STUDY ON TURBULENCE IDENTIFICATION AND LOAD REDUCTION OF WIND TURBINES BASED ON MONITORING DATA

Wang Yazhou; Cai Xin; Lin Shifa; Wang Hao; Zhang Yuan; Bian Saixian

doi:10.19912/j.0254-0096.tynxb.2022-0076

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (6) : 360-366. DOI: 10.19912/j.0254-0096.tynxb.2022-0076

STUDY ON TURBULENCE IDENTIFICATION AND LOAD REDUCTION OF WIND TURBINES BASED ON MONITORING DATA

Wang Yazhou¹, Cai Xin¹, Lin Shifa², Wang Hao³, Zhang Yuan⁴, Bian Saixian²

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Abstract

Aiming at the problem that the extreme load of wind turbine often occurs in extreme turbulent flow conditions, which endangers the operation safety of wind turbine, a turbulence intensity identification method based on wind turbine monitoring data was proposed, a calculation model of turbulence threshold indirectly calculated by nacelle acceleration was constructed, and a load reduction strategy was proposed for extreme turbulent flow conditions. Load reduction often results in generating capacity loss, so a mathematical model for load reduction optimization under extreme turbulent flow conditions is established. By solving the extreme value of the objective function satisfying the constraints, both load reduction and generating capacity can be achieved. Finally, a 5 MW wind turbine is taken as an example to verify the research results through numerical simulation, The results show that the ultimate loads of hub M_y and tower top M_y are reduced by 15% and 12.1%,respectively, and the loads of other parts are reduced by about 5%, without loss of power generation under normal conditions.

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wind turbines / turbulence / monitoring / load reduction / turbulence threshold

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Wang Yazhou, Cai Xin, Lin Shifa, Wang Hao, Zhang Yuan, Bian Saixian. STUDY ON TURBULENCE IDENTIFICATION AND LOAD REDUCTION OF WIND TURBINES BASED ON MONITORING DATA[J]. Acta Energiae Solaris Sinica. 2023, 44(6): 360-366 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0076

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