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Control tuning by genetic algorithm of a low scale model wind turbine

dc.book.title17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)
dc.contributor.authorAndrade Aimara , Giordy Alexander
dc.contributor.authorEsteban San Román, Segundo
dc.contributor.authorSantos Peñas, Matilde
dc.contributor.editorGarcía Bringas, P.
dc.date.accessioned2025-01-24T12:39:17Z
dc.date.available2025-01-24T12:39:17Z
dc.date.issued2023
dc.description.abstractThe continuous rise of wind energy makes it necessary to design controllers that make turbines more and more efficient. However, control designs are usually developed in simulation, which does not consider the many factors that affect control in a real turbine. An intermediate step, before testing them on turbines, is to check them on prototypes. In this paper, a first design of a laboratory scale model of a wind turbine (WT) is proposed, with the aim of testing different control algorithms. The model is built with commercial hardware and “ad hoc” circuits. Two control loops have been implemented; an external loop that commands the electric charge, and an internal loop that controls the pitch of the blades. The controllers have been tuned first experimentally, obtaining the best possible behavior by trial and error. Using genetic algorithms, the most optimal values for the controller are obtained, improving the response of the system. The operating and functional modes of a real WT have been also replicated on the model using a microcontroller programmed with the Arduino IDE input-output. Results obtained using optimized conventional controllers prove the correct performance of the prototype.
dc.description.departmentDepto. de Arquitectura de Computadores y Automática
dc.description.facultyFac. de Ciencias Físicas
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia e Innovación (España)
dc.description.statuspub
dc.identifier.citationAndrade Aimara, G.A., Esteban San Román, S., Santos, M. (2023). Control Tuning by Genetic Algorithm of a Low Scale Model Wind Turbine. In: García Bringas, P., et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_50
dc.identifier.doi10.1007/978-3-031-18050-7_50
dc.identifier.essn2367-3389
dc.identifier.isbn978-3-031-18049-1
dc.identifier.issn2367-3370
dc.identifier.officialurlhttps://doi.org/10.1007/978-3-031-18050-7_50
dc.identifier.relatedurlhttp://2022.sococonference.eu/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/116033
dc.language.isoeng
dc.page.final524
dc.page.initial515
dc.publication.placeSalamanca
dc.publisherSpringer
dc.relation.ispartofseriesLecture Notes in Networks and Systems
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/ RTI2018–094902-B-C21/ES/ WINDWAVE. ANÁLISIS Y CONTROL DE UN DISPOSITIVO FLOTANTE HÍBRIDO DE ENERGÍA EÓLICA Y MARINA
dc.rights.accessRightsrestricted access
dc.subject.cdu537
dc.subject.keywordWind turbine
dc.subject.keywordControl
dc.subject.keywordGenetic algorithms
dc.subject.keywordScale model
dc.subject.keywordPrototype
dc.subject.keywordArduino
dc.subject.ucmElectrónica (Física)
dc.subject.ucmElectrónica (Informática)
dc.subject.ucmProgramación de ordenadores (Informática)
dc.subject.unesco3311.02 Ingeniería de Control
dc.subject.unesco3311.01 Tecnología de la Automatización
dc.titleControl tuning by genetic algorithm of a low scale model wind turbine
dc.typebook part
dc.type.hasVersionVoR
dc.volume.number531
dspace.entity.typePublication
relation.isAuthorOfPublication386f94e5-c78d-49d3-8046-ece83adf5ecc
relation.isAuthorOfPublication99cac82a-8d31-45a5-bb8d-8248a4d6fe7f
relation.isAuthorOfPublication.latestForDiscovery386f94e5-c78d-49d3-8046-ece83adf5ecc

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