, the study helps to achieve better turbine performance, and it serves as a benchmark for future studies on HAWTs.