• DocumentCode
    1049521
  • Title

    Prediction of Metallic Conductor Voltage Owing to Electromagnetic Coupling Using Neuro Fuzzy Modeling

  • Author

    Al-Badi, A.H. ; Ghania, Samy M. ; El-Saadany, Ehab F.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Sultan Qaboos Univ., Muscat
  • Volume
    24
  • Issue
    1
  • fYear
    2009
  • Firstpage
    319
  • Lastpage
    327
  • Abstract
    Electromagnetic interference effects of transmission lines on nearby metallic structures such as pipelines, communication lines, or railroads are a real problem, which can place both operator safety and structure integrity at risk. The level of these voltages can be reduced to a safe value in accordance with the IEEE standard 80 by designing a proper mitigation system. This paper presents a Fuzzy algorithm that can predict the level of the metallic conductor voltage. The model outlined in this paper is both fast and accurate and can accurately predict the voltage magnitude even with changing system parameters (soil resistivity, fault current, separation distance, mitigated or unmitigated system). Simulation results for three different scenarios, confirm the capability of the proposed Fuzzy system model in modeling and predicting the total voltage and are found to be in good agreement with data obtained from the CDEGS software.
  • Keywords
    electromagnetic interference; fuzzy neural networks; fuzzy set theory; power engineering computing; power transmission lines; electromagnetic coupling; electromagnetic interference; fuzzy algorithm; metallic conductor voltage; metallic structures; neuro fuzzy modeling; transmission lines; Conductors; Electromagnetic coupling; Electromagnetic interference; Electromagnetic modeling; Pipelines; Prediction algorithms; Predictive models; Railway safety; Transmission lines; Voltage; Adaptive neuro-fuzzy; electromagnetic; interference; pipelines; power transmission lines;
  • fLanguage
    English
  • Journal_Title
    Power Delivery, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8977
  • Type

    jour

  • DOI
    10.1109/TPWRD.2008.2002657
  • Filename
    4729796