Quantifying the value of improved wind energy forecasts in a pool-based electricity market

Simple item page
dc.contributor.authorMcGarrigle, Edward V.
dc.contributor.authorLeahy, Paul G.
dc.contributor.funderIrish Research Council for Science Engineering and Technologyen
dc.date.accessioned2015-05-06T11:45:47Z
dc.date.available2015-05-06T11:45:47Z
dc.date.issued2015-08
dc.date.updated2015-05-06T11:34:01Z
dc.description.abstractThis work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.en
dc.description.sponsorshipIrish Research Council (Embark Scholarship); Science Foundation Ireland (Stokes Lectureshipen
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMcGarrigle, Edward V.; Leahy, Paul G. (2015) 'Quantifying the value of improved wind energy forecasts in a pool-based electricity market'. Renewable Energy, 80 (8):517-524.en
dc.identifier.doi10.1016/j.renene.2015.02.023
dc.identifier.endpage524en
dc.identifier.issn0960-1481
dc.identifier.issued8en
dc.identifier.journaltitleRenewable Energyen
dc.identifier.startpage517en
dc.identifier.urihttps://hdl.handle.net/10468/1792
dc.identifier.volume80en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S0960148115001135
dc.rightsCopyright © 2015 Elsevier Inc. All rights reserved. NOTICE: this is the author’s version of a work that was accepted for publication in Renewable Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable Energy [Volume 80, August 2015, Pages 517–524] http://dx.doi.org/10.1016/j.renene.2015.02.023en
dc.subjectWind forecasen
dc.subjectUnit commitmenten
dc.subjectEconomic dispatchen
dc.subjectPLEXOSen
dc.subjectAutoregressive moving averageen
dc.subjectCurtailmenten
dc.subjectStochastic schedulingen
dc.titleQuantifying the value of improved wind energy forecasts in a pool-based electricity marketen
dc.typeArticle (peer-reviewed)en
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
EdwardMcGarrigle_Wind_Forecasting_and_bbl.pdf
Size:
395.38 KB
Format:
Adobe Portable Document Format
Description:
Accepted Version
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
2.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Civil and Environmental Engineering - Journal articles