Including Dynamic Security Constraints in Isolated Power Systems Unit Commitment/Economic Dispatch: A Machine Learning-based Approach

Rui Pinto De Sousa, Carlos Moreira, Leonel Carvalho, Manuel Matos

Resultado de pesquisarevisão de pares

1 Citação (Scopus)

Resumo

Isolated power systems with high shares of renewables can require additional inertia as a complementary resource to assure the system operation in a dynamic safe region. This paper presents a methodology for the day-ahead Unit Commitment/Economic Dispatch UC/ED for low-inertia power systems including dynamic security constraints for key frequency indicators computed by an Artificial Neural-Network (ANN)-supported Dynamic Security Assessment (DSA) tool. The ANN-supported DSA tool infers the system dynamic performance with respect to key frequency indicators following critical disturbances and computes the additional synchronous inertia that brings the system back to its dynamic security region, by dispatching Synchronous Condensers (SC) if required. The results demonstrate the effectiveness of the methodology proposed by enabling the system operation within safe frequency margins for a set of high relevance fault type contingencies while minimizing the additional costs associated with the SC operation.

Idioma originalInglês
Título da publicação do anfitrião2023 IEEE Belgrade PowerTech, PowerTech 2023
EditoraInstitute of Electrical and Electronics Engineers Inc.
ISBN (eletrónico)9781665487788
DOIs
Estado da publicaçãoPublicadas - 2023
Publicado externamenteSim
Evento2023 IEEE Belgrade PowerTech, PowerTech 2023 - Belgrade
Duração: 25 jun. 202329 jun. 2023

Série de publicação

Nome2023 IEEE Belgrade PowerTech, PowerTech 2023

Conferência

Conferência2023 IEEE Belgrade PowerTech, PowerTech 2023
País/TerritórioSerbia
CidadeBelgrade
Período25/06/2329/06/23

Nota bibliográfica

Publisher Copyright:
© 2023 IEEE.

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