Intelligent Control of Networked Buildings
Description:
The project involves developing and comparing computationally inexpensive black/grey-box developing models (neural network architectures and Bayesian estimation methods) for residential/commercial buildings where data comes from EnergyPlus and other open-source building data repositories like PecanStreet. Then a simulation framework has to be developed to co-simulate these building models at scale with OpenDSS (along with HELICS) to aid the development of both single-building and aggregator-level intelligent controllers which can optimize the energy consumption of buildings for grid support. Currently, we are pursuing model estimation and development of the co-simulation platform.