Patent · US Active

Methods, controllers and systems for the control of distribution systems using a neural network architecture

US11341396B2 · kind B2 · utility

0Cited by

0References

20Claims

0Family size

Assignee

VITO NV · BE

Inventors

Bert Claessens · Spalbeek, BE
Peter VRANCX · Brussels, BE

Key dates

Filing date	Dec 26, 2016
Grant date	May 24, 2022
Priority date	—
Expiry date	Aug 24, 2039

Classification

Technology area (CPC G)Physics
CPC primaryG06Q50/06
WIPO fieldComputer technology
WIPO sectorElectrical engineering

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.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.