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Advances in Geosciences An open-access journal for refereed proceedings and special publications
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Volume 45 | Copyright
Adv. Geosci., 45, 289-294, 2018
https://doi.org/10.5194/adgeo-45-289-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Sep 2018

14 Sep 2018

A methodology for optimizing probabilistic wind power forecasting

Christos Stathopoulos1, George Galanis1,2, Nikolaos S. Bartsotas1, and George Kallos1 Christos Stathopoulos et al.
  • 1National and Kapodistrian University of Athens, School of Physics, Athens, Greece
  • 2Hellenic Naval Academy, Section of Mathematics, Mathematical Modelling and Applications Laboratory, Piraeus, Greece

Abstract. Deterministic wind power forecasts enclose an inherent uncertainty due to several sources of error. In order to counterbalance this deficiency, an analysis of the error characteristics and construction of probabilistic forecasts with associated confidence levels is necessary for the quantification of the corresponding uncertainty. This work proposes a probabilistic forecasting method using an atmospheric model, optimization techniques for addressing the temporal error dependencies and Kalman filtering for eliminating systematic errors and enhancing the symmetry-normality of the shaped error distributions. The method is applied in case studies, using real time data from four wind farms in Greece. The performance is compared against a reference method as well as other common methods showing an improvement in the predictive reliability.

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