Wind Turbine Power Prediction

By Elijah Reber1; Guang Lin2; Nickolas D Winovich2

1. Penn State University 2. Purdue University

This tool uses a trained neural network algorithm to predict the energy output and failure of a wind turbine using sensor data

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Version 1.0 - published on 30 Jul 2018

doi:10.4231/D3QJ78131 cite this

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Abstract

This GUI uses a neural network algorithm that was trained on sensor data taken from the Mozura Wind Farm in Monetenegro over 13 months.  The algorithm takes in the numbers as inputs and provides a probability distribution of the 30 second and 10 minute energy outputs, as well as a binary prediction of failure.

Cite this work

Researchers should cite this work as follows:

  • Elijah Reber, Guang Lin, Nickolas D Winovich (2018), "Wind Turbine Power Prediction," https://nanohub.org/resources/turbinepredict. (DOI: 10.4231/D3QJ78131).

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Tags

  1. energy
  2. neural computations
  3. Wind