Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs

Detalhes bibliográficos
Autor(a) principal: Faria, Pedro
Data de Publicação: 2016
Outros Autores: Spínola, João, Vale, Zita
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/9358
Resumo: The use of distributed generation and demand-response (DR) programs is needed for improving business models, namely concerning the remuneration of these resources in the context of smart grids. In this paper, a methodology is proposed in which a virtual power player aggregates several small-sized resources, including consumers participating in DR programs. The global operation costs resulting from the resource scheduling are minimized. After scheduling the resources in several operation scenarios, clustering tools are applied in order to obtain distinct resources’ groups. The remuneration structure that better fits the aggregator goals is then determined. Two clustering algorithms are compared: 1) hierarchical; nd 2) fuzzy c-means clustering. The remuneration of small resources and consumers that are aggregated is made considering the maximum tariff in each group. The implemented case study considers 2592 operation scenarios based on a real Portuguese distribution network with 548 distributed generators and 20 310 consumers.
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spelling Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response ProgramsClusteringDemand response (DR) programsDistributed generation (DG)Smart gridsThe use of distributed generation and demand-response (DR) programs is needed for improving business models, namely concerning the remuneration of these resources in the context of smart grids. In this paper, a methodology is proposed in which a virtual power player aggregates several small-sized resources, including consumers participating in DR programs. The global operation costs resulting from the resource scheduling are minimized. After scheduling the resources in several operation scenarios, clustering tools are applied in order to obtain distinct resources’ groups. The remuneration structure that better fits the aggregator goals is then determined. Two clustering algorithms are compared: 1) hierarchical; nd 2) fuzzy c-means clustering. The remuneration of small resources and consumers that are aggregated is made considering the maximum tariff in each group. The implemented case study considers 2592 operation scenarios based on a real Portuguese distribution network with 548 distributed generators and 20 310 consumers.IEEERepositório Científico do Instituto Politécnico do PortoFaria, PedroSpínola, JoãoVale, Zita2017-01-24T14:25:16Z2016-062016-06-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/9358eng10.1109/TII.2016.2541542metadata 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:RCAAP2023-03-13T12:50:44Zoai:recipp.ipp.pt:10400.22/9358Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:29:58.547531Repositório 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 Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
title Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
spellingShingle Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
Faria, Pedro
Clustering
Demand response (DR) programs
Distributed generation (DG)
Smart grids
title_short Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
title_full Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
title_fullStr Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
title_full_unstemmed Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
title_sort Aggregation and Remuneration of Electricity Consumers and Producers for the Definition of Demand-Response Programs
author Faria, Pedro
author_facet Faria, Pedro
Spínola, João
Vale, Zita
author_role author
author2 Spínola, João
Vale, Zita
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Faria, Pedro
Spínola, João
Vale, Zita
dc.subject.por.fl_str_mv Clustering
Demand response (DR) programs
Distributed generation (DG)
Smart grids
topic Clustering
Demand response (DR) programs
Distributed generation (DG)
Smart grids
description The use of distributed generation and demand-response (DR) programs is needed for improving business models, namely concerning the remuneration of these resources in the context of smart grids. In this paper, a methodology is proposed in which a virtual power player aggregates several small-sized resources, including consumers participating in DR programs. The global operation costs resulting from the resource scheduling are minimized. After scheduling the resources in several operation scenarios, clustering tools are applied in order to obtain distinct resources’ groups. The remuneration structure that better fits the aggregator goals is then determined. Two clustering algorithms are compared: 1) hierarchical; nd 2) fuzzy c-means clustering. The remuneration of small resources and consumers that are aggregated is made considering the maximum tariff in each group. The implemented case study considers 2592 operation scenarios based on a real Portuguese distribution network with 548 distributed generators and 20 310 consumers.
publishDate 2016
dc.date.none.fl_str_mv 2016-06
2016-06-01T00:00:00Z
2017-01-24T14:25:16Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/9358
url http://hdl.handle.net/10400.22/9358
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1109/TII.2016.2541542
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dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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