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A Short-Term Outage Model of Wind Turbines with Doubly Fed Induction Generators Based on Supervisory Control and Data Acquisition Data

Author

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  • Peng Sun

    (The State Key Laboratory of Power Transmission Equipment and System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China)

  • Jian Li

    (The State Key Laboratory of Power Transmission Equipment and System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China)

  • Junsheng Chen

    (The State Key Laboratory of Power Transmission Equipment and System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China)

  • Xiao Lei

    (The State Key Laboratory of Power Transmission Equipment and System Security and New Technology, College of Electrical Engineering, Chongqing University, Chongqing 400044, China)

Abstract

This paper presents a short-term wind turbine (WT) outage model based on the data collected from a wind farm supervisory control and data acquisition (SCADA) system. Neural networks (NNs) are used to establish prediction models of the WT condition parameters that are dependent on environmental conditions such as ambient temperature and wind speed. The prediction error distributions are discussed and used to calculate probabilities of the operation of protection relays (POPRs) that were caused by the threshold exceedance of the environmentally sensitive parameters. The POPRs for other condition parameters are based on the setting time of the operation of protection relays. The union probability method is used to integrate the probabilities of operation of each protection relay to predict the WT short term outage probability. The proposed method has been used for real 1.5 MW WTs with doubly fed induction generators (DFIGs). The results show that the proposed method is more effective in WT outage probability prediction than traditional methods.

Suggested Citation

  • Peng Sun & Jian Li & Junsheng Chen & Xiao Lei, 2016. "A Short-Term Outage Model of Wind Turbines with Doubly Fed Induction Generators Based on Supervisory Control and Data Acquisition Data," Energies, MDPI, vol. 9(11), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:11:p:882-:d:81576
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    References listed on IDEAS

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    Cited by:

    1. Yancai Xiao & Ruolan Dai & Guangjian Zhang & Weijia Chen, 2017. "The Use of an Improved LSSVM and Joint Normalization on Temperature Prediction of Gearbox Output Shaft in DFWT," Energies, MDPI, vol. 10(11), pages 1-13, November.

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