Lightning and Power Transmission Lines

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Lightning and Power Transmission Lines

• EE ---
• Term Paper
• By ---

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Outline of Presentation

• The Thunderstorm
• The Lightning Discharge (Stages)
• Lightning Currents and Related Parameters
• Protection of Power-Transmission
• Effect of Lightning on Power Transmission systems

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The Thunderstorm

• Global Distribution of Thunderstorms
• The Thundercloud
• Point-Discharge Currents
• The Lightning Discharge

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Global Distribution of Thunderstorms
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The Thundercloud

• Two main classes heat storms and frontal storms
• Heat storm in tropics and mountain areas
• Frontal storms in temperate regions
• Characterized by the electrical charge of water
  droplets.

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Point-Discharge Currents
Electrostatic field distribution about vertical
lightning conductor (could induce lightning
discharge)
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The Thundercloud continued
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The Lightning Discharge (Stages)

• Temporal Development of Flash to Ground
• Mature Stage
• The Leader Stroke
• The Dart Leader

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The Lightning Discharge (Stages) continued
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Lightning Currents and Related Parameters

• Lightning Currents
• Average lightning current amplitude is 25 kA
  (lowest 2kA, highest recorded 270 kA)
• Frequency of Lightning Discharges (flash density)
• Varies from place to place
• Measured in thunderstorm days and lightning flash
  density
• Lightning flash density for Greece 3.7 (most
  recent data)

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Protection of Power-Transmission Systems

• Reasons for Protection
• Avoid power disruptions
• Lightning protection methods
• The Air Terminal (overhead conductors)
• Tower Impedance (ability of tower to resist
  lightning)
• The Buried Earth System (underground grid of
  conductors)
• Protective Leakage Paths-Pipe-Pipe Gaps (utilizes
  a gap between conductors)
• Underground Cables (Utilizes insulation of the
  earth)
• Lightning Arresters (acts as over-voltage release
  valves)

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Effect of Lightning on Power Transmission systems

• Lightning Location
• Prediction of Lightning Activities

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Lightning Location

• Use of magnetic link locators, lightning counters
  location within country-wide networks
• Recorded by Meteorological Services and Power
  distribution companies over time
• Empirical formula for calculation of lightning
  flash density correlate well with actual flash
  density obtain from magnetic counters (most
  recent data obtained from Greece and Japan)

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Prediction of Lightning Activities

• Prediction based on a variety of methods
• Modeling of lightning parameters
• Prediction based on neural networks
• Prediction based on fuzzy neural networks
• All based on data obtained from lightning
  location from meteorological and power services.

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Prediction based on Fuzzy Neural Networks

• New technique used in Japan
• Gave better prediction of lighting strike
  compared to neural networks
• Limitations only predicts lightning strike few
  hours before the strike.

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Conclusions

• Thunderstorms occur at highest at the equatorial
  belt and decreases towards the poles. Local
  thunderstorm activity varies from year to year.
• Lightning data is available from the
  meteorological services of countries in the form
  of flash maps showing isokeraunic lines, i.e.
  lines joining areas have the same number of
  thunderstorm days.
• The mechanism of light formation and discharge
  involves electrical charging of water droplets
  within a cloud leading to a dipole. The
  electrical field thus produces causes a cloud to
  cloud lightning discharge or a cloud to earth
  discharge.
• The average lightning current of about 25 kA.

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Conclusions continued

• The earth flash density varies in different parts
  of the world with the earth flash density
  estimated at 1 to 2 flashes per 10 thunderstorm
  days.
• A variety of protection mechanism exist for the
  lightning protection of transmission lines
  including ground conductors(air terminals),
  counterpoise , pipe-pipe gap, down-lead,
  grounding systems, underground cables and
  lightning arresters.

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Conclusions continued

• Traditional methods of lightning monitoring
  include the use of magnetic link direction
  finders and lightning counters.
• Correlation between lightning data obtained from
  meteorological lightning networks and those
  obtained using standard formula show good
  agreement.
• More modern methods have focused on lighting
  prediction using neural network and fuzzy neural
  network techniques, but these only provide
  prediction a couple of hours before the lightning
  strike.

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End of Presentation

• Thank You