One of the most critical issues in the evaluation of power systems is the identification of critical buses. For this purpose, this paper proposes a new methodology that evaluates the substitution of the power flow tec...One of the most critical issues in the evaluation of power systems is the identification of critical buses. For this purpose, this paper proposes a new methodology that evaluates the substitution of the power flow technique by the geodesic vulnerability index to identify critical nodes in power systems.Both methods are applied comparatively to demonstrate the scope of the proposed approach. The applicability of the methodology is illustrated using the IEEE 118-bus test system as a case study. To identify the critical components, a node is initially disconnected, and the performance of the resulting topology is evaluated in the face of simulations for multiple cascading faults. Cascading events are simulated by randomly removing assets on a system that continually changes its structure with the elimination of each component. Thus, the classification of the critical nodes is determined by evaluating the resulting performance of 118 different topologies and calculating the damaged area for each of the disintegration curves of cascading failures. In summary, the feasibility and suitability of complex network theory are justified to identify critical nodes in power systems.展开更多
基金supported by TECNM-Mexico (No. 6520.18-P)the Ministry of Economy and Competitiveness,Spain (No. ENE2016-77172-R)。
文摘One of the most critical issues in the evaluation of power systems is the identification of critical buses. For this purpose, this paper proposes a new methodology that evaluates the substitution of the power flow technique by the geodesic vulnerability index to identify critical nodes in power systems.Both methods are applied comparatively to demonstrate the scope of the proposed approach. The applicability of the methodology is illustrated using the IEEE 118-bus test system as a case study. To identify the critical components, a node is initially disconnected, and the performance of the resulting topology is evaluated in the face of simulations for multiple cascading faults. Cascading events are simulated by randomly removing assets on a system that continually changes its structure with the elimination of each component. Thus, the classification of the critical nodes is determined by evaluating the resulting performance of 118 different topologies and calculating the damaged area for each of the disintegration curves of cascading failures. In summary, the feasibility and suitability of complex network theory are justified to identify critical nodes in power systems.
