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Coherency Groups Analysis based on Self Organizing Maps

Authors

BALTAS, NICHOLAS-GREGORY, Chamorro H.R. , Gonzalez-Longatt F. , RODRÍGUEZ CORTÉS, PEDRO

External publication

No

Means

IEEE Power Energy Soc. Gen. Meet.

Scope

Conference Paper

Nature

Científica

JCR Quartile

SJR Quartile

SJR Impact

0.395

Publication date

01/01/2019

Scopus Id

2-s2.0-85079066792

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.

Keywords

Coherency Groups Identification; Data Clustering; Self Organizing Maps; Sliding Window

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