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.
Model-predictive control (MPC) based optimization approaches present a promising solution for increasing the operational efficiency of HVAC systems. This seminar discusses MPC optimization technologies, including a novel MPC approach, a field evaluation study, and a framework for performance benchmarking. Using a dynamic data-driven model or physical-based model and disturbance forecast to predict HVAC system performance, this provides a given objective and taking into consideration future events. It combines the models with the real-time data from the building automation system (BAS) to determine the optimal control setpoints and feedback to the BAS to minimize energy consumption or costs.
1. Adaptive Model-Based Predictive Control for HVAC
Draguna Vrabie, Ph.D., Member
2. Field Evaluation of Model-Predictive Optimized Control System in Commercial Buildings
Guanjing Lin, Ph.D., Associate Member
3. A Framework for Comparing Model Predictive Control Solutions: Needs and Approach
David Blum
| File Size : | 1
file
, 110 MB |
| Note : | This product is unavailable in Russia, Belarus |
| Product Code(s) : | D-KC19Sem39 |
| Published : | 2019 |
