Methods, controllers and systems for the control of distribution systems using a neural network architecture
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United States of America Patent
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May 24, 2022
Grant Date -
Jan 17, 2019
app pub date -
Dec 26, 2016
filing date -
Dec 31, 2015
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Abstract
A deep approximation neural network architecture which extrapolates data over unseen states for demand response applications in order to control distribution systems like product distribution systems of which energy distribution systems, e.g. heat or electrical power distribution, are one example. The method is a model-free control technique mainly in the form of Reinforcement Learning (RL) where a controller learns from interaction with the system to be controlled to control product distributions of which energy distribution systems, e.g. heat or electrical power distribution, are one example.
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