Heat pumps are becoming increasingly popular as a substitute for expensive oil and gas furnaces in private homes, however many heat pump systems are limited in their ability to automatically adjust temperatures when different factors change, such as the weather.
Assistant Professor Peter Gjøl Jensen has been granted an InnoExplorer from Innovation Fund Denmark for the project "Cost Efficient heat pumps using predictive DigitAltwins and Reinforcement learning (CEDAR)".
The project aims to significantly reduce the amount of energy used and, thus, the cost for homeowners, by improving the control of air-to-water and geothermal heat pumps.
By combining a digital twin, simulation, and AI technology, CEDAR will provide homeowners with an innovative heat pump system that automatically reacts to changes in weather, electricity prices, and residential behavior.
Want to know more?
Read the article: Homeowners can save a lot of money through intelligent heat pump control
Also, watch the interview with Peter Gjøl Jensen from Digital Tech Summit 2022, where he talked about reinforcement learning for green energy buildings
Contact:
Assistant Professor Peter Gjøl Jensen
Department of Computer Science
Mail: pgj@cs.aau.dk
Telephone: 6154 7278
