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mylonasc / fatigue_cvae

Code for "Conditional Variational Autoencoders for Probabilistic Wind Turbine Blade Fatigue Estimation using SCADA data"
Apache License 2.0
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Conditional Variational Autoencoder for Wind Turbine Blade Fatigue

This code applied a simple Conditional Variational Autoencoder (CVAE) with feed-forward layers on the problem of estimation of fatigue from coarse (10-minute) Supervisory Control and Data Acquisition (SCADA) system data.

In the following animation the effect of changing the conditioning variables on the estimated cross-section fatigue values is shown. anim

For more information on the simulation data please refer to our paper.

Dataset and Pre/post processing code.

The dataset is fatigue computations for 1999 different wind conditions, performed with OpenFAST and BECAS.

Dependencies

The dependencies are tensorflow (tested with version 2.4.0) and tensorflow_probability(tested with version 0.12.1).

Demo Colab

You can run the code in a google colab notebook:

Open In Colab