Título Coherency Groups Analysis based on Self Organizing Maps
Autores BALTAS, NICHOLAS-GREGORY, Chamorro H.R. , Gonzalez-Longatt F. , RODRÍGUEZ CORTÉS, PEDRO
Publicación externa No
Medio IEEE Power Energy Soc. Gen. Meet.
Alcance Conference Paper
Naturaleza Científica
Impacto SJR 0.39500
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079066792&doi=10.1109%2fPESGM40551.2019.8973411&partnerID=40&md5=506dee7227513bd7a14632032a87929f
Fecha de publicacion 01/01/2019
Scopus Id 2-s2.0-85079066792
DOI 10.1109/PESGM40551.2019.8973411
Abstract The secure operation of power systems should be maintained into secure states under different grid impact events. Such operational and non-operational grid states events occur infrequently, but when they do, they reveal the dynamics of the system and the need for security strategies to counteract events such as cascading failures. The coherency groups identification provides a protecting planning for proposing possible blackouts in the system. Additionally, coherency methods based on measurements are a requirement since the power systems continuous expansion. This paper applies the Self Organizing Maps (SOM) to assess the coherency groups identification based on the measurements obtained. Several observations have been evaluated assuming different time sliding window frames. The results are validated based on simulation of the Nordic test system. © 2019 IEEE.
Palabras clave Coherency Groups Identification; Data Clustering; Self Organizing Maps; Sliding Window
Miembros de la Universidad Loyola

Change your preferences Gestionar cookies