Equivalent dynamic model of active distribution networks for large voltage disturbances

Nuno Fulgêncio, Carlos Moreira, Leonel Carvalho, João Peças Lopes

Resultado de pesquisarevisão de pares

3 Citações (Scopus)

Resumo

This paper proposes a 'grey-box' dynamic equivalent model for medium voltage active distribution networks, taking into account a heterogeneous fleet of generation technologies alongside the latest European grid codes requirements. It aims to properly represent the transient behavior of the system upon large voltage disturbances in the transmission side. The proposed equivalent model is composed by four main components: two equivalent generation units, one for converter-connected units' representation, and another accounting for the synchronous generation units' portfolio; an equivalent composite load model; and a battery energy storage system, also converter-connected to the grid. The model's parameters are estimated by an evolutionary particle swarm optimization algorithm, by comparing a fully-detailed model of a medium voltage distribution network with the equivalent model's frequency domain's responses of active and reactive power flows, at the boundary of distribution-transmission interface substation.

Idioma originalInglês
Título da publicação do anfitrião2019 IEEE Milan PowerTech, PowerTech 2019
EditoraInstitute of Electrical and Electronics Engineers Inc.
ISBN (eletrónico)9781538647226
DOIs
Estado da publicaçãoPublicadas - jun. 2019
Publicado externamenteSim
Evento2019 IEEE Milan PowerTech, PowerTech 2019 - Milan
Duração: 23 jun. 201927 jun. 2019

Série de publicação

Nome2019 IEEE Milan PowerTech, PowerTech 2019

Conferência

Conferência2019 IEEE Milan PowerTech, PowerTech 2019
País/TerritórioItaly
CidadeMilan
Período23/06/1927/06/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

Financiamento

Financiadoras/-esNúmero do financiador
EU-SysFlex
Horizon 2020 Framework Programme773505
Fundação para a Ciência e a Tecnologia
Instituto Nacional de Ciência e Tecnologia para Excitotoxicidade e NeuroproteçãoUID/EEA/50014/2019

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