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Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (IRES)ORCID iD: 0000-0003-0685-0199
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (IRES)
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (IRES)
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0002-8189-2420
2019 (English)In: IET Renewable Power Generation, ISSN 1752-1416, E-ISSN 1752-1424, ISSN 1752-1416Article in journal (Refereed) Published
Abstract [en]

A good understanding of forecast errors is imperative for greater penetration of wind power, as it can facilitate planning and operation tasks. Oftentimes, public data is used for system studies without questioning or verifying its origin. In this paper, we propose a methodology to verify public data with the example of wind power prognosis published by Nord Pool. We focus on Swedish data and identify a significant bias that increases over the forecast horizon. In order to explore the origin of this bias, we first compare against Danish forecast and then describe the underlying structure behind the submission processes of this data. Based on the balance settlement structure, we reveal that Swedish "wind power prognoses" on Nord Pool are in fact rather wind production plans than technical forecasts. We conclude with the recommendation for improved communication and transparency with respect to terminology of public data on Nord Pool. We stress the importance for the research community to check publicly available input data before further use. Furthermore, the root-mean-square error and the spatio-temporal correlation between the errors in the bidding areas at different horizons is presented. Even with this compromised data, a stronger correlation is identified in neighbouring areas.

Place, publisher, year, edition, pages
2019.
Keywords [en]
wind power forecasts, forecast anaylsis
Keywords [sv]
vindkraftspognoser, analys av vindkraftsprognoser
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Energy Systems
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-241639DOI: 10.1049/iet-rpg.2018.5086ISI: 000462942900006Scopus ID: 2-s2.0-85063728250OAI: oai:DiVA.org:kth-241639DiVA, id: diva2:1282265
Note

QC 20190124

Available from: 2019-01-24 Created: 2019-01-24 Last updated: 2019-04-29Bibliographically approved

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Publisher's full textScopushttps://digital-library.theiet.org/content/journals/10.1049/iet-rpg.2018.5086

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Herre, LarsMatusevičius, TadasOlauson, JonSöder, Lennart

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CiteExportLink to record
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Citation style
  • apa
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