A new clustering algorithm for load profiling based on billing data
Autor(a) principal: | |
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Data de Publicação: | 2012 |
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/123456789/2222 |
Resumo: | In open energy markets, the settlement process between distribution operators and traders is made on an hourly (or 15 min) basis, while LV consumers' billing data continues to result from monthly energy bills. In order to reconcile these two different realities, load profiling is used as a means to redistribute the consumed energy of each trader's portfolio by hourly intervals, according to recorded consumption patterns. This paper presents a new clustering approach to derive typical load diagrams that can be used in the process. The algorithm uses real load diagrams obtained in measurement campaigns to define classes (in the billing information space) that maximize the compactness of the diagrams in each class. The methodology was developed in a project with EDP Distribution (the Portuguese distribution system operator) and the result was approved by the Regulatory Authority that adopted the proposed profiles for market use. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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A new clustering algorithm for load profiling based on billing dataIn open energy markets, the settlement process between distribution operators and traders is made on an hourly (or 15 min) basis, while LV consumers' billing data continues to result from monthly energy bills. In order to reconcile these two different realities, load profiling is used as a means to redistribute the consumed energy of each trader's portfolio by hourly intervals, according to recorded consumption patterns. This paper presents a new clustering approach to derive typical load diagrams that can be used in the process. The algorithm uses real load diagrams obtained in measurement campaigns to define classes (in the billing information space) that maximize the compactness of the diagrams in each class. The methodology was developed in a project with EDP Distribution (the Portuguese distribution system operator) and the result was approved by the Regulatory Authority that adopted the proposed profiles for market use.2017-11-16T13:22:23Z2012-01-01T00:00:00Z2012info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2222engJosé Nuno FidalgoManuel MatosLuís Ribeiroinfo: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:RCAAP2023-05-15T10:20:54Zoai:repositorio.inesctec.pt:123456789/2222Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:46.379547Repositório 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 |
A new clustering algorithm for load profiling based on billing data |
title |
A new clustering algorithm for load profiling based on billing data |
spellingShingle |
A new clustering algorithm for load profiling based on billing data José Nuno Fidalgo |
title_short |
A new clustering algorithm for load profiling based on billing data |
title_full |
A new clustering algorithm for load profiling based on billing data |
title_fullStr |
A new clustering algorithm for load profiling based on billing data |
title_full_unstemmed |
A new clustering algorithm for load profiling based on billing data |
title_sort |
A new clustering algorithm for load profiling based on billing data |
author |
José Nuno Fidalgo |
author_facet |
José Nuno Fidalgo Manuel Matos Luís Ribeiro |
author_role |
author |
author2 |
Manuel Matos Luís Ribeiro |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
José Nuno Fidalgo Manuel Matos Luís Ribeiro |
description |
In open energy markets, the settlement process between distribution operators and traders is made on an hourly (or 15 min) basis, while LV consumers' billing data continues to result from monthly energy bills. In order to reconcile these two different realities, load profiling is used as a means to redistribute the consumed energy of each trader's portfolio by hourly intervals, according to recorded consumption patterns. This paper presents a new clustering approach to derive typical load diagrams that can be used in the process. The algorithm uses real load diagrams obtained in measurement campaigns to define classes (in the billing information space) that maximize the compactness of the diagrams in each class. The methodology was developed in a project with EDP Distribution (the Portuguese distribution system operator) and the result was approved by the Regulatory Authority that adopted the proposed profiles for market use. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-01-01T00:00:00Z 2012 2017-11-16T13:22:23Z |
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/123456789/2222 |
url |
http://repositorio.inesctec.pt/handle/123456789/2222 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
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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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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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1799131611229323264 |