PyConTurb: An open-source constrained turbulence generator

Abstract

This paper presents an open-source tool that can be used to simulate turbulence boxes constrained by measured data, which is useful for wind turbine model validation. The tool, called PyConTurb for "Python Constrained Turbulence", uses a novel algorithm based on the Kaimal Spectrum with Exponential Coherence method, and the algorithm can efficiently generate turbulence boxes under a wide variety of measurement constraints. The theoretical background for the technique is presented along with a few notes on its implementation in Python. The utility of PyConTurb is demonstrated using real data measured using three-dimensional sonic anemometers at the Denmark Technical University Riso campus. The presented results demonstrate that PyConTurb can successfully generate turbulence boxes from real measured data, including recreating the desired spatial coherence relationships between the simulated and measured time series. PyConTurb is shown to be a promising tool for investigating new spatial coherence models and for future one-to-one wind turbine validation studies.