The electricity consumption forecast with micro and macro analysis
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/8685 |
Resumo: | Electricity forecast is a key subject to support decision making. Understand all key factors, the major agent’s interaction and the results of the available energy mix are important on the electricity sector. The present paper presents a method of approach to define a complete top-down and bottom-up hybrid model. This method is a baseline to build a tool to test and analyse the electricity market in a Country to provide results that would allow to make quantitative balance and to eliminate unfeasible options. The present paper focuses on the behaviour and on the response areas of the electricity markets. |
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The electricity consumption forecast with micro and macro analysisElectricity forecastTop-downBottom-upDecision support systemEnergy mixElectricity forecast is a key subject to support decision making. Understand all key factors, the major agent’s interaction and the results of the available energy mix are important on the electricity sector. The present paper presents a method of approach to define a complete top-down and bottom-up hybrid model. This method is a baseline to build a tool to test and analyse the electricity market in a Country to provide results that would allow to make quantitative balance and to eliminate unfeasible options. The present paper focuses on the behaviour and on the response areas of the electricity markets.Innovative JournalRCIPLDomingues, Nuno2020-07-01T00:30:11Z2018-062018-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/8685engDOMINGUES, Nuno – The electricity consumption forecast with micro and macro analysis. Journal of Business Management and Economics. ISSN 2347-5471. Vol. 6, N.º 6 (2018), pp. 18-222347-5471https://doi.org/10.15520/jbme.v6i06.2190info: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:RCAAP2023-08-03T09:56:28Zoai:repositorio.ipl.pt:10400.21/8685Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:17:23.979916Repositório 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 |
The electricity consumption forecast with micro and macro analysis |
title |
The electricity consumption forecast with micro and macro analysis |
spellingShingle |
The electricity consumption forecast with micro and macro analysis Domingues, Nuno Electricity forecast Top-down Bottom-up Decision support system Energy mix |
title_short |
The electricity consumption forecast with micro and macro analysis |
title_full |
The electricity consumption forecast with micro and macro analysis |
title_fullStr |
The electricity consumption forecast with micro and macro analysis |
title_full_unstemmed |
The electricity consumption forecast with micro and macro analysis |
title_sort |
The electricity consumption forecast with micro and macro analysis |
author |
Domingues, Nuno |
author_facet |
Domingues, Nuno |
author_role |
author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Domingues, Nuno |
dc.subject.por.fl_str_mv |
Electricity forecast Top-down Bottom-up Decision support system Energy mix |
topic |
Electricity forecast Top-down Bottom-up Decision support system Energy mix |
description |
Electricity forecast is a key subject to support decision making. Understand all key factors, the major agent’s interaction and the results of the available energy mix are important on the electricity sector. The present paper presents a method of approach to define a complete top-down and bottom-up hybrid model. This method is a baseline to build a tool to test and analyse the electricity market in a Country to provide results that would allow to make quantitative balance and to eliminate unfeasible options. The present paper focuses on the behaviour and on the response areas of the electricity markets. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-06 2018-06-01T00:00:00Z 2020-07-01T00:30:11Z |
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/10400.21/8685 |
url |
http://hdl.handle.net/10400.21/8685 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
DOMINGUES, Nuno – The electricity consumption forecast with micro and macro analysis. Journal of Business Management and Economics. ISSN 2347-5471. Vol. 6, N.º 6 (2018), pp. 18-22 2347-5471 https://doi.org/10.15520/jbme.v6i06.2190 |
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 |
Innovative Journal |
publisher.none.fl_str_mv |
Innovative Journal |
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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1799133436416360448 |