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Short-term load forecasting error distributions and implications for renewable integration studies : preprint

Author: Bri-Mathias Hodge; Debra Lew; Michael R Milligan; National Renewable Energy Laboratory (U.S.),
Publisher: [Golden, Colo.] : National Renewable Energy Laboratory, 2013.
Series: Conference paper (National Renewable Energy Laboratory (U.S.)), 5500-57340.
Edition/Format:   eBook : Document : Conference publication : National government publication : English
Database:WorldCat
Summary:
Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that  Read more...
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Genre/Form: Conference proceedings
Congresses
Material Type: Conference publication, Document, Government publication, National government publication, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Bri-Mathias Hodge; Debra Lew; Michael R Milligan; National Renewable Energy Laboratory (U.S.),
OCLC Number: 839964796
Notes: Title from PDF title screen (viewed on Apr. 18, 2013).
"January 2013."
"To be presented at the IEEE Green Technologies Conference, Denver, Colorado, April 4-5, 2013."
Description: 1 online resource (8 pages) : illustrations (chiefly color).
Series Title: Conference paper (National Renewable Energy Laboratory (U.S.)), 5500-57340.
Other Titles: Short term load forecasting error distributions and implications for renewable integration studies
Responsibility: B.-M. Hodge, D. Lew, and M. Milligan.

Abstract:

Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

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