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Machine Learning Applications in Power System Condition Monitoring

Author

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  • Bruce Stephen

    (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

Abstract

While machine learning has made inroads into many industries, power systems have some unique application constraints and barriers that have motivated the creation of this Special Issue on their applications in condition monitoring [...]

Suggested Citation

  • Bruce Stephen, 2022. "Machine Learning Applications in Power System Condition Monitoring," Energies, MDPI, vol. 15(5), pages 1-2, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1808-:d:761507
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    References listed on IDEAS

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    1. Becky Corley & Sofia Koukoura & James Carroll & Alasdair McDonald, 2021. "Combination of Thermal Modelling and Machine Learning Approaches for Fault Detection in Wind Turbine Gearboxes," Energies, MDPI, vol. 14(5), pages 1-14, March.
    2. Wenshuo Tang & Darius Roman & Ross Dickie & Valentin Robu & David Flynn, 2020. "Prognostics and Health Management for the Optimization of Marine Hybrid Energy Systems," Energies, MDPI, vol. 13(18), pages 1-29, September.
    3. Phong B. Dao, 2021. "A CUSUM-Based Approach for Condition Monitoring and Fault Diagnosis of Wind Turbines," Energies, MDPI, vol. 14(11), pages 1-19, June.
    4. Conor McKinnon & James Carroll & Alasdair McDonald & Sofia Koukoura & David Infield & Conaill Soraghan, 2020. "Comparison of New Anomaly Detection Technique for Wind Turbine Condition Monitoring Using Gearbox SCADA Data," Energies, MDPI, vol. 13(19), pages 1-19, October.
    5. Xingshuo Li & Jinfu Liu & Jiajia Li & Xianling Li & Peigang Yan & Daren Yu, 2020. "A Stacked Denoising Sparse Autoencoder Based Fault Early Warning Method for Feedwater Heater Performance Degradation," Energies, MDPI, vol. 13(22), pages 1-21, November.
    6. Eleni Tsioumpri & Bruce Stephen & Stephen D. J. McArthur, 2021. "Weather Related Fault Prediction in Minimally Monitored Distribution Networks," Energies, MDPI, vol. 14(8), pages 1-21, April.
    7. Conor McKinnon & Alan Turnbull & Sofia Koukoura & James Carroll & Alasdair McDonald, 2020. "Effect of Time History on Normal Behaviour Modelling Using SCADA Data to Predict Wind Turbine Failures," Energies, MDPI, vol. 13(18), pages 1-19, September.
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    Cited by:

    1. Sepideh Radhoush & Bradley M. Whitaker & Hashem Nehrir, 2023. "An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks," Energies, MDPI, vol. 16(16), pages 1-29, August.

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