Abstract
The prevention of cascading failures and large-scale power outages of power grids by identifying weak links has become one of the key topics in power systems research. In this paper, a vulnerability radius index is proposed to identify the initial fault, and a fault chain model of cascading failure is developed with probabilistic attributes to identify the set of fault chains that have a significant impact on the safe and stable operation of power grids. On this basis, a method for evaluating the vulnerability of transmission lines based on a multi-criteria decision analysis is proposed, which can quickly identify critical transmission lines in the process of cascading failure. Finally, the proposed model and method for identifying vulnerable lines during the cascading failure process is demonstrated on the IEEE-118 bus system.
Highlights
Assessment of Transmission LinesLarge-scale power outages around the world are often caused by cascading faults [1,2], and the propagation of cascading faults is closely related to weak links in the power grid [3,4]
A few power grid vulnerability assessment methods have been previously proposed for studying cascading failure, namely, structural analysis methods based on complex network theory [5,6,7], fault simulation methods based on self-organizing criticality theory [8,9,10], fault evolution methods based on cellular automata theory [11,12], and fault chain extraction methods based on Heinrich causal chain theory [13,14,15]
Purpose of the vulnerability assessment is to find the specific link of the fault chain which is important to the stability of the power grid, combating the inaccurate prediction of a single fault chain
Summary
Large-scale power outages around the world are often caused by cascading faults [1,2], and the propagation of cascading faults is closely related to weak links in the power grid [3,4]. In view of the above shortcomings, a probabilistic vulnerability assessment method based on the fault chain model is proposed in this paper to identify the weak lines. The major contributions of this article are as follows: (1) a cascading fault chain model with probabilistic attributes considering a variety of factors affecting cascading failure in the power system is proposed. This model can reasonably select initial faults and the subsequent lines, save the calculation of searching fault chain set, and predict the chain fault development mode with a more serious impact on the power grid. Simulation results from IEEE-118 bus system demonstrate the feasibility and effectiveness of the method proposed in this paper
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