Methods and systems for training HVAC control using surrogate model
US11573540B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 23, 2019 |
| Grant date | Feb 7, 2023 |
| Priority date | — |
| Expiry date | Mar 6, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/2614
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for training a reinforcement learning (RL) model for HVAC control are disclosed herein. A calibrated simulation model is used to train a surrogate model of the HVAC system operating within a building. The surrogate model is used to generate simulated experience data for the HVAC system. The simulated experience data can be used to train a reinforcement learning (RL) model of the HVAC system. The RL model is used to control the HVAC system based on the current state of the system and the best predicted action to perform in the current state. The HVAC system generates real experience data based on the actual operation of the HVAC system within the building. The real experience data is used to retrain the surrogate model, and additional simulated experience data is generated using the surrogate model. The RL model can be retrained using the additional simulated experience data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.