Industrial IoT based condition monitoring for wind energy conversion system

Abstract

Wind energy has become a second dominating source in the world renewable energy generation. Conversion and distribution of the wind energy have brought technology revolution by developing advanced wind energy conversion system (WECS) including multilevel inverters (MLI). The conventional rectifier produces ripples in their output waveforms while MLI suffers from voltage balancing issue across 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. On the other hand, 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 early stages, they may lead to catastrophic failures to the WECS and continuity of power supply. This paper proposes a new algorithm embedded into 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 associated hardware prototype is proposed to monitor the condition of WECS in real-time environment.

RAS ID

38950

Document Type

Journal Article

Date of Publication

2020

School

School of Science / Electron Science Research Institute

Copyright

free_to_read

Publisher

Chinese Society of Electrical Engineering

Comments

Hossain, M. L., Abu-Siada, A., Muyeen, S. M., Hasan, M. M., & Rahman, M. M. (2020). Industrial IoT based condition monitoring for wind energy conversion system. CSEE Journal of Power and Energy Systems, 7(3), 654-664. https://doi.org/10.17775/CSEEJPES.2

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Link to publisher version (DOI)

10.17775/CSEEJPES.2020.00680