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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
    • Red Electrica de Espana
    • Australian Energy Market Operator (AEMO)
    • Fraunhofer Institute for Energy Economics and Energy System Technology
    • ERCOT
    • Energy and Meteo Systems GmbH
    • Southwest Power Pool
    • WEPROG
    • CAISO
    • RandD Nester
    • UL-AWS Truepower

    Research output: Contribution to journalArticlepeer-review

    55 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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