H
Hans-Peter Waldl
Researcher at University of Oldenburg
Publications - 10
Citations - 464
Hans-Peter Waldl is an academic researcher from University of Oldenburg. The author has contributed to research in topics: Wind power & Offshore wind power. The author has an hindex of 6, co-authored 9 publications receiving 439 citations.
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Short-term prediction of the aggregated power output of wind farms—a statistical analysis of the reduction of the prediction error by spatial smoothing effects
TL;DR: In this paper, an analytical model based on the spatial correlation function of the prediction error is derived to describe the statistical characteristics of arbitrary configurations of wind farms, and it is shown that the magnitude of the error reduction depends only weakly on the number of sites and is mainly determined by the size of the region.
Journal ArticleDOI
Modelling of Offshore Wind Turbine Wakes with the Wind Farm Program FLaP
Bernhard Lange,Hans-Peter Waldl,Algert Gil Guerrero,Detlev Heinemann,Rebecca Jane Barthelmie +4 more
TL;DR: In this article, an approach based on the simplified Reynolds equation with eddy viscosity closure is chosen to describe the wake behind one rotor in an axisymmetric wake model.
Journal ArticleDOI
Wake effects in a linear wind farm
TL;DR: The wind farm at Norddeich as mentioned in this paper consists of 5 wind turbines of 16 m rotor diameter and 55 kW power rating. The turbines are arranged in a straight line with a spacing of approximately 4 rotor diameters.
Anemos : development of a next generation wind power forecasting system for the large-scale integration of onshore & offshore wind farms
Georges Kariniotakis,Didier Mayer,J. Moussafir,R. Chevallaz-Perrier,Julio Usaola,Ismael Sánchez,Ignacio Marti,Henrik Madsen,Torben Skov Nielsen,C. Lac,P. Frayssinet,Hans-Peter Waldl,J. Halliday,Gregor Giebel,George Kallos,J. Ottavi,Ulrich Focken,Matthias Lange,Detlev Heinemann,J. Kintxo Ancin,J. Toefting,P. O'Donnel,D. Mc Coy,M. Collmann,A. Gigandidou,G. Gonzales-Morales,C. Barquero,I. Cruz,Nikos Hatziargyriou +28 more
TL;DR: In this article, the authors present the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting, exploiting both statistical and physical modeling approaches.
Modelling Tools for Wind Farm Upgrading
TL;DR: In this paper, the authors used a kinematic and an eddy-viscosity model to predict the wake losses of wind farms with different turbine types and hub heights.