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

Thiyagarajan Rameshkumar, Perumal Chandrasekar, Raju Kannadasan, Venkatraman Thiyagarajan, Mohammed H. Alsharif and James Hyungkwan Kim
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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

Sustainability, 2022, vol. 14, issue 8, 1-22

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.

Keywords: acoustic sensors; empirical wavelet transform (EWT); matrix converter; input filter; power quality; vibrational assessment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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