A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

Kai Yuan, Jian Liu, Kaipei Liu and Tianyuan Tan

PLOS ONE, 2015, vol. 10, issue 3, 1-17

Abstract: Background: Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods: This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion: Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0112940

DOI: 10.1371/journal.pone.0112940

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