An overview on wind power forecasting methods

Songjian Chai, Zhao Xu, Loi Lei Lai, Kit Po Wong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

With the continually increasing growth in wind generation being integrated into the electric networks, it brings about significant challenges for decision-makers of power system operation due to its high volatility and uncertainty. One efficient approach to tackling such a problem is using reliable forecasting tools. As the conventional point forecasting can only provide a deterministic predicted value, instead, the probabilistic interval forecasting was attracted broad attention in the last few years since it can reflect the information of the uncertainties associated with wind power generation, which can significantly facilitate a large number of decision-making problems in power system operation. This paper presents an overview of current methods used in wind power forecasting. First of all, the frequently-used traditional point forecasting methods are reviewed Afterwards, various state-of-the-art techniques in terms of probabilistic forecasting are discussed. The indications for future development in wind power forecasting approaches and conclusions are given in the end.
Original languageEnglish
Title of host publicationProceedings of 2015 International Conference on Machine Learning and Cybernetics, ICMLC 2015
PublisherIEEE Computer Society
Pages765-770
Number of pages6
Volume2
ISBN (Electronic)9781467372213
DOIs
Publication statusPublished - 30 Nov 2015
Event14th International Conference on Machine Learning and Cybernetics, ICMLC 2015 - Holiday Inn Guangzhou Shifu, Guangzhou, China
Duration: 12 Jul 201515 Jul 2015

Conference

Conference14th International Conference on Machine Learning and Cybernetics, ICMLC 2015
CountryChina
CityGuangzhou
Period12/07/1515/07/15

Keywords

  • Interval forecast
  • Point forecast
  • Probabilistic forecast
  • Wind power forecast

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

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