A Novel AI-driven Hybrid Method for Flicker Estimation in Power Systems

Javad Enayati, Pedram Asef, Aliakbar Yousefi, M. B. Asadpourahmadchali, Alexandre Benoit

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

Abstract

This paper introduces a novel hybrid method using a combination of an H-infinity filter and artificial neural network (ANN) to estimate flicker components within power distribution system voltages. The H-infinity filter first extracts the estimated envelope of the applied voltage waveforms, incorporating a new voltage fluctuation model that realistically accounts for both harmonic and flicker components. Furthermore, an ADALINE (adaptive linear neuron) extracts the specific flicker components within the envelope. The hybrid process decouples prediction states, enhancing convergence behavior. Additionally, it showcases robust flicker component tracking even in the presence of power harmonics and noise, offering advantages over traditional signal processing methods. The algorithm's performance in flicker estimation is validated through statistical analysis using Monte Carlo (MC) simulations and real world data.

Original languageEnglish
Title of host publication2024 International Conference on Smart Energy Systems and Technologies
Subtitle of host publicationDriving the Advances for Future Electrification, SEST 2024 - Proceedings
Place of PublicationU. S. A.
PublisherIEEE
ISBN (Electronic)9798350386493
DOIs
Publication statusPublished - 12 Sept 2024
Externally publishedYes
Event2024 International Conference on Smart Energy Systems and Technologies, SEST 2024 - Torino, Italy
Duration: 10 Sept 202412 Sept 2024

Publication series

Name2024 International Conference on Smart Energy Systems and Technologies: Driving the Advances for Future Electrification, SEST 2024 - Proceedings

Conference

Conference2024 International Conference on Smart Energy Systems and Technologies, SEST 2024
Country/TerritoryItaly
CityTorino
Period10/09/2412/09/24

Keywords

  • adaptive linear neuron
  • estimation process
  • Flicker
  • H-Infinity
  • machine learning
  • voltage fluctuations

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering
  • Control and Optimization

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