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On the Statistical Characterization of Lightning-Induced Voltages

doi: 10.3390/app8040651
handle: 11588/724089
Protection against lightning-induced voltages is a particularly critical issue, especially for smart grids, due to the presence of electronic-based equipment, as well as control and monitoring devices. Analysis of the severity of the induced voltages is then imperative; on the other hand, the random nature of the lightning phenomenon cannot be disregarded. In this paper, the severity of lightning-induced voltage is analyzed by means of a probabilistic approach which, starting from closed-form solutions, uses a Monte Carlo procedure. Parametric distributions that best fit the distributions of the induced voltages are investigated as well. The results show that the lognormal and the generalized extreme value distributions are the best candidates.
Technology, lightning-induced voltage, QH301-705.5, T, Physics, QC1-999, Lightning-induced voltage; Monte Carlo procedure; Statistical analysis, Monte Carlo procedure, Engineering (General). Civil engineering (General), lightning-induced voltage; Monte Carlo procedure; statistical analysis, Lightning-induced voltage, Chemistry, statistical analysis, Statistical analysis, TA1-2040, Biology (General), QD1-999
Technology, lightning-induced voltage, QH301-705.5, T, Physics, QC1-999, Lightning-induced voltage; Monte Carlo procedure; Statistical analysis, Monte Carlo procedure, Engineering (General). Civil engineering (General), lightning-induced voltage; Monte Carlo procedure; statistical analysis, Lightning-induced voltage, Chemistry, statistical analysis, Statistical analysis, TA1-2040, Biology (General), QD1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
