Ageing assessment of a wind turbine over time by interpreting wind farm SCADA data

被引：70

作者：

Dai, Juchuan ^{[1
,2
]}

Yang, Wenxian ^{[2
,3
]}

Cao, Junwei ^{[1
]}

Liu, Deshun ^{[1
]}

Long, Xing ^{[4
]}

机构：

[1] Hunan Univ Sci & Technol, Sch Electromech Engn, Xiangtan 411201, Peoples R China

[2] Newcastle Univ, Sch Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[3] Hunan Inst Engn, Hunan Prov Cooperat Innovat Ctr Wind Power Equipm, Xiangtan 411104, Peoples R China

[4] XEMC Windpower Co Ltd, Xiangtan 411000, Peoples R China

来源：

RENEWABLE ENERGY | 2018年 / 116卷

关键词：

Wind turbines; Ageing assessment; Performance degradation; SCADA data; KERNEL DENSITY-ESTIMATION; FAULT-DIAGNOSIS; PREDICTION; BEM; OPTIMIZATION; MAINTENANCE; PERFORMANCE; MODEL;

D O I：

10.1016/j.renene.2017.03.097

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Ageing of a wind turbine and its components is inevitable. It will affect the reliability and power generation of the turbine over time. Therefore, performing the ageing assessment of wind turbines is of significance not only to optimize the operation and maintenance strategy of the wind turbine but also to improve the management of a wind farm. However, in contrast to the significant number of research on wind turbine condition monitoring and reliability analysis, little effort was made before to investigate the ageing led performance degradation issue of wind turbines over time. To fill such a technology gap, four SCADA-based wind turbine ageing assessment criteria are proposed in this paper for measuring the ageing resultant performance degradation of the turbine. With the aid of these four criteria, a reliable information fusion based wind turbine ageing assessment method is developed and verified in the end using the real wind farm SCADA data. It has been shown that the proposed method is effective and reliable in performing the ageing assessment of a wind turbine. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：199 / 208

页数：10

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