Forecasting the Electric Network Frequency Signals on Power Grid

Woorim Bang, Ji Won Yoon

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

Abstract

The power grid, which is one of the important infrastructures, has a very challenging issue to stably manage electric power. The Electrical Network Frequency (ENF) which is the supply frequency on the power grid, however, has small variations near a constant frequency over time. In this paper, we studied the feasibility of predicting ENF values to operate the power grid reliably. To forecast ENF values, we analyzed the ENF signals by using auto-correlation and correlation coefficient. Based on the analysis results, we employed two approaches to forecast ENF values using a kernel regression model with correlation coefficient and autoregressive moving average model. To evaluate the accuracy of the proposed prediction algorithm, we experimented ENF data for 29 days in three power grids of the United States; the Eastern, the Western, and the Texas power grid. The results of our suggested methods presented the remarkable performance in forecasting ENF signals.

Original languageEnglish
Title of host publicationICTC 2019 - 10th International Conference on ICT Convergence
Subtitle of host publicationICT Convergence Leading the Autonomous Future
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1218-1223
Number of pages6
ISBN (Electronic)9781728108926
DOIs
Publication statusPublished - 2019 Oct
Event10th International Conference on Information and Communication Technology Convergence, ICTC 2019 - Jeju Island, Korea, Republic of
Duration: 2019 Oct 162019 Oct 18

Publication series

NameICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future

Conference

Conference10th International Conference on Information and Communication Technology Convergence, ICTC 2019
CountryKorea, Republic of
CityJeju Island
Period19/10/1619/10/18

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Keywords

  • Data Mining
  • Electric Network Frequency
  • Prediction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems and Management
  • Management of Technology and Innovation
  • Safety, Risk, Reliability and Quality
  • Media Technology
  • Control and Optimization

Cite this

Bang, W., & Yoon, J. W. (2019). Forecasting the Electric Network Frequency Signals on Power Grid. In ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future (pp. 1218-1223). [8939676] (ICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICTC46691.2019.8939676