Publications
International Journal on Smart Sensing and Intelligent Systems
Professor Subhas Chandra Mukhopadhyay
Exeley Inc. (New York)
Subject: Computational Science & Engineering, Engineering, Electrical & Electronic
eISSN: 1178-5608
SEARCH WITHIN CONTENT
SMART SENSING SYSTEM FOR ENHANCEING THE RELIABILITY OF POWER ELECTRONIC DEVICES
USED IN WIND TURBINES
S. H. Teay / C. Batunlu / A. Albarbar
Keywords : Autonomous sensor, lifetime consumption analysis, online rainflow algorithm, dSPACE, finite element, IGBT temperature.
Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 10, Issue 2, Pages 407-424, DOI: https://doi.org/10.21307/ijssis-2017-218
License : (CC BY-NC-ND 4.0)
Received Date : 02-February-2017 / Accepted: 19-April-2017 / Published Online: 01-June-2017
- ARTICLE
- FIGURES & TABLES
- REFERENCES
- EXTRA FILES
- COMMENTS
ARTICLE
ABSTRACT
Reliability of modern power systems, in particular those use wind and solar energies, is affected by the relatively short lifetime of the associated power electronic converters (PECs). Thermal stress has been identified as one of the commonest causes for failures in PECs. However, existing thermal monitoring systems are expensive, bulky and with no intelligent capabilities, which limit their full acceptance as monitoring and control tools in operational power plants. This work presents autonomous and inexpensive microcontroller-based system for monitoring and predicting thermal behaviour of switching devices used in PECs. System’s inputs are non-intrusively measured voltages and currents drawn by those devices while in operation. The developed system also determines lifetime consumption and has the ability to communicate with external monitoring and control systems e.g. supervisory, control and data acquisition (SCADA) platforms. The performance of the developed system was critically assessed and compared with high-resolution thermal
imaging camera. Good agreement between both systems was achieved and the inexpensive
developed system was found to have an accuracy of 95%.
FIGURES & TABLES
REFERENCES
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