Hybrid dynamic harmonic regression with calendar variation for Turkey short-term electricity load forecasting

Regita Putri Permata, Dedy Dwi Prastyo*, Wibawati

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

10 Citations (Scopus)

Abstract

Short-term electricity load forecasting plays a vital role in determining the energy supplied. It has daily, weekly, and yearly harmonics patterns. In Muslim countries, it is influenced by religious celebrations held on the Islamic Hijri calendar. This study aims to compare Dynamic Harmonic Regression forecasting and its hybrid version involving calendar variation effect. This study is designed in two scenarios. Scenario 1 shows that out-of-sample forecasting can capture both seasonal and calendar variation patterns, while Scenario 2 shows the performance while only seasonal patterns exist. The results show that the hybrid model outperforms the individual models in two scenarios.

Original languageEnglish
Pages (from-to)25-33
Number of pages9
JournalProcedia Computer Science
Volume197
DOIs
Publication statusPublished - 2021
Event6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy
Duration: 7 Aug 20218 Aug 2021

Keywords

  • Calendar variation
  • Dynamic harmonic regression
  • Hybrid
  • Short-term electricity load

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