Network topological notions for power systems security assessment

The identification of topological vulnerabilities is a prerequisite for the study of security analysis. This paper presents a graph-theoretic framework to detect the minimum set of transmission lines interconnecting subnetworks inside of a power network. Moreover, the framework is used to develop a...

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Autores:
Moreno-Chuquen, Ricardo
Obando Ceron, Johan Samir
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/11393
Acceso en línea:
http://hdl.handle.net/10614/11393
https://doi.org/10.15866/iree.v13i3.14210
Palabra clave:
Análisis de redes eléctricas
Electric network analysis
Sistemas de interconexión eléctrica
Interconnected electric utility systems
Graph theory
Network assessment
Contingency analysis
Power system security
Rights
restrictedAccess
License
Derechos Reservados - Universidad Autónoma de Occidente
Description
Summary:The identification of topological vulnerabilities is a prerequisite for the study of security analysis. This paper presents a graph-theoretic framework to detect the minimum set of transmission lines interconnecting subnetworks inside of a power network. Moreover, the framework is used to develop a method to classify the criticality of substations. The approach can be used with power transfer distribution factors information to gain an insight about the power system security. Sometimes the power network exhibits high vulnerability related to critical transmission lines interconnecting critical substations from a physical point of view. The quantification of structural properties can provide meaningful information needed to assess and enhance the reliability and security of power system networks. The capabilities for the topological approach are illustrated on two large-scale networks. The proposed approach provides an effective tool for both real-time and offline environments for security analysis and control