Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids

Detalhes bibliográficos
Autor(a) principal: Mário Hélder Gomes
Data de Publicação: 2010
Outros Autores: João Tomé Saraiva
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/123456789/2057
Resumo: MicroGrids represent a new paradigm for the operation of distribution systems and there are several advantages as well as challenges regarding their development. One of the advantages is related with the participation of MicroGrid agents in electricity markets and in the provision of ancillary services. This paper describes two optimization models to allocate three ancillary services among MicroGrid agents – reactive power/voltage control, active loss balancing and demand interruption. These models assume that MicroGrid agents participate in the day ahead market sending their bids to the MicroGrid Central Controller, MGCC, that acts as an interface with the Market Operator. Once the Market Operator returns the economic dispatch of the Microgrid agents, the MGCC checks its technical feasibility (namely voltage magnitude and branch flow limits) and activates an adjustment market to change the initial schedule and to allocate these three ancillary services. One of the models has crisp nature considering that voltage and branch flow limits are rigid while the second one admits that voltage and branch flow limits are modeled in a soft way using Fuzzy Set concepts. Finally, the paper illustrates the application of these models with a case study using a 55 node MV/LV network.
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spelling Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGridsMicroGrids represent a new paradigm for the operation of distribution systems and there are several advantages as well as challenges regarding their development. One of the advantages is related with the participation of MicroGrid agents in electricity markets and in the provision of ancillary services. This paper describes two optimization models to allocate three ancillary services among MicroGrid agents – reactive power/voltage control, active loss balancing and demand interruption. These models assume that MicroGrid agents participate in the day ahead market sending their bids to the MicroGrid Central Controller, MGCC, that acts as an interface with the Market Operator. Once the Market Operator returns the economic dispatch of the Microgrid agents, the MGCC checks its technical feasibility (namely voltage magnitude and branch flow limits) and activates an adjustment market to change the initial schedule and to allocate these three ancillary services. One of the models has crisp nature considering that voltage and branch flow limits are rigid while the second one admits that voltage and branch flow limits are modeled in a soft way using Fuzzy Set concepts. Finally, the paper illustrates the application of these models with a case study using a 55 node MV/LV network.2017-11-16T13:09:42Z2010-01-01T00:00:00Z2010info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2057engMário Hélder GomesJoão Tomé Saraivainfo: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:RCAAP2023-05-15T10:19:47Zoai:repositorio.inesctec.pt:123456789/2057Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:13.171397Repositório 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 Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
title Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
spellingShingle Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
Mário Hélder Gomes
title_short Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
title_full Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
title_fullStr Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
title_full_unstemmed Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
title_sort Allocation of Reactive Power Support, Active Loss Balancing and Demand Interruption Ancillary Services in MicroGrids
author Mário Hélder Gomes
author_facet Mário Hélder Gomes
João Tomé Saraiva
author_role author
author2 João Tomé Saraiva
author2_role author
dc.contributor.author.fl_str_mv Mário Hélder Gomes
João Tomé Saraiva
description MicroGrids represent a new paradigm for the operation of distribution systems and there are several advantages as well as challenges regarding their development. One of the advantages is related with the participation of MicroGrid agents in electricity markets and in the provision of ancillary services. This paper describes two optimization models to allocate three ancillary services among MicroGrid agents – reactive power/voltage control, active loss balancing and demand interruption. These models assume that MicroGrid agents participate in the day ahead market sending their bids to the MicroGrid Central Controller, MGCC, that acts as an interface with the Market Operator. Once the Market Operator returns the economic dispatch of the Microgrid agents, the MGCC checks its technical feasibility (namely voltage magnitude and branch flow limits) and activates an adjustment market to change the initial schedule and to allocate these three ancillary services. One of the models has crisp nature considering that voltage and branch flow limits are rigid while the second one admits that voltage and branch flow limits are modeled in a soft way using Fuzzy Set concepts. Finally, the paper illustrates the application of these models with a case study using a 55 node MV/LV network.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01T00:00:00Z
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