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DOE OSTI · 1891467

Adaptive Neurocontrol for Grid-Following Inverters

Chang, Chin-Yao·Lin, Yashen
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Abstract

The new generation of power systems involve a large number of autonomous operating units with the flow of data being restricted by privacy concerns or infrastructure hurdles. The systems are also time-varying so the control should adjust in a timely manner to avoid failures that usually have very negative economical implications. Adaptive neurocontrol which takes elements from adaptive control (great for time-varying problems) and model identification (could be in the form of neural network) by using local available data is a compelling tool. In this work, we summarize analytical results for adaptive neurocontrol, followed with numerical verification of how the method could work for future grids.

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24 POWER TRANSMISSION AND DISTRIBUTIONAdaptive ControlGrid-Following InverterMachine Learning

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Chang, Chin-Yao, Lin, Yashen. 2022-10-01. Adaptive Neurocontrol for Grid-Following Inverters. https://doi.org/10.2172/1891467

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