The estimation of the lightning performance of a power distribution network is of great importance to design its protection system against lightning. An accurate evaluation of the number of lightning events that can create dangerous overvoltages requires a huge computational effort, as it implies the adoption of a Monte Carlo procedure. Such a procedure consists of generating many different random lightning events and calculating the corresponding overvoltages. The paper proposes a methodology to deal with the problem in two computationally efficient ways: (i) finding out the minimum number of Monte Carlo runs that lead to reliable results; and (ii) setting up a procedure that bypasses the lightning field-to-line coupling problem for each Monte Carlo run. The proposed approach is shown to provide results consistent with existing approaches while exhibiting superior Central Processing Unit (CPU) time performances..

A methodology to reduce the computational effort in the evaluation of the lightning performance of distribution networks

Bendato, Ilaria;Brignone, Massimo;Delfino, Federico;Procopio, Renato;
2016

Abstract

The estimation of the lightning performance of a power distribution network is of great importance to design its protection system against lightning. An accurate evaluation of the number of lightning events that can create dangerous overvoltages requires a huge computational effort, as it implies the adoption of a Monte Carlo procedure. Such a procedure consists of generating many different random lightning events and calculating the corresponding overvoltages. The paper proposes a methodology to deal with the problem in two computationally efficient ways: (i) finding out the minimum number of Monte Carlo runs that lead to reliable results; and (ii) setting up a procedure that bypasses the lightning field-to-line coupling problem for each Monte Carlo run. The proposed approach is shown to provide results consistent with existing approaches while exhibiting superior Central Processing Unit (CPU) time performances..
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/890093
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