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  • 1.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Matusevicius, Tadas
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems.
    Swedish Wind Power Forecasts: Procedure, ErrorDistribution and Spacio-Temporal Correlation2017In: 16th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, Berlin, 2017, article id WIW17-124Conference paper (Refereed)
    Abstract [en]

    The stochastic nature of wind imposes challengeson accurate predictions of wind power generation. A goodunderstanding of the errors that may occur is imperativefor greater penetration of wind power into the system, asit can facilitate planning and operation tasks. In this paper,Swedish wind power forecast accuracy over the forecasthorizon is analyzed and compared among different biddingzones. The root-mean-square error trajectory over the horizonis shown for Sweden and its individual bidding areas. Inaddition, a significant systematic wind power under-predictionis identified and discussed. The paper continues to analyzethe wind power forecast error distribution with respect tothe horizon. Furthermore, the spacio-temporal correlationbetween the errors at different horizons and bidding areasis presented. As expected, a stronger correlation between theforecast errors is identified in neighboring areas.

  • 2.
    Herre, Lars
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Matusevičius, Tadas
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Olauson, Jon
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Exploring Wind Power Prognosis Data on Nord Pool: The Case of Sweden and Denmark2019In: IET Renewable Power Generation, ISSN 1752-1416, E-ISSN 1752-1424, ISSN 1752-1416Article in journal (Refereed)
    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.

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