A review on the selected applications of forecasting models in renewable power systems

Adil Ahmed*, Muhammad Khalid

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

221 Scopus citations

Abstract

This paper presents a literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy (RE) in power systems. This review is drafted on the basis of the selected high quality research publications from the past decade. Although the development of forecast models for RE generation, i.e., wind and solar energy, is a well-researched area, however, the performance of these models is usually evaluated using statistical error metrics. With regard to application, determining the optimality of accurate forecasts in terms of system economics and major planning aspects is an emerging phenomenon, that chalks out the main subject area of this survey. Specifically, the application domains include: 1) optimal power system dispatch (unit commitment, generation scheduling, economic dispatch), 2) optimal sizing of energy storage system, 3) energy market policies and profit maximization of market participants, 4) reliability assessment, and 5) optimal reserve size determination in power systems. The application-oriented review on these vital areas can be used by the power sector for familiarization with the recent trends and for analyzing the impact of forecasting improvement on optimal power system design and operation.

Original languageEnglish
Pages (from-to)9-21
Number of pages13
JournalRenewable and Sustainable Energy Reviews
Volume100
DOIs
StatePublished - Feb 2019

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

Keywords

  • Energy market operation
  • Energy storage sizing
  • Forecasting models
  • Optimal spinning reserve
  • Power system dispatch
  • Reliability
  • Renewable energy resources

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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