AI Driven HVAC Optimization with Tagup

Tagup’s optimization platform combines machine learning and physics to optimize HVAC equipment in real time, in response to changes in anticipated weather and load. By using HVAC engineering principles as a scaffolding for training, the platform can estimate the impact of operational changes on operating cost or carbon emission before collecting sensor data, and then continuously refine the models. Once deployed, it can optimize multiple control points—including condenser and chilled water temperature set points—to improve system efficiency while simultaneously ensuring the system delivers the projected cooling load. In this talk, we will provide an overview of the technology, how it is being deployed via integrations with building automation or distributed control systems, how it performs at different sites, and what is next in terms of development. BIO: Robert Lauer has a background in high energy physics research. At Tagup, he is the technical lead for HVAC Optimization, developing the AI models for live optimization of cooling systems coordinating the deployment of the technology on buildings across the country.