Combining multi-objective evolutionary algorithm and HΔ matrix for SCADA and PMU placement (2017)
- Authors:
- USP affiliated authors: LONDON JUNIOR, JOAO BOSCO AUGUSTO - EESC ; DELBEM, ALEXANDRE CLÁUDIO BOTAZZO - ICMC
- Unidades: EESC; ICMC
- Subjects: COMPUTAÇÃO EVOLUTIVA; SISTEMAS ELÉTRICOS; ALGORITMOS; ENGENHARIA ELÉTRICA
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway, NJ, USA
- Date published: 2017
- Source:
- Título do periódico: Proceedings
- Conference titles: IEEE Power & Energy Society General Meeting
-
ABNT
VIGLIASSI, M. P. et al. Combining multi-objective evolutionary algorithm and HΔ matrix for SCADA and PMU placement. 2017, Anais.. Piscataway, NJ, USA: IEEE, 2017. . Acesso em: 24 abr. 2024. -
APA
Vigliassi, M. P., London Junior, J. B. A., Delbem, A. C. B., & Piereti, S. A. R. (2017). Combining multi-objective evolutionary algorithm and HΔ matrix for SCADA and PMU placement. In Proceedings. Piscataway, NJ, USA: IEEE. -
NLM
Vigliassi MP, London Junior JBA, Delbem ACB, Piereti SAR. Combining multi-objective evolutionary algorithm and HΔ matrix for SCADA and PMU placement. Proceedings. 2017 ;[citado 2024 abr. 24 ] -
Vancouver
Vigliassi MP, London Junior JBA, Delbem ACB, Piereti SAR. Combining multi-objective evolutionary algorithm and HΔ matrix for SCADA and PMU placement. Proceedings. 2017 ;[citado 2024 abr. 24 ] - Algoritmo evolutivo com representação nó-profundidade aplicado para otimização do processo de restabelecimento de energia utilizando chaves automáticas
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