This product is a zip file that contains files that consist of PowerPoint slides synchronized with the audio-recording of the speaker, PDF files of the slides, and audio only (mp3 format) as noted.
Data-driven and model-predictive control (MPC) of buildings and building systems provides significant opportunities to reduce energy and greenhouse gas emissions from the built environment, and support load modulation for grid resilience. Ongoing research efforts in the U.S. work towards the development and demonstration of such methods for residential and commercial buildings. This session covers ongoing efforts at universities and national laboratories across the country.
- Model Predictive Control or Deep Reinforcement Learning-Based Control for Commercial Building Energy System< /br>Yangyang Fu, Ph.D., Member, Drexel University, Philadelphia, PA
- Optimal Precooling Using a Data-Driven Thermal Model in Residential Buildings< /br>Junke Wang, Student Member, University of Oklahoma, Norman, OK
- Load Management Using Reinforcement Learning< /br>Helia Zandi, Member, Oak Ridge National Laboratory, Oak Ridge, TN
Citation: ASHRAE 2021 Virtual Seminar, Extended Abstracts
Product Details
- Published:
- 2021
- File Size:
- 1 file
- Product Code(s):
- D-VCA21Sem38
