The effect of system characteristics on very-short-term load forecasting

Y. Loewenstern, L. Katzir, D. Shmilovitz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Over the past three decades, the number of papers published on Load Forecasting (LF) has increased exponentially, largely due to the advance of Artificial-Intelligence/Machine Learning techniques. Most research has focused on short-term load forecasting (STLF), hours or days in advance. The rise of the Smart Grid and Microgrid concepts require load demand control at shorter lead times, at a resolution of minutes, leading to the need for Very Short Term Load Forecasting (VSTLF). There is not a significant body of research on this topic. Additionally, attention needs to be paid to small power systems, far smaller than those studied in most of the literature. Previous work has used statistical techniques to characterize power systems and studied univariate methods for accurate VSTLF. This study builds upon the previous research and investigates the relationship between system characteristics and the achievable VSTLF accuracy. The results presented here are based on study and simulated forecasting of three years' worth of real load data obtained from the New York Independent System Operator (NYISO).

Original languageEnglish
Title of host publication12th Conference-Seminar
Subtitle of host publicationInternational School on Nonsinusoidal Currents and Compensation, ISNCC 2015 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479984169
DOIs
StatePublished - 31 Jul 2015
Event12th Conference-Seminar: International School on Nonsinusoidal Currents and Compensation, ISNCC 2015 - Lagow, Poland
Duration: 15 Jun 201518 Jun 2015

Publication series

Name12th Conference-Seminar: International School on Nonsinusoidal Currents and Compensation, ISNCC 2015 - Conference Proceedings

Conference

Conference12th Conference-Seminar: International School on Nonsinusoidal Currents and Compensation, ISNCC 2015
Country/TerritoryPoland
CityLagow
Period15/06/1518/06/15

Keywords

  • Load forecasting
  • Smart Grid
  • load modeling
  • power systems

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