Alarms management by supervisory control and data acquisition system for wind turbines

被引：0
|
作者：
Ramirez I.S. [1 ]
Mohammadi-Ivatloo B. [2 ,3 ]
Márquez F.P.G. [1 ]
机构：
[1] Ingenium Research Group, Universidad Castilla-La Mancha, Ciudad Real
[2] Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz
[3] Department of Energy Technology, Aalborg University, Aalborg East
来源：
Eksploatacja i Niezawodnosc | 2021年 / 23卷 / 01期
关键词：
Alarm management; Maintenance management; Principal component analysis; SCADA; Wind turbines;
D O I：
10.17531/EIN.2021.1.12
中图分类号：
学科分类号：
摘要：
Wind energy is one of the most relevant renewable energy. A proper wind turbine maintenance management is required to ensure continuous operation and optimized maintenance costs. Larger wind turbines are being installed and they require new monitoring systems to ensure optimization, reliability and availability. Advanced analytics are employed to analyze the data and reduce false alarms, avoiding unplanned downtimes and increasing costs. Supervisory control and data acquisition system determines the condition of the wind turbine providing large dataset with different signals and alarms. This paper presents a new approach combining statistical analysis and advanced algorithm for signal processing, fault detection and diagnosis. Principal component analysis and artificial neural networks are employed to evaluate the signals and detect the alarm activation pattern. The dataset has been reduced by 93% and the performance of the neural network is incremented by 1000% in comparison with the performance of original dataset without filtering process. © 2021, Polish Academy of Sciences Branch Lublin. All rights reserved.
引用
收藏
页码：110 / 116
页数：6
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