Description |
1 online resource (8 pages) : illustrations (chiefly color). |
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text rdacontent |
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computer rdamedia |
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online resource rdacarrier |
Series |
NREL/CP ; 5500-57340 |
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Conference paper (National Renewable Energy Laboratory (U.S.)) ; 5500-57340.
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Note |
Title from PDF title screen (viewed on Apr. 18, 2013). |
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"January 2013." |
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"To be presented at the IEEE Green Technologies Conference, Denver, Colorado, April 4-5, 2013." |
Bibliography |
Includes bibliographical references (page 8). |
Type Of Report |
Conference paper. |
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 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. |
Funding |
Sponsored by National Renewable Energy Laboratory contract no.: DE-AC36-08GO28308 |
Subject |
Electric power-plants -- Load -- Congresses.
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Electric power systems -- Load dispatching -- Congresses.
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Electric power distribution -- Congresses.
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Renewable energy sources -- Congresses.
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Added Author |
Lew, Debra, author.
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Milligan, Michael R., author.
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National Renewable Energy Laboratory (U.S.), issuing body.
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IEEE Green Technologies Conference (2013 : Denver, Colo.), sponsoring body.
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Added Title |
Short term load forecasting error distributions and implications for renewable integration studies |
Gpo Item No. |
0430-P-04 (online) |
Sudoc No. |
E 9.17:NREL/CP-5500-57340 |
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