Blades icing identification model of wind turbines based on SCADA data

Xinghui Dong, Di Gao, Jia Li, Zhang Jincao and Kai Zheng

Renewable Energy, 2020, vol. 162, issue C, 575-586

Abstract: Blades icing would reduce the aerodynamic performance, cause power generation loss of WTGs, and even affect the safety of production and operation. By analyzing the relationship between blades icing and Supervisory Control And Data Acquisition (SCADA) data characteristic parameters at different stages in the process of wind turbines generating energy transfer, the paper calculated the accompanying changes in blades icing timing of Wind Turbine Generator System (WTGs) output power performance, mechanical performance and aerodynamic performance characteristic parameters. This paper then applies the residual to describe the deviation degree of each characteristic parameters value, and establishes the blades icing identification model by progressive parameterization judgment form. In addition, combined with the statistical properties of historical meteorological parameters of blades icing, the timely and accurate determination of blades icing was achieved. The identification results of the model are reliable and accurate through the verification of blades icing examples in different regions and of different wind turbines. The blades icing identification model based on SCADA data variation characteristics does not require adding new hardware and software investment, but it has even higher sensitivity. It can make accurate judgment in the early icing process, which is conducive to implement the control strategy and develop de-icing plan in advance.

Keywords: Wind turbines; Blades; Icing identification; SCADA data; Residual (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:162:y:2020:i:c:p:575-586

DOI: 10.1016/j.renene.2020.07.049

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