Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements

This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. T...

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Bibliographic Details
Published in:Applied sciences 2020-12, Vol.10 (24), p.8975
Main Authors: M’zoughi, Fares, Garrido, Izaskun, Garrido, Aitor J., De La Sen, Manuel
Format: Article
Language:English
Subjects:
acoustic doppler current profiler
Air pollution
Alternative energy sources
artificial neural network
back-to-back converter
Carbon dioxide
Climate change
Design
Emissions
Energy efficiency
Induction generators
Neural networks
oscillating water column
Paris Agreement
R&D
Research & development
rotational speed control
Speed control
stalling behavior
Turbines
Turbulence models
Water circulation
Wave power
Wells turbines
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Summary:This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. The ANN-based MPPT predicts the optimal rotational speed reference from wave amplitude and period. The neural network has been trained and uses wave surface elevation measurements gathered by an acoustic Doppler current profiler. The implemented ANN-based rotational speed control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which improved the power generation.
ISSN:2076-3417
2076-3417
DOI:10.3390/app10248975