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Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter

Author

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  • Thiyagarajan Rameshkumar

    (Department of Electrical and Electronics Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India)

  • Perumal Chandrasekar

    (Department of Electrical and Electronics Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India)

  • Raju Kannadasan

    (Department of Electrical and Electronics Engineering, Sri Venkateswara College of Engineering, Sriperubudur 602117, India)

  • Venkatraman Thiyagarajan

    (Department of Electrical and Electronics Engineering, Sri Sivasubramaniya Nadar (SSN) College of Engineering, Chennai 603110, India)

  • Mohammed H. Alsharif

    (Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, Seoul 05006, Korea)

  • James Hyungkwan Kim

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720, USA)

Abstract

Permanent magnet synchronous generator (PMSG)-based wind turbine systems have a wide range of applications, notably, for higher-rated wind energy conversion systems (WECS). A WECS involves integrating several components to generate electrical power effectively on a large scale due to the advanced wind turbine model. However, it offers several glitches during operation due to various factors, notably, mechanical and electrical stresses. This work focuses on evaluating the mechanical and electrical characteristics of the WECS using two individual schemes. Firstly, wind turbines were examined to assess the vibrational signatures of the drive train components for different wind speed profiles. To apply this need, acoustic sensors were employed that record the vibration signals. However, due to substantial environmental impacts, several noises are logged with the observed signal from sensors. Therefore, this work adapted the acoustic signal and empirical wavelet transform (EWT) to assess the vibration frequency and magnitude to avoid mechanical failures. Further, a matrix converter (MC) with input filters was employed to enhance the efficiency of the system with reduced harmonic contents injected into the grid. The simulated results reveal that the efficiency of the matrix converter with input filter attained a significant scale of about 95.75% and outperformed the other existing converting techniques. Moreover, the total harmonic distortion (THD) for voltage and current were examined and found to be at least about 8.24% and 3.16%, respectively. Furthermore, the frequency and magnitude of the vibration signals show a minimum scale for low wind speed profile and higher range for medium wind profile rather than higher wind profile. Consolidating these results from both mechanical and electrical characteristics, it can be perceived that the combination of these schemes improves the efficiency and quality of generated power with pre-estimation of mechanical failures using acoustic signal and EWT.

Suggested Citation

  • Thiyagarajan Rameshkumar & Perumal Chandrasekar & Raju Kannadasan & Venkatraman Thiyagarajan & Mohammed H. Alsharif & James Hyungkwan Kim, 2022. "Electrical and Mechanical Characteristics Assessment of Wind Turbine System Employing Acoustic Sensors and Matrix Converter," Sustainability, MDPI, vol. 14(8), pages 1-22, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4404-:d:788926
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    References listed on IDEAS

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    1. Liu, Zepeng & Zhang, Long & Carrasco, Joaquin, 2020. "Vibration analysis for large-scale wind turbine blade bearing fault detection with an empirical wavelet thresholding method," Renewable Energy, Elsevier, vol. 146(C), pages 99-110.
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    3. Varadharajan Sankaralingam Sriraja Balaguru & Nesamony Jothi Swaroopan & Kannadasan Raju & Mohammed H. Alsharif & Mun-Kyeom Kim, 2021. "Techno-Economic Investigation of Wind Energy Potential in Selected Sites with Uncertainty Factors," Sustainability, MDPI, vol. 13(4), pages 1-31, February.
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    5. Mohanasundaram Anthony & Valsalal Prasad & Kannadasan Raju & Mohammed H. Alsharif & Zong Woo Geem & Junhee Hong, 2020. "Design of Rotor Blades for Vertical Axis Wind Turbine with Wind Flow Modifier for Low Wind Profile Areas," Sustainability, MDPI, vol. 12(19), pages 1-26, September.
    6. Mani Rajalakshmi & Sankaralingam Chandramohan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "Design and Validation of BAT Algorithm-Based Photovoltaic System Using Simplified High Gain Quasi Boost Inverter," Energies, MDPI, vol. 14(4), pages 1-24, February.
    7. Krishnamoorthy R & Udhayakumar K & Kannadasan Raju & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "An Assessment of Onshore and Offshore Wind Energy Potential in India Using Moth Flame Optimization," Energies, MDPI, vol. 13(12), pages 1-41, June.
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