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Flow Control in Wells Turbines for Harnessing Maximum Wave Power

Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In th...

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Autores principales: Lekube, Jon, Garrido, Aitor J., Garrido, Izaskun, Otaola, Erlantz, Maseda, Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855045/
https://www.ncbi.nlm.nih.gov/pubmed/29439408
http://dx.doi.org/10.3390/s18020535
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author Lekube, Jon
Garrido, Aitor J.
Garrido, Izaskun
Otaola, Erlantz
Maseda, Javier
author_facet Lekube, Jon
Garrido, Aitor J.
Garrido, Izaskun
Otaola, Erlantz
Maseda, Javier
author_sort Lekube, Jon
collection PubMed
description Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness.
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spelling pubmed-58550452018-03-20 Flow Control in Wells Turbines for Harnessing Maximum Wave Power Lekube, Jon Garrido, Aitor J. Garrido, Izaskun Otaola, Erlantz Maseda, Javier Sensors (Basel) Article Oceans, and particularly waves, offer a huge potential for energy harnessing all over the world. Nevertheless, the performance of current energy converters does not yet allow us to use the wave energy efficiently. However, new control techniques can improve the efficiency of energy converters. In this sense, the plant sensors play a key role within the control scheme, as necessary tools for parameter measuring and monitoring that are then used as control input variables to the feedback loop. Therefore, the aim of this work is to manage the rotational speed control loop in order to optimize the output power. With the help of outward looking sensors, a Maximum Power Point Tracking (MPPT) technique is employed to maximize the system efficiency. Then, the control decisions are based on the pressure drop measured by pressure sensors located along the turbine. A complete wave-to-wire model is developed so as to validate the performance of the proposed control method. For this purpose, a novel sensor-based flow controller is implemented based on the different measured signals. Thus, the performance of the proposed controller has been analyzed and compared with a case of uncontrolled plant. The simulations demonstrate that the flow control-based MPPT strategy is able to increase the output power, and they confirm both the viability and goodness. MDPI 2018-02-10 /pmc/articles/PMC5855045/ /pubmed/29439408 http://dx.doi.org/10.3390/s18020535 Text en © 2018 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/).
spellingShingle Article
Lekube, Jon
Garrido, Aitor J.
Garrido, Izaskun
Otaola, Erlantz
Maseda, Javier
Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title_full Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title_fullStr Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title_full_unstemmed Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title_short Flow Control in Wells Turbines for Harnessing Maximum Wave Power
title_sort flow control in wells turbines for harnessing maximum wave power
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5855045/
https://www.ncbi.nlm.nih.gov/pubmed/29439408
http://dx.doi.org/10.3390/s18020535
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