TY - JOUR A1 - Falk, Constantin A1 - El Ghayed, Tarek A1 - van de Sand, Ron A1 - Reiff-Stephan, Jörg T1 - A Data-Driven Approach Towards the Application of Reinforcement Learning Based HVAC Control JF - Journal of the Nigerian Society of Physical Sciences N2 - Refrigeration applications consume a significant share of total electricity demand, with a high indirect impact on global warming through greenhouse gas emissions. Modern technology can help reduce the high power consumption and optimize the cooling control. This paper presents a case study of machine-learning for controlling a commercial refrigeration system. In particular, an approach to reinforcement learning is implemented, trained and validated utilizing a model of a real chiller plant. The reinforcement-learning controller learns to operate the plant based on its interactions with the modeled environment. The validation demonstrates the functionality of the approach, saving around 7% of the energy demand of the reference control. Limitations of the approach were identified in the discretization of the real environment and further model-based simplifications and should be addressed in future research. KW - refrigeration system KW - reinforcement learning KW - optimized control KW - Q-learning Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-17066 SN - 2714-4704 VL - 5 IS - 1 PB - Department of Physics, Federal University Lafia Nasarawa State, Nigeria ; Nigerian Society of Physical Sciences ER -