Optimal maintenance management of offshore wind turbines by minimizing the costs

Renewable and sustainable energy production systems offer promising perspectives for the future, as their production and maintenance prices decrease, and their efficiency and reliability increase, favouring the competitiveness of this industry. Thereby, wind energy is one of the most used and develo...

Descripción completa

Detalles Bibliográficos
Autores: Peinado Gonzalo, Alfredo, Benmessaoud, Tahar, Entezami, Mani, García Márquez, Fausto Pedro
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/36247
Acceso en línea:https://hdl.handle.net/10578/36247
Access Level:acceso abierto
Palabra clave:Maintenance
Wind farm
Offshore
Genetic Algorithms (GA)
Particle Swarm Optimization (PSO)
id ES_e4c02c8f638bfbf005abc34905c4e99e
oai_identifier_str oai:ruidera.uclm.es:10578/36247
network_acronym_str ES
network_name_str España
spelling Optimal maintenance management of offshore wind turbines by minimizing the costs Peinado Gonzalo, Alfredo Benmessaoud, Tahar Entezami, Mani García Márquez, Fausto Pedro Maintenance Wind farm Offshore Genetic Algorithms (GA) Particle Swarm Optimization (PSO) Renewable and sustainable energy production systems offer promising perspectives for the future, as their production and maintenance prices decrease, and their efficiency and reliability increase, favouring the competitiveness of this industry. Thereby, wind energy is one of the most used and developed as renewable energy, since it is a cost-effective way to generate clean and sustainable energy. Wind energy is divided into onshore and offshore depending on the wind farm location. Offshore wind energy is increasing its use. However, the offshore industry requires more maintenance, which is also more complicated to do because of the environmental conditions. Setting the best maintenance strategy becomes a complicated optimization problem with several objectives and constraint functions. In this paper, a novel multi-objective optimization problem is defined and solved for real case studies by using Genetic Algorithms and Particle Swarm Optimization to minimize operational costs and maximize performance of the wind turbines. The results of both algorithms are compared considering several scenarios in a real case study. These results show a better performance of Particle Swarm Optimization for optimal cost achieved, and less computational cost to solve it. Finally, the influence of the model parameters is studied by performing a sensitivity study, that shows the importance of preventive maintenance and the reduction of corrective maintenance tasks. Elsevier https://hdl.handle.net/10578/36247
title Optimal maintenance management of offshore wind turbines by minimizing the costs
spellingShingle Optimal maintenance management of offshore wind turbines by minimizing the costs
Peinado Gonzalo, Alfredo
Maintenance
Wind farm
Offshore
Genetic Algorithms (GA)
Particle Swarm Optimization (PSO)
title_short Optimal maintenance management of offshore wind turbines by minimizing the costs
title_full Optimal maintenance management of offshore wind turbines by minimizing the costs
title_fullStr Optimal maintenance management of offshore wind turbines by minimizing the costs
title_full_unstemmed Optimal maintenance management of offshore wind turbines by minimizing the costs
title_sort Optimal maintenance management of offshore wind turbines by minimizing the costs
author Peinado Gonzalo, Alfredo
author_facet Peinado Gonzalo, Alfredo
Benmessaoud, Tahar
Entezami, Mani
García Márquez, Fausto Pedro
author_role author
author2 Benmessaoud, Tahar
Entezami, Mani
García Márquez, Fausto Pedro
author2_role author
author
author
topic Maintenance
Wind farm
Offshore
Genetic Algorithms (GA)
Particle Swarm Optimization (PSO)
topic_facet Maintenance
Wind farm
Offshore
Genetic Algorithms (GA)
Particle Swarm Optimization (PSO)
description Renewable and sustainable energy production systems offer promising perspectives for the future, as their production and maintenance prices decrease, and their efficiency and reliability increase, favouring the competitiveness of this industry. Thereby, wind energy is one of the most used and developed as renewable energy, since it is a cost-effective way to generate clean and sustainable energy. Wind energy is divided into onshore and offshore depending on the wind farm location. Offshore wind energy is increasing its use. However, the offshore industry requires more maintenance, which is also more complicated to do because of the environmental conditions. Setting the best maintenance strategy becomes a complicated optimization problem with several objectives and constraint functions. In this paper, a novel multi-objective optimization problem is defined and solved for real case studies by using Genetic Algorithms and Particle Swarm Optimization to minimize operational costs and maximize performance of the wind turbines. The results of both algorithms are compared considering several scenarios in a real case study. These results show a better performance of Particle Swarm Optimization for optimal cost achieved, and less computational cost to solve it. Finally, the influence of the model parameters is studied by performing a sensitivity study, that shows the importance of preventive maintenance and the reduction of corrective maintenance tasks.
publishDate 2022
format article
url https://hdl.handle.net/10578/36247
eu_rights_str_mv openAccess
publisher Elsevier
institution Universidad de Castilla-La Mancha
collection RUIdeRA. Repositorio Institucional de la UCLM
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
instname_str Universidad de Castilla-La Mancha
_version_ 1878442123222581248
publishDateSort 2022
author_browse Benmessaoud, Tahar
Entezami, Mani
García Márquez, Fausto Pedro
Peinado Gonzalo, Alfredo
publisherStr Elsevier
score 6,9303427

Similares en LA Referencia