Self-scheduling and bidding strategies of thermal units with stochastic emission constraints
Autor(a) principal: | |
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Data de Publicação: | 2015 |
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/10400.21/5731 |
Resumo: | This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. 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. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved. |
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Self-scheduling and bidding strategies of thermal units with stochastic emission constraintsBidding strategyBilateral contractsEmission allowancesStochastic programmingThermal self-schedulingThis paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. 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. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.Pergamon-Elsevier Science LTDRCIPLLaia, RuiPousinho, Hugo Miguel InácioMelício, RuiMendes, Victor2016-02-24T15:41:06Z2015-01-012015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/5731engLAIA, Rui; [et al.] - Self-scheduling and bidding strategies of thermal units with stochastic emission constraints. Energy Conversion and Management. ISSN. 0196-8904. Vol. 89 (2015), pp. 975-9840196-890410.1016/j.enconman.2014.10.063metadata 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:RCAAP2023-08-03T09:49:34Zoai:repositorio.ipl.pt:10400.21/5731Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:14:58.543979Repositório 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 |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
title |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
spellingShingle |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints Laia, Rui Bidding strategy Bilateral contracts Emission allowances Stochastic programming Thermal self-scheduling |
title_short |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
title_full |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
title_fullStr |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
title_full_unstemmed |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
title_sort |
Self-scheduling and bidding strategies of thermal units with stochastic emission constraints |
author |
Laia, Rui |
author_facet |
Laia, Rui Pousinho, Hugo Miguel Inácio Melício, Rui Mendes, Victor |
author_role |
author |
author2 |
Pousinho, Hugo Miguel Inácio Melício, Rui Mendes, Victor |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Laia, Rui Pousinho, Hugo Miguel Inácio Melício, Rui Mendes, Victor |
dc.subject.por.fl_str_mv |
Bidding strategy Bilateral contracts Emission allowances Stochastic programming Thermal self-scheduling |
topic |
Bidding strategy Bilateral contracts Emission allowances Stochastic programming Thermal self-scheduling |
description |
This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. 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. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 2015-01-01T00:00:00Z 2016-02-24T15:41:06Z |
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/10400.21/5731 |
url |
http://hdl.handle.net/10400.21/5731 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
LAIA, Rui; [et al.] - Self-scheduling and bidding strategies of thermal units with stochastic emission constraints. Energy Conversion and Management. ISSN. 0196-8904. Vol. 89 (2015), pp. 975-984 0196-8904 10.1016/j.enconman.2014.10.063 |
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 |
Pergamon-Elsevier Science LTD |
publisher.none.fl_str_mv |
Pergamon-Elsevier Science LTD |
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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1799133407916064768 |