Novel Multi-Stage Stochastic DG Investment Planning with Recourse
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/4806 http://dx.doi.org/10.1109/tste.2016.2590460 |
Resumo: | This paper presents a novel multi-stage stochastic distributed generation investment planning model for making investment decisions under uncertainty. The problem, formulated from a coordinated system planning viewpoint, simultaneously minimizes the net present value of costs rated to losses, emission, operation, and maintenance, as well as the cost of unserved energy. The formulation is anchored on a two-period planning horizon, each having multiple stages. The first period is a short-term horizon in which robust decisions are pursued in the face of uncertainty; whereas, the second one spans over a medium to long-term horizon involving exploratory and/or flexible investment decisions. The operational variability and uncertainty introduced by intermittent generation sources, electricity demand, emission prices, demand growth, and others are accounted for via probabilistic and stochastic methods, respectively. Metrics such as cost of ignoring uncertainty and value of perfect information are used to clearly demonstrate the benefits of the proposed stochastic model. A real-life distribution network system is used as a case study and the results show the effectiveness of the proposed model. |
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Novel Multi-Stage Stochastic DG Investment Planning with RecourseThis paper presents a novel multi-stage stochastic distributed generation investment planning model for making investment decisions under uncertainty. The problem, formulated from a coordinated system planning viewpoint, simultaneously minimizes the net present value of costs rated to losses, emission, operation, and maintenance, as well as the cost of unserved energy. The formulation is anchored on a two-period planning horizon, each having multiple stages. The first period is a short-term horizon in which robust decisions are pursued in the face of uncertainty; whereas, the second one spans over a medium to long-term horizon involving exploratory and/or flexible investment decisions. The operational variability and uncertainty introduced by intermittent generation sources, electricity demand, emission prices, demand growth, and others are accounted for via probabilistic and stochastic methods, respectively. Metrics such as cost of ignoring uncertainty and value of perfect information are used to clearly demonstrate the benefits of the proposed stochastic model. A real-life distribution network system is used as a case study and the results show the effectiveness of the proposed model.2017-12-22T17:58:22Z2017-01-01T00:00:00Z2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4806http://dx.doi.org/10.1109/tste.2016.2590460engSantos,SFFitiwi,DZBizuayehu,AWShafie khah,MAsensio,MContreras,JPereira Cabrita,CMPJoão Catalãoinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:19:49Zoai:repositorio.inesctec.pt:123456789/4806Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:15.389597Repositório 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 |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
title |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
spellingShingle |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse Santos,SF |
title_short |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
title_full |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
title_fullStr |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
title_full_unstemmed |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
title_sort |
Novel Multi-Stage Stochastic DG Investment Planning with Recourse |
author |
Santos,SF |
author_facet |
Santos,SF Fitiwi,DZ Bizuayehu,AW Shafie khah,M Asensio,M Contreras,J Pereira Cabrita,CMP João Catalão |
author_role |
author |
author2 |
Fitiwi,DZ Bizuayehu,AW Shafie khah,M Asensio,M Contreras,J Pereira Cabrita,CMP João Catalão |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Santos,SF Fitiwi,DZ Bizuayehu,AW Shafie khah,M Asensio,M Contreras,J Pereira Cabrita,CMP João Catalão |
description |
This paper presents a novel multi-stage stochastic distributed generation investment planning model for making investment decisions under uncertainty. The problem, formulated from a coordinated system planning viewpoint, simultaneously minimizes the net present value of costs rated to losses, emission, operation, and maintenance, as well as the cost of unserved energy. The formulation is anchored on a two-period planning horizon, each having multiple stages. The first period is a short-term horizon in which robust decisions are pursued in the face of uncertainty; whereas, the second one spans over a medium to long-term horizon involving exploratory and/or flexible investment decisions. The operational variability and uncertainty introduced by intermittent generation sources, electricity demand, emission prices, demand growth, and others are accounted for via probabilistic and stochastic methods, respectively. Metrics such as cost of ignoring uncertainty and value of perfect information are used to clearly demonstrate the benefits of the proposed stochastic model. A real-life distribution network system is used as a case study and the results show the effectiveness of the proposed model. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12-22T17:58:22Z 2017-01-01T00:00:00Z 2017 |
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://repositorio.inesctec.pt/handle/123456789/4806 http://dx.doi.org/10.1109/tste.2016.2590460 |
url |
http://repositorio.inesctec.pt/handle/123456789/4806 http://dx.doi.org/10.1109/tste.2016.2590460 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 |
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1799131599296528384 |