Articles | Volume 5, issue 3
Wind Energ. Sci., 5, 1211–1223, 2020
Wind Energ. Sci., 5, 1211–1223, 2020
Research article
23 Sep 2020
Research article | 23 Sep 2020

Multipoint reconstruction of wind speeds

Christian Behnken et al.

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Cited articles

IEC: IEC 61400-1 Wind turbines Part 1: Design requirements, 2005. a
Ali, N., Fuchs, A., Neunaber, I., Peinke, J., and Cal, R. B.: Multi-scale/fractal processes in the wake of a wind turbine array boundary layer, J. Turbul., 20, 93–120,, 2019. a
Anvari, M., Lohmann, G., Wächter, M., Milan, P., Lorenz, E., Heinemann, D., Tabar, M. R. R., and Peinke, J.: Short term fluctuations of wind and solar power systems, New J. Phys., 18, 063027,, 2016. a
Boettcher, F., Renner, C., Waldl, H.-P., and Peinke, J.: On the statistics of wind gusts, Bound.-Lay. Meteorol., 108, 163–173,, 2003. a, b
Brokish, K. and Kirtley, J. L.: Pitfalls of modeling wind power using Markov chains, in: 2009 IEEE/PES Power Systems Conference and 320 Exposition, 1–6,, 2009. a, b
Short summary
We extend the common characterisation and modelling of wind time series with respect to higher-order statistics. We present an approach which enables us to obtain the general multipoint statistics of wind time series measured. This work is an important step in a more comprehensive description of wind also including extreme events. Important is that we show how stochastic equations can be derived from measured wind data which can be used to model long time series.