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  • 标题:Forecasting Analysis Based on Multi-scale and Multi-time with Uncertainty
  • 本地全文:下载
  • 作者:Keon-Jun Park ; Sung-Yong Son
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2019
  • 卷号:52
  • 期号:4
  • 页码:318-323
  • DOI:10.1016/j.ifacol.2019.08.229
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe dissemination of distributed resources presents a new paradigm for the power industry. Especially solar power is creating a new chapter for trading electricity as a new source. Solar power sources and load resources are each uncertain by their size and time factors. This paper discusses the uncertainties due to the accuracy of the forecast by forecasting PV power source and by forecasting load resource based multi-scale and multi-time. To do this, artificial neural networks are used to forecast these resources at a different time interval and the amounts by aggregation. Uncertainty from the forecasting results is discussed.
  • 关键词:KeywordsPV forecastingLoad forecastingArtificial IntelligenceMulti-scaleMulti-timeUncertainty
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