Journal
APPLIED SCIENCES-BASEL
Volume 10, Issue 24, Pages -Publisher
MDPI
DOI: 10.3390/app10248975
Keywords
acoustic doppler current profiler; artificial neural network; back-to-back converter; oscillating water column; rotational speed control; stalling behavior; wave energy; wells turbine
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Funding
- Basque Government [IT1207-19]
- MCIU/MINECO [RTI2018-094902-B-C21/RTI2018-094902-B-C22]
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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.
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