Seismic vulnerability assessment of power transmission networks : a system thinking approach

• Main Author: Buriticá, Jessica Ana Maria
• Language: English
• Published: University of British Columbia 2013
• Online Access: http://hdl.handle.net/2429/44169

Electrical power transmission systems are essential to the economy and well-being of modern societies. The systems consist of power generating facilities, substations, and supervisory control and data acquisition, which are inter-connected through transmission lines arranged within a high dimensional network (i.e., large amount of edges and nodes). Efficiency and service quality are influenced by reliability of this network. Therefore, identification of critical components and vulnerability analysis become paramount, in particular, in regions where seismic activity is significant. In this research a novel methodology for seismic vulnerability assessment of power transmission systems is developed. The analysis is carried out from the perspective of both the system’s form (i.e., topological-electrical importance of elements) and system’s strength (i.e., probability of failure). The form combines the electrical properties of the network (e.g., electrical distance, power flow) with the systems approach via hierarchical network decomposition. On the other hand, the strength focuses on evaluating the probability of failure by means of the physical consequences of multiple earthquakes scenarios. Therefore, the vulnerability measure presents a trade–off between strength and form. Sensitivity analysis is carried out, where the influence of each perspective (i.e., form and strength) in the vulnerability measure is exhibited. Finally, different techniques for identification of critical components are compared with the proposed methodology. The results showed that the proposed approach exhibit features that provide a better understanding of seismic vulnerability of power systems than traditional approaches. === Applied Science, Faculty of === Engineering, School of (Okanagan) === Graduate