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Power loss by blade deflection in flexible rotor wind turbines
Abstract
Effects of deflection onto the performance of small wind turbines with flexible rotor-blades have been studied and analysed. The goal of the study has been the evaluation of the wind turbine output power loss due to angular deflection because of bending effects caused by gravity. Wind turbine blades have been deformed under constant load at the tip of the blade for periods up to 40 days. Deformation process has been accelerated using a very heavy load and the corresponding angular deflection has been obtained. Wind turbine performance has been characterized through the P-V curve for different wind speed operation conditions. Tests have been run for different deformation states to compare the evolution of the power loss with angular deflection. Results from experimental tests have shown there is a constant power loss with deformation increase. Power reduction for angular deflection of 2.3º is between 35% and 45% for blade tip wind speed from 27.6 m/s to 42 m/s. Power coefficient, Cp, has also been analyzed and determined for the angular deflection of 2.3º and 4.3º; the reduction of the power coefficient value has been computed through a power loss factor, fP, that shows a reduction in the range of 25% to 50% for the 2.3º angular deflection, and between 45% and 55% for the angular deflection of 4.3º.
References
Mohammad Asadi, Rahim Hassanzadeh et.al, Effects of internal rotor parameters on the performance of a two bladed Darrieus-two bladed Savonius hybrid wind turbine, Energy Conversion and Management, June(2021);Volume 238.
Behnam Moghadassian, Anupam Sharma et al, Designing wind turbine rotor blades to enhance energy capture in turbine arrays, Renewable Energy, 2020, Volume 148, Pp 651-664.
Widad Yossri, Samah Ben Ayed, et al.., Airfoil type and blade size effects on the aerodynamic performance of small-scale wind turbines: Computational fluid dynamics investigation, Energy, (2021) ;Volume 229.
B.Pitchia Krishnan, M.Mathanbabu, G.Sathyamoorthy, K.Gokulnath, L.Govind Sanjeev Kumar Performance estimation and redesign of horizontal axis wind turbine (HAWT) blade, Materialstoday Proceedings, Available online March 2021.
Júlio Xavier Vianna Neto, Elci José Guerra Junior, Sinvaldo Rodrigues Moreno, Helon Vicente Hultmann Ayala, Viviana Cocco Mariania, Leandro dos Santos Coelho, Wind turbine blade geometry design based on multi-objective optimization using metaheuristics, Energy, 1 November 2018, Volume 162;Pp 645-658.
Ahmed Riyad Ali, Md. Zishan Akhter, Farag Khalifa Omar Performance enhancement of a small-scale wind turbine featuring morphed trailing edge, Sustainable Energy Technologies and Assessments, 2021;Volume 46.
Erfan Salimipour, Shima Yazdani (2020) Improvement of aerodynamic performance of an offshore wind turbine blade by moving surface mechanism, Ocean Engineering, Volume 195.
Lucas I.Lago, Fernando L.Ponta, Alejandro D.Otero (2013) Analysis of alternative adaptive geometrical configurations for the NREL-5 MW wind turbine blade, Renewable Energy, Volume 59, Pp13-22.
Widad Yossri, Samah Ben Ayed, Abdessattar Abdelkefi (2021) Airfoil type and blade size effects on the aerodynamic performance of small-scale wind turbines: Computational fluid dynamics investigation, Energy, Volume 229.
Achilles M.Boulamatsis, Thanasis K.Barlas, Herricos Stapountzis (2019) Active control of wind turbines through varying blade tip sweep, Renewable Energy, Volume 131PP 25-36.
Fernando L.Ponta, Alejandro D.Otero, Lucas I.Lago, Anurag Rajan (2016) Effects of rotor deformation in wind-turbine performance: The Dynamic Rotor Deformation Blade Element Momentum model (DRD–BEM), Renewable Energy, Volume 92, Pp 157-170.
Kevin Cox, Andreas Echtermeyer Geometric Scaling Effects of Bend-twist Coupling in Rotor Blades, Energy Procedia, (2013) ; Volume 35, Pp2-11.
Fernando L.Ponta, Alejandro D.Otero, et. al (2014) The adaptive-blade concept in wind-power applications, Energy for Sustainable Development, Volume 22, Pp 3-12
C. Armenta-Déu .Effects of Rotor-Blade Deformation onto Performance of Domestic Wind Turbines, Journal of Alternate Energy Sources & Technologies, (2021);Volume 12, No. 1, Pp27-42
B. Dose, H. Rahimi, B. Stoevesandt, J. Peinke, J.G. Schepers3 ;On the effect of blade deformations on the aerodynamic performance of wind turbine rotors subjected to yawed inflow, Journal of Physics: Conference Series, Volume 1037, Issue 2. (2018).
L. Li, Y. H. Li, Q. K. Liu, B. K. Jiang, Effect of balance weight on dynamic characteristics of a rotating wind turbine blade, Journal of Engineering Mathematics (2015);volume 97, Pp 49–65.
Jianwei Li, Jinghua Wang, Leian Zhang, Xuemei Huang, Yongfeng Yu ;Study on the Effect of Different Delamination Defects on Buckling Behavior of Spar Cap in Wind Turbine Blade, Advances in Materials Science and Engineering, Volume 2020.
Zhaoyong Mao, Wenlong Tian ; Effect of the blade arc angle on the performance of a Savonius wind turbine, Advances in Mechanical Engineering, (2015);Volume 7, Issue 5.
Mehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, Seyedali Mirjalili, Daniele Groppi, Azim Heydari, Lina Bertling Tjernberg, Davide Astiaso Garcia, Bradley Alexander, Qinfeng Shi, Markus Wagner (2021) Wind turbine power output prediction using a new hybrid neuro-evolutionary method, Energy, Volume 229.
Despina Karamichailidou, Vasiliki Kalouts, Alex Alexandridis (2021) Wind turbine power curve modeling using radial basis function neural networks and tabu search, Renewable Energy Volume 163, Pp 2137-2152.
Peter Enevoldsen, Mark Z.Jacobson (2021) Data investigation of installed and output power densities of onshore and offshore wind turbines worldwide, Energy for Sustainable Development, Volume 60, Pp 40-51
XinLiu, Zheming Cao, Zijun Zhang; Short-term predictions of multiple wind turbine power outputs based on deep neural networks with transfer learning, Energy, (2021);Volume 217.
Paul A.Adedeji, Stephen Akinlabi, Nkosinathi Madushele, Obafemi O.Olatunji (2020) Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model, Journal of Cleaner Production, Volume 254.
Qing'an Li, Chang Cai, Yasunari Kamada, Takao Maeda, Yuto Hiromori, Shuni Zhou, Jianzhong Xua (2021) Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model, Energy, Volume 231.
L.J.S.Bradbury (2013) The probability density distribution for the power output from arrays of wind turbines and the intermittent nature of wind power, Journal of Wind Engineering and Industrial Aerodynamics, Volume 123, Part A, Pp 121-129.
Katharina Garus (2014) Wind measurement based on rotor blade deformation, Sun & Wind Energy, https://www.sunwindenergy.com/wind-energy/wind-measurement-based-rotor-blade-deformation
M. H. El-Ahmar; Abou-Hashema M. El-Sayed; A. M. Hemeida ;Evaluation of factors affecting wind turbine output power, Nineteenth International Middle East Power Systems Conference (MEPCON), 19-21 December (2017); Cairo, Egypt, IEEEXplore, Feb 27; (2018).
J.F. Manwell, J.G. McGowan, A.L. Rogers, Wind Energy Explained, Theory, Design and Applications, Ed. John Wiley and Sons, 2002
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