Bidding strategy of wind-thermal energy producers
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/7160 |
Resumo: | This paper presents a stochastic mixed-integer linear programming approach for solving the selfscheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An effi- cient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Bidding strategy of wind-thermal energy producersBidding strategyStochastic programmingMixed integer linear programmingWind thermal coordinationThis paper presents a stochastic mixed-integer linear programming approach for solving the selfscheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An effi- cient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.UID/EMS/50022/2013ElsevierRCIPLLaia, R.Pousinho, H. M. I.Melício, R.Mendes, Victor2017-06-07T10:39:16Z20162016-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/7160engLAIA, R.; [et al] - Bidding strategy of wind-thermal energy producers. Renewable Energy. ISSN 0960-1481. Vol. 99, (2016), pp. 673-6810960-148110.1016/j.renene.2016.07.049metadata only accessinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T09:52:52Zoai:repositorio.ipl.pt:10400.21/7160Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:16:10.033185Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Bidding strategy of wind-thermal energy producers |
title |
Bidding strategy of wind-thermal energy producers |
spellingShingle |
Bidding strategy of wind-thermal energy producers Laia, R. Bidding strategy Stochastic programming Mixed integer linear programming Wind thermal coordination |
title_short |
Bidding strategy of wind-thermal energy producers |
title_full |
Bidding strategy of wind-thermal energy producers |
title_fullStr |
Bidding strategy of wind-thermal energy producers |
title_full_unstemmed |
Bidding strategy of wind-thermal energy producers |
title_sort |
Bidding strategy of wind-thermal energy producers |
author |
Laia, R. |
author_facet |
Laia, R. Pousinho, H. M. I. Melício, R. Mendes, Victor |
author_role |
author |
author2 |
Pousinho, H. M. I. Melício, R. Mendes, Victor |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Laia, R. Pousinho, H. M. I. Melício, R. Mendes, Victor |
dc.subject.por.fl_str_mv |
Bidding strategy Stochastic programming Mixed integer linear programming Wind thermal coordination |
topic |
Bidding strategy Stochastic programming Mixed integer linear programming Wind thermal coordination |
description |
This paper presents a stochastic mixed-integer linear programming approach for solving the selfscheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An effi- cient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016 2016-01-01T00:00:00Z 2017-06-07T10:39:16Z |
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/10400.21/7160 |
url |
http://hdl.handle.net/10400.21/7160 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
LAIA, R.; [et al] - Bidding strategy of wind-thermal energy producers. Renewable Energy. ISSN 0960-1481. Vol. 99, (2016), pp. 673-681 0960-1481 10.1016/j.renene.2016.07.049 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
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1799133421185794048 |