Lightning impulse parameter estimation using nonlinear least squares algorithm

Mohammad I.Al Saaideh, Eyad A. Feilat, Dia I. Abu-Al-Nadi, Amer S. Al-Hinai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new technique based on nonlinear least square (NLSQ) algorithm for estimating the mean curve and parameters of the standard lightning impulse (LI) waveform as required by IEC 60 and IEEE Std. 4. The proposed NLSQ technique is applied to analytical LI waveforms to estimate the mean curve of the impulse using a bi-exponential model after removing high frequency components from the simulated (measured) impulse. The effectiveness of the proposed technique is assessed by conducting several cases of LI impulse waveforms with front and tail oscillations and LI waveform with overshoot. The results of the NLSQ technique are compared with those obtained by the particle swarm optimization (PSO) algorithm. The simulation results show that the proposed NLSQ technique is robust and effective in estimating the peak value, front and tail times of the impulse waveform accurately.

Original languageEnglish
Title of host publication2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages97-102
Number of pages6
ISBN (Electronic)9781538679425
DOIs
Publication statusPublished - May 16 2019
Event2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2019 - Amman, Jordan
Duration: Apr 9 2019Apr 11 2019

Publication series

Name2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2019 - Proceedings

Conference

Conference2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2019
CountryJordan
CityAmman
Period4/9/194/11/19

Keywords

  • Impulse waveform
  • Least square
  • Mean curve
  • Optimization
  • Particle swarm
  • Signal processing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Computational Mathematics

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