Decomposition forecasting methods: A review of applications in power systems

Nhlanhla Mbuli, Malusi Mathonsi, Modisane Seitshiro, Jan Harm C. Pretorius

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

The aim of this paper is to present a comprehensive literature review on the application of decomposition methods of time series forecasting in power systems. A comprehensive search is conducted, relevant publications are identified and summarised in terms of the aim of the forecast, decomposition forecasting method used, and a comparison is made with other forecasting techniques. Moreover, publications are analysed by number of publications per year, number of papers by the decomposition method used, and number of publications by area of application of the method in power systems. It is shown that the number of publications per annum grew substantially after 2014 due to studies on the application of decomposition methods in forecasting distributed generation output. Of the methods of forecasting, most publications have used multiplicative decomposition, a lower number has used additive decomposition, with the balance of the papers only using decomposition of the time series as an initial phase towards forecasting using other techniques. The analysis of the papers also shows that decomposition methods have been used in power systems mainly for load, price and distributed generation forecasting. The review contributes to literature by providing an extensive overview of the papers and a repository of references to researchers interested in decomposition forecasting techniques.

Original languageEnglish
Pages (from-to)298-306
Number of pages9
JournalEnergy Reports
Volume6
DOIs
Publication statusPublished - Dec 2020

Keywords

  • Additive decomposition method
  • Decomposition
  • Multiplicative decomposition method

ASJC Scopus subject areas

  • General Energy

Fingerprint

Dive into the research topics of 'Decomposition forecasting methods: A review of applications in power systems'. Together they form a unique fingerprint.

Cite this