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

This tool is closed source.

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Usage

World usage

Location of all "Wind Turbine Power Prediction" Users Since Its Posting

Cumulative Simulation Users

22

1 2 4 5 7 9 9 9 10 10 11 11 12 12 12 12 13 16 17 18 19 20 21 22 22

Users By Organization Type
Type Users
Unidentified 17 (77.27%)
Educational - University 5 (22.73%)
Users by Country of Residence
Country Users
us UNITED STATES 4 (80%)
in INDIA 1 (20%)

Simulation Runs

72

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Overview
Average Total
Wall Clock Time 6.07 hours 10.61 days
CPU time 15.81 seconds 11.07 minutes
Interaction Time 23.54 minutes 16.48 hours