The Spatial Statistics of Self-organized in Power System

Simple item page
dc.contributor.authorJiang, Nannan
dc.contributor.authorRen, Hui
dc.contributor.authorWatts Casimis, David Eduardo
dc.contributor.authorLiu, Ying
dc.contributor.authorLu, Haitao
dc.contributor.authorTian, Jiefu
dc.date.accessioned2022-05-18T14:38:43Z
dc.date.available2022-05-18T14:38:43Z
dc.date.issued2018
dc.description.abstractSelf-organized criticality (SOC) is one of explanation accepted so far on the mechanism of large blackouts. Based on the previous study on the temporal statistics of self-organized power system, the spatial statistics of the power system along its evolution is analyzed for better understanding of the mechanism of large blackouts. The conventional sensitivity method, Power Transfer Distribution Factor (PTDF), is used as the spatial weight matrix for the calculation of spatial auto correlation by Moran's I. An equivalent transmission capacity is defined as the observation. Besides Moran's I, mean, standard deviation and Entropy of equivalent transmission capacity are also provided for a better understanding of the effect of the evolution of transmission capacity on the system entering SOC, when large blackouts are of bigger possibility. IEEE -118 system is taken as a test system for the analysis. The analysis shows that spatial auto correlation by Moran's I is better for describing the heterogeneity of the power system and is a prospective candidate for the early warning of power system entering SOC.
dc.fuente.origenIEEE
dc.identifier.doi10.1109/POWERCON.2018.8602185
dc.identifier.isbn978-1538664612
dc.identifier.urihttps://doi.org/10.1109/POWERCON.2018.8602185
dc.identifier.urihttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8602185
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/64149
dc.information.autorucEscuela de ingeniería ; Watts Casimis, David Eduardo ; S/I ; 93141
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherIEEE
dc.relation.ispartofInternational Conference on Power System Technology (2018 : Guangzhou, China)
dc.rightsacceso restringido
dc.subjectLoad flow
dc.subjectEntropy
dc.subjectCorrelation
dc.subjectTransmission line matrix methods
dc.subjectPower system faults
dc.subjectPower system protection
dc.titleThe Spatial Statistics of Self-organized in Power Systemes_ES
dc.typecomunicación de congreso
sipa.codpersvinculados93141
Files
Collections
Artículos de conferencia