Evaluation of AI-driven adaptive control algorithms for optimizing heat pump efficiency in building heating and hot water supply: First practical insights

We propose two distinct AI-based approaches to smart heat pump control for domestic hot water and space heating heat pumps, which can consider various variable factors (such as load prediction from forecasting algorithms and weather), learn the system model and adapt to changing environmental conditions. Based on these factors, the controllers optimize the management of the heat pumps to reduce energy consumption while maintaining user comfort. We present initial insights gained from laboratory experiments and a real-world field test, highlighting the practical effectiveness and environmental impacts of AI-driven strategies for enhancing heat pump efficiency, while also identifying areas for further improvement.