Multifractal analysis of wind turbine power and rainfall from an operational wind farm – Part 1: Wind turbine power and the associated biases

Jose, Jerry; Gires, Auguste; Roustan, Yelva; Schnorenberger, Ernani; Tchiguirinskaia, Ioulia; Schertzer, Daniel

doi:https://doi.org/10.5194/npg-31-587-2024

Articles | Volume 31, issue 4

https://doi.org/10.5194/npg-31-587-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/npg-31-587-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 31, issue 4

Research article

|

10 Dec 2024

Research article |

| 10 Dec 2024

Multifractal analysis of wind turbine power and rainfall from an operational wind farm – Part 1: Wind turbine power and the associated biases

Jerry Jose, Auguste Gires, Yelva Roustan, Ernani Schnorenberger, Ioulia Tchiguirinskaia, and Daniel Schertzer

Data sets

Data for "Approximate multifractal correlation and products of universal multifractal fields, with application to rainfall data" by Auguste Gires, Ioulia Tchiguirinskaia, and Daniel Schertzer, NPG 2020 A. Gires et al. https://doi.org/10.5281/zenodo.3707904

Data for "Three months of combined high resolution rainfall and wind data collected on a wind farm" A. Gires et al. https://doi.org/10.5281/zenodo.5801900

Short summary

Wind energy exhibits extreme variability in space and time. However, it also shows scaling properties (properties that remain similar across different times and spaces of measurement). This can be quantified using appropriate statistical tools. In this way, the scaling properties of power from a wind farm are analysed here. Since every turbine is manufactured by design for a rated power, this acts as an upper limit on the data. This bias is identified here using data and numerical simulations.