The use of probabilistic forecasts: Applying them in theory and practice

  • Sue Ellen Haupt
  • , Mayte Garcia Casado
  • , Michael Davidson
  • , Jan Dobschinski
  • , Pengwei Du
  • , Matthias Lange
  • , Timothy Miller
  • , Corinna Mohrlen
  • , Amber Motley
  • , Rui Pestana
  • , John Zack

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

Abstract

Much of the electric system is weather dependent; thus, our ability to forecast the weather contributes to its efficient and economical operation. Climatological forecasts of meteorological variables are used for long-term planning, capturing changing frequencies of extreme events, such as cold and hot periods, and identifying suitable locations for deploying new resources. Planning for fuel delivery and maintenance relies on subseasonal to seasonal forecasts. On shorter timescales of days, the weather affects both energy demand and supply. Electrical load depends critically on weather because electricity is used for heating and cooling. As more renewable energy is deployed, it becomes increasingly important to understand how these energy sources vary with atmospheric conditions; thus, predictions are necessary for planning unit commitments. On the scales of minutes to hours, shortterm nowcasts aid in the real-time grid integration of these variable energy resources (VERs).

Original languageEnglish
Article number8878053
Pages (from-to)46-57
Number of pages12
JournalIEEE Power and Energy Magazine
Volume17
Issue number6
DOIs
StatePublished - Nov 1 2019

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