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The Use of Probabilistic Forecasts: Applying them in Theory and Practice

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

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IEEE power & energy magazine 17 (2019), No.6, pp.46-57
ISSN: 1540-7977
English
Journal Article
Fraunhofer IEE ()
forecasting; probabilistic; EPS; grid integration

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).

: http://publica.fraunhofer.de/documents/N-572536.html