ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements

Oscillating water column (OWC) plants face power generation limitations due to the stalling phenomenon. This behavior can be avoided by an airflow control strategy that can anticipate the incoming peak waves and reduce its airflow velocity within the turbine duct. In this sense, this work aims to us...

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Autores: M'Zoughi, Fares, Garrido Hernández, Izaskun, Garrido Hernández, Aitor Josu, De la Sen Parte, Manuel
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/42389
Acceso en línea:http://hdl.handle.net/10810/42389
Access Level:acceso abierto
Palabra clave:acoustic doppler current profiler
airflow control
artificial neural network
oscillating water column
power generation
stalling behavior
wave energy
Wells turbine
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spelling ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation MeasurementsM'Zoughi, FaresGarrido Hernández, IzaskunGarrido Hernández, Aitor JosuDe la Sen Parte, Manuelacoustic doppler current profilerairflow controlartificial neural networkoscillating water columnpower generationstalling behaviorwave energyWells turbineOscillating water column (OWC) plants face power generation limitations due to the stalling phenomenon. This behavior can be avoided by an airflow control strategy that can anticipate the incoming peak waves and reduce its airflow velocity within the turbine duct. In this sense, this work aims to use the power of artificial neural networks (ANN) to recognize the different incoming waves in order to distinguish the strong waves that provoke the stalling behavior and generate a suitable airflow speed reference for the airflow control scheme. The ANN is, therefore, trained using real surface elevation measurements of the waves. The ANN-based airflow control will control an air valve in the capture chamber to adjust the airflow speed as required. A comparative study has been carried out to compare the ANN-based airflow control to the uncontrolled OWC system in different sea conditions. Also, another study has been carried out using real measured wave input data and generated power of the NEREIDA wave power plant. Results show the effectiveness of the proposed ANN airflow control against the uncontrolled case ensuring power generation improvement.This work was supported in part by the Basque Government, through project IT1207-19 and by the MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE).MDPI2020202020202020info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/42389reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoInglésinfo:eu-repo/grantAgreement/MCIU/RTI2018-094902-B-C21/info:eu-repo/grantAgreement/MCIU/RTI2018-094902-B-C22/https://www.mdpi.com/1424-8220/20/5/1352info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/es/© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).oai:addi.ehu.eus:10810/423892026-06-18T09:23:17Z
dc.title.none.fl_str_mv ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
title ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
spellingShingle ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
M'Zoughi, Fares
acoustic doppler current profiler
airflow control
artificial neural network
oscillating water column
power generation
stalling behavior
wave energy
Wells turbine
title_short ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
title_full ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
title_fullStr ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
title_full_unstemmed ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
title_sort ANN-Based Airflow Control for an Oscillating Water Column Using Surface Elevation Measurements
dc.creator.none.fl_str_mv M'Zoughi, Fares
Garrido Hernández, Izaskun
Garrido Hernández, Aitor Josu
De la Sen Parte, Manuel
author M'Zoughi, Fares
author_facet M'Zoughi, Fares
Garrido Hernández, Izaskun
Garrido Hernández, Aitor Josu
De la Sen Parte, Manuel
author_role author
author2 Garrido Hernández, Izaskun
Garrido Hernández, Aitor Josu
De la Sen Parte, Manuel
author2_role author
author
author
dc.subject.none.fl_str_mv acoustic doppler current profiler
airflow control
artificial neural network
oscillating water column
power generation
stalling behavior
wave energy
Wells turbine
topic acoustic doppler current profiler
airflow control
artificial neural network
oscillating water column
power generation
stalling behavior
wave energy
Wells turbine
description Oscillating water column (OWC) plants face power generation limitations due to the stalling phenomenon. This behavior can be avoided by an airflow control strategy that can anticipate the incoming peak waves and reduce its airflow velocity within the turbine duct. In this sense, this work aims to use the power of artificial neural networks (ANN) to recognize the different incoming waves in order to distinguish the strong waves that provoke the stalling behavior and generate a suitable airflow speed reference for the airflow control scheme. The ANN is, therefore, trained using real surface elevation measurements of the waves. The ANN-based airflow control will control an air valve in the capture chamber to adjust the airflow speed as required. A comparative study has been carried out to compare the ANN-based airflow control to the uncontrolled OWC system in different sea conditions. Also, another study has been carried out using real measured wave input data and generated power of the NEREIDA wave power plant. Results show the effectiveness of the proposed ANN airflow control against the uncontrolled case ensuring power generation improvement.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/42389
url http://hdl.handle.net/10810/42389
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MCIU/RTI2018-094902-B-C21/
info:eu-repo/grantAgreement/MCIU/RTI2018-094902-B-C22/
https://www.mdpi.com/1424-8220/20/5/1352
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/es/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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