Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting
Autor(a) principal: | |
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Data de Publicação: | 2022 |
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/10400.22/22082 |
Resumo: | The residential sector electricity demand has been increasing over the years, leading to an increasing effort of the power network components, namely during the peak demand periods. This demand increasing together with the increasing levels of renewable-based energy generation and the need to ensure the electricity service quality, namely in terms of the voltage profile, is challenging the distribution network operation. Demand response can play an important role in facing these challenges, bringing several benefits, both for the network operation and for the consumer (e.g., increase network components lifetime and consumers bill reduction). The present research work proposes a genetic algorithm-based model to use the consumers’ load flexibility with demand response event participation. The proposed method optimally shifts residential loads to enable the consumers’ participation in demand response while respecting consumers’ preferences and constraints. A realistic low voltage distribution network with 236 buses is used to illustrate the application of the proposed model. The results show considerable energy cost savings for consumers and an improvement in voltage profile. |
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Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load ShiftingDemand responseDistribution networkLoad flexibilityLoad shiftingVoltage profile improvementThe residential sector electricity demand has been increasing over the years, leading to an increasing effort of the power network components, namely during the peak demand periods. This demand increasing together with the increasing levels of renewable-based energy generation and the need to ensure the electricity service quality, namely in terms of the voltage profile, is challenging the distribution network operation. Demand response can play an important role in facing these challenges, bringing several benefits, both for the network operation and for the consumer (e.g., increase network components lifetime and consumers bill reduction). The present research work proposes a genetic algorithm-based model to use the consumers’ load flexibility with demand response event participation. The proposed method optimally shifts residential loads to enable the consumers’ participation in demand response while respecting consumers’ preferences and constraints. A realistic low voltage distribution network with 236 buses is used to illustrate the application of the proposed model. The results show considerable energy cost savings for consumers and an improvement in voltage profile.This article is a result of the Project Real-time support infrastructure and energy management for intelligent carbon-neutral smart cities (RETINA) (NORTE-01-0145-FEDER-000062), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF).IEEERepositório Científico do Instituto Politécnico do PortoCanizes, BrunoMota, BrunoRibeiro, PedroVale, Zita2023-02-01T16:29:47Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/22082eng10.1109/ACCESS.2022.3182580info: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:RCAAP2023-03-13T13:18:25Zoai:recipp.ipp.pt:10400.22/22082Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:42:08.355897Repositório 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 |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
title |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
spellingShingle |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting Canizes, Bruno Demand response Distribution network Load flexibility Load shifting Voltage profile improvement |
title_short |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
title_full |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
title_fullStr |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
title_full_unstemmed |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
title_sort |
Demand Response Driven by Distribution Network Voltage Limit Violation: A Genetic Algorithm Approach for Load Shifting |
author |
Canizes, Bruno |
author_facet |
Canizes, Bruno Mota, Bruno Ribeiro, Pedro Vale, Zita |
author_role |
author |
author2 |
Mota, Bruno Ribeiro, Pedro Vale, Zita |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Repositório Científico do Instituto Politécnico do Porto |
dc.contributor.author.fl_str_mv |
Canizes, Bruno Mota, Bruno Ribeiro, Pedro Vale, Zita |
dc.subject.por.fl_str_mv |
Demand response Distribution network Load flexibility Load shifting Voltage profile improvement |
topic |
Demand response Distribution network Load flexibility Load shifting Voltage profile improvement |
description |
The residential sector electricity demand has been increasing over the years, leading to an increasing effort of the power network components, namely during the peak demand periods. This demand increasing together with the increasing levels of renewable-based energy generation and the need to ensure the electricity service quality, namely in terms of the voltage profile, is challenging the distribution network operation. Demand response can play an important role in facing these challenges, bringing several benefits, both for the network operation and for the consumer (e.g., increase network components lifetime and consumers bill reduction). The present research work proposes a genetic algorithm-based model to use the consumers’ load flexibility with demand response event participation. The proposed method optimally shifts residential loads to enable the consumers’ participation in demand response while respecting consumers’ preferences and constraints. A realistic low voltage distribution network with 236 buses is used to illustrate the application of the proposed model. The results show considerable energy cost savings for consumers and an improvement in voltage profile. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z 2023-02-01T16:29:47Z |
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/10400.22/22082 |
url |
http://hdl.handle.net/10400.22/22082 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1109/ACCESS.2022.3182580 |
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 |
IEEE |
publisher.none.fl_str_mv |
IEEE |
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 |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131507942490112 |