4 papers
BESTOpt: A Modular, Physics-Informed Machine Learning based Building Modeling, Control and Optimization Framework
Zixin Jiang, Ruizhi Song, Guowen Li +5
Modern buildings are increasingly interconnected with occupancy, heating, ventilation, and air-conditioning (HVAC) systems, distributed energy resources (DERs), and power grids. Mo…
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning
Zixin Jiang, Xuezheng Wang, Bing Dong
Physics-informed machine learning (PIML) provides a promising solution for building energy modeling and can serve as a virtual environment to enable reinforcement learning (RL) age…
Physics-informed machine learning for building performance simulation-A review of a nascent field
Zixin Jiang, Xuezheng Wang, Han Li +5
Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing performance of the built environment, optimizing energy efficiency, im…
The Smart Buildings Control Suite: A Diverse Open Source Benchmark to Evaluate and Scale HVAC Control Policies for Sustainability
Judah Goldfeder, Victoria Dean, Zixin Jiang +4
Commercial buildings account for 17% of U.S. carbon emissions, with roughly half of that from Heating, Ventilation, and Air Conditioning (HVAC). HVAC devices form a complex thermod…