Presenters: Andrew Brody and Tom Anderson
This session will describe how AES uses AI and ML tools to give our wind energy operations teams early indications of an issue on a specific wind asset by leveraging principle components analysis on a sitewide basis. We can predict major component failures early enough to allow the site to make a more informed decision on when to perform the repair to better suit business needs. We can quickly analyze large wind sites of 50-200 wind turbines and give them a list of three to five wind turbines that actually need intervention. We are looking at every turbine sensor across the whole fleet, all in one analysis.
