Adaptively learning surrogate model for predicting building system dynamics from simulation model
US11531308B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 23, 2019 |
| Grant date | Dec 20, 2022 |
| Priority date | — |
| Expiry date | Nov 19, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG05B2219/25011
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for training a surrogate model for predicting system states for a building management system based on generated data from a simulation model are disclosed herein. The simulation model is calibrated for a building of interest. The building of interest includes building equipment operable to control a variable state of the building. The simulated data of system states are generated using the calibrated simulation model. A surrogate model is trained based on the simulated data of system states from the calibrated simulation model. System state predictions are generated using the surrogate model. The surrogate model is re-trained based on updated operational data. An updated series of system state predictions is generated using the re-trained surrogate model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.