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

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2023

Autores

de Sousa, RP (Autor) Outra; C. L. Moreira (Autor) FEUP; Leonel Carvalho (Autor) FEUP; Manuel Matos (Autor) FEUP

Ata de Conferência Internacional

Título: 2023 IEEE BELGRADE POWERTECH

IEEE Belgrade PowerTech Conference

Belgrade, SERBIA, JUN 25-29, 2023

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00Y-T83

DOI: 10.1109/powertech55446.2023.10202690

Abstract (EN): 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: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6