access icon openaccess Monte-Carlo-based simulation and investigation of 230 kV transmission lines outage due to lightning

Here, using the probabilistic evaluation based on the Monte Carlo method, back-flashover rate and shielding failure flashover rate of 230 kV overhead transmission lines in the western regions of Iran are evaluated. To such an aim, first, the number of thunderstorm days per year is collected from the reported weather information in order to determine the ground flash density. Then, using MRU-200 equipment, the tower-footing resistance of several towers is measured. Matlab® software is used in order to produce lightning surges considering its probabilistic nature and randomly distribution on the ground to evaluate striking distance based on the geometric model. Then, calculated parameters are transferred to EMTP-RV software by establishing a link to perform the transient simulation and report the results for modelled 230 kV transmission line. Finally, considering IEEE-1243 standard, it is shown that due to high ground flash density, using 230 kV tower with one shield wire is not sufficient to protect the line against lightning phenomena.

Inspec keywords: shielding; probability; power overhead lines; Matlab; lightning protection; poles and towers; IEEE standards; flashover; EMTP; power transmission reliability; power system simulation; thunderstorms; Monte Carlo methods; power transmission protection

Other keywords: ground flash density; probabilistic evaluation; Iran; EMTP-RV software; back-flashover rate; voltage 230.0 kV; thunderstorm; transient simulation; IEEE-1243 standard; Monte Carlo method; Matlab software; probabilistic nature; lightning surges; geometric model; shielding failure flashover rate; western regions; overhead transmission lines; weather information; transmission lines outage; tower-footing resistance

Subjects: Power engineering computing; Monte Carlo methods; Overhead power lines; Reliability; Power line supports, insulators and connectors; Power system protection; Monte Carlo methods

http://iet.metastore.ingenta.com/content/journals/10.1049/hve.2019.0147
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content/journals/10.1049/hve.2019.0147
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