Artificial Neural Network-based Methodology for Short-Term Electric Load Scenario Generation

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2015

Autores

Vagropoulos, SI (Autor) Outra; Kardakos, EG (Autor) Outra; Simoglou, CK (Autor) Outra; Bakirtzis, AG (Autor) Outra; Catalao, JPS (Autor) FEUP

Ata de Conferência Internacional

Título: 2015 18th International Conference on Intelligent System Application to Power Systems (ISAP)

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 5 Citações

Outras Informações

ID Authenticus: P-00K-C5A

DOI: 10.1109/isap.2015.7325540

Abstract (EN): In this paper a novel scenario generation methodology based on artificial neural networks (ANNs) is proposed. The methodology is able to create scenarios for various power system-related stochastic variables. Scenario reduction methodologies can then be applied to effectively reduce the number of scenarios. An application of the methodology for the creation of short-term electric load scenarios for one day up to seven days ahead is presented. Test results on the real-world insular power system of Crete present the effectiveness of the proposed methodology.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6