- Title
- Industrial IoT based condition monitoring for wind energy conversion system
- Creator
- Hossain, Md Liton; Abu-Siada, Ahmed; Muyeen, S.; Hasan, Mubashwar; Rahman, Md Momtazur
- Date
- 2021
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/177890
- Identifier
- vital:15353
- Identifier
-
https://doi.org/10.17775/CSEEJPES.2020.00680
- Identifier
- ISBN:2096-0042 (ISSN)
- Abstract
- Wind energy has been identified as the second dominating source in the world renewable energy generation after hydropower. Conversion and distribution of wind energy has brought technology revolution by developing the advanced wind energy conversion system (WECS) including multilevel inverters (MLIs). The conventional rectifier produces ripples in their output waveforms while the MLI suffers from voltage balancing issues across the DC-link capacitor. This paper proposes a simplified proportional integral (PI)-based space vector pulse width modulation (SVPWM) to minimize the output waveform ripples, resolve the voltage balancing issue and produce better-quality output waveforms. WECS experiences various types of faults particularly in the DC-link capacitor and switching devices of the power converter. These faults, if not detected and rectified at an early stage, may lead to catastrophic failures to the WECS and continuity of the power supply. This paper proposes a new algorithm embedded in the proposed PI-based SVPWM controller to identify the fault location in the power converter in real time. Since most wind power plants are located in remote areas or offshore, WECS condition monitoring needs to be developed over the internet of things (IoT) to ensure system reliability. In this paper, an industrial IoT algorithm with an associated hardware prototype is proposed to monitor the condition of WECS in the real-time environment. © 2015 CSEE.
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- CSEE Journal of Power and Energy Systems Vol. 7, no. 3 (2021), p. 654-664
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2020 CSEE
- Rights
- Open Access
- Subject
- 0906 Electrical and Electronic Engineering; Asset management; Condition monitoring; Fault diagnosis; Industrial internet of things (IoT); Wind energy conversion system
- Full Text
- Reviewed
- Funder
- The first author would like to thank Curtin International Postgraduate Research Scholarship (CIPRS) and Curtin Strategic International Research Scholarship (CSIRS) program for supporting this research.
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