RAM factors in the operation and maintenance phase of wind turbines
Main Author: | |
---|---|
Publication Date: | 2012 |
Other Authors: | , , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/1822/21695 |
Summary: | The high complexity of technological systems and the increasing requirement and competitiveness of markets request the implementation of adequate management strategies for these systems in order to improve their availability and productivity. In this context, RAM factors constitute a strategic approach for integrating reliability, availability and maintainability, by using methods, tools and engineering techniques to identify and quantify equipment and system failures that prevent the achievement of its objectives. This paper presents the most relevant aspects and findings of a study conducted for assessing the operational performance of a wind turbine system installed in a wind farm in Portugal. The study was based on the analysis of the behavior of states defined for each individual wind turbine over a period of two years, and was aimed to identify and evaluate the effects of RAM-type factors. Given the structure and nature of the data, a Markov Chain approach was adopted for this evaluation. The main finding was that the usage of a particular technique (the frequency and duration technique) is adequate to effectively evaluate the overall performance of the wind farm and find opportunities for improvements. |
id |
RCAP_cf5fb44168cb5f35f008d05d202bef1c |
---|---|
oai_identifier_str |
oai:repositorium.sdum.uminho.pt:1822/21695 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
RAM factors in the operation and maintenance phase of wind turbinesRAM factorsReliabilityAvailabilityMaintainabilityThe high complexity of technological systems and the increasing requirement and competitiveness of markets request the implementation of adequate management strategies for these systems in order to improve their availability and productivity. In this context, RAM factors constitute a strategic approach for integrating reliability, availability and maintainability, by using methods, tools and engineering techniques to identify and quantify equipment and system failures that prevent the achievement of its objectives. This paper presents the most relevant aspects and findings of a study conducted for assessing the operational performance of a wind turbine system installed in a wind farm in Portugal. The study was based on the analysis of the behavior of states defined for each individual wind turbine over a period of two years, and was aimed to identify and evaluate the effects of RAM-type factors. Given the structure and nature of the data, a Markov Chain approach was adopted for this evaluation. The main finding was that the usage of a particular technique (the frequency and duration technique) is adequate to effectively evaluate the overall performance of the wind farm and find opportunities for improvements.This work is financed with FEDER Funds by Programa Operacional Fatores de Competitividade – COMPETE and by National Funds by FCT – Fundação para a Ciência e Tecnologia, Project: FCOMP-01-0124-FEDER- 022674Universidade do MinhoCajazeira, Carolina Leite BarbosaNunes, Eusébio P.Telhada, JoséCarvalho, Mariana Teixeira Baptista de2012-072012-07-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/21695enghttp://www.icieom.org/artigosicieom.aspinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:46:09Zoai:repositorium.sdum.uminho.pt:1822/21695Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:03:45.778065Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
RAM factors in the operation and maintenance phase of wind turbines |
title |
RAM factors in the operation and maintenance phase of wind turbines |
spellingShingle |
RAM factors in the operation and maintenance phase of wind turbines Cajazeira, Carolina Leite Barbosa RAM factors Reliability Availability Maintainability |
title_short |
RAM factors in the operation and maintenance phase of wind turbines |
title_full |
RAM factors in the operation and maintenance phase of wind turbines |
title_fullStr |
RAM factors in the operation and maintenance phase of wind turbines |
title_full_unstemmed |
RAM factors in the operation and maintenance phase of wind turbines |
title_sort |
RAM factors in the operation and maintenance phase of wind turbines |
author |
Cajazeira, Carolina Leite Barbosa |
author_facet |
Cajazeira, Carolina Leite Barbosa Nunes, Eusébio P. Telhada, José Carvalho, Mariana Teixeira Baptista de |
author_role |
author |
author2 |
Nunes, Eusébio P. Telhada, José Carvalho, Mariana Teixeira Baptista de |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Cajazeira, Carolina Leite Barbosa Nunes, Eusébio P. Telhada, José Carvalho, Mariana Teixeira Baptista de |
dc.subject.por.fl_str_mv |
RAM factors Reliability Availability Maintainability |
topic |
RAM factors Reliability Availability Maintainability |
description |
The high complexity of technological systems and the increasing requirement and competitiveness of markets request the implementation of adequate management strategies for these systems in order to improve their availability and productivity. In this context, RAM factors constitute a strategic approach for integrating reliability, availability and maintainability, by using methods, tools and engineering techniques to identify and quantify equipment and system failures that prevent the achievement of its objectives. This paper presents the most relevant aspects and findings of a study conducted for assessing the operational performance of a wind turbine system installed in a wind farm in Portugal. The study was based on the analysis of the behavior of states defined for each individual wind turbine over a period of two years, and was aimed to identify and evaluate the effects of RAM-type factors. Given the structure and nature of the data, a Markov Chain approach was adopted for this evaluation. The main finding was that the usage of a particular technique (the frequency and duration technique) is adequate to effectively evaluate the overall performance of the wind farm and find opportunities for improvements. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-07 2012-07-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/21695 |
url |
http://hdl.handle.net/1822/21695 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.icieom.org/artigosicieom.asp |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833595712396328960 |