| Title | 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 |
| SJR Impact | 0.395 |
| Web | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079066792&doi=10.1109%2fPESGM40551.2019.8973411&partnerID=40&md5=506dee7227513bd7a14632032a87929f |
| Publication date | 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. |
| Keywords | Coherency Groups Identification; Data Clustering; Self Organizing Maps; Sliding Window |
| Universidad Loyola members |