Wind farm layout optimization under uncertainty
Main Author: | |
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Publication Date: | 2024 |
Other Authors: | |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10773/43167 |
Summary: | Wind power is a major source of green energy production. However, the energy generation of wind power is highly affected by uncertainty. Here, we consider the problem of designing the cable network that interconnects the turbines to the substation in wind farms, aiming to minimize both the infrastructure cost and the cost of the energy losses during the wind farm’s lifetime. Nonetheless, the energy losses depend on wind direction and speed, which are rarely known with certainty in real situations. Hence, the design of the network should consider these losses as uncertain parameters. We assume that the exact probability distribution of these parameters is unknown but belongs to an ambiguity set and propose a distributionally robust two-stage mixed integer model. The model is solved using a decomposition algorithm. Three enhancements are proposed given the computational difficulty in solving real problem instances. Computational results are reported based on real data. |
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Wind farm layout optimization under uncertaintyWind farm layout optimizationdistributionally robust optimizationdecomposition algorithmWind power is a major source of green energy production. However, the energy generation of wind power is highly affected by uncertainty. Here, we consider the problem of designing the cable network that interconnects the turbines to the substation in wind farms, aiming to minimize both the infrastructure cost and the cost of the energy losses during the wind farm’s lifetime. Nonetheless, the energy losses depend on wind direction and speed, which are rarely known with certainty in real situations. Hence, the design of the network should consider these losses as uncertain parameters. We assume that the exact probability distribution of these parameters is unknown but belongs to an ambiguity set and propose a distributionally robust two-stage mixed integer model. The model is solved using a decomposition algorithm. Three enhancements are proposed given the computational difficulty in solving real problem instances. Computational results are reported based on real data.Springer Nature2025-07-01T00:00:00Z2024-01-01T00:00:00Z2024info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/43167eng1134-576410.1007/s11750-023-00663-7Agra, AgostinhoCerveira, Adelaideinfo: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:RCAAP2025-01-13T01:48:34Zoai:ria.ua.pt:10773/43167Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:39:11.988872Repositórios 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 |
Wind farm layout optimization under uncertainty |
title |
Wind farm layout optimization under uncertainty |
spellingShingle |
Wind farm layout optimization under uncertainty Agra, Agostinho Wind farm layout optimization distributionally robust optimization decomposition algorithm |
title_short |
Wind farm layout optimization under uncertainty |
title_full |
Wind farm layout optimization under uncertainty |
title_fullStr |
Wind farm layout optimization under uncertainty |
title_full_unstemmed |
Wind farm layout optimization under uncertainty |
title_sort |
Wind farm layout optimization under uncertainty |
author |
Agra, Agostinho |
author_facet |
Agra, Agostinho Cerveira, Adelaide |
author_role |
author |
author2 |
Cerveira, Adelaide |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Agra, Agostinho Cerveira, Adelaide |
dc.subject.por.fl_str_mv |
Wind farm layout optimization distributionally robust optimization decomposition algorithm |
topic |
Wind farm layout optimization distributionally robust optimization decomposition algorithm |
description |
Wind power is a major source of green energy production. However, the energy generation of wind power is highly affected by uncertainty. Here, we consider the problem of designing the cable network that interconnects the turbines to the substation in wind farms, aiming to minimize both the infrastructure cost and the cost of the energy losses during the wind farm’s lifetime. Nonetheless, the energy losses depend on wind direction and speed, which are rarely known with certainty in real situations. Hence, the design of the network should consider these losses as uncertain parameters. We assume that the exact probability distribution of these parameters is unknown but belongs to an ambiguity set and propose a distributionally robust two-stage mixed integer model. The model is solved using a decomposition algorithm. Three enhancements are proposed given the computational difficulty in solving real problem instances. Computational results are reported based on real data. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-01-01T00:00:00Z 2024 2025-07-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/43167 |
url |
http://hdl.handle.net/10773/43167 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1134-5764 10.1007/s11750-023-00663-7 |
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.publisher.none.fl_str_mv |
Springer Nature |
publisher.none.fl_str_mv |
Springer Nature |
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 |
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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 |
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1833598234313883648 |