Control temperature of room with reinforcement learning
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Författare
Typ
Examensarbete på kandidatnivå
Program
Modellbyggare
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ISSN
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Sammanfattning
The human connection to the increase of average temperature on earth is a known
issue because of the energy need that is partly full-filled with fossil fuels. Currently
40% of the world’s energy comes from buildings and by making heating/cooling systems
more efficient there could be a big reduction of the energy need.
The purpose of this research is to explore the possibilities of implementing machine
learning to regulate temperature in a room.
Using Python, Tensorflow and the Stable-baselines framework a simple model for
reinforcement learning was created and trained on to explore if it was possible to
use reinforcement learning to regulate the temperature in a room.
The trained model managed to control the inside-temperature in a stable manner,
this with a highly fluctuating outside-temperature and with a room-size never seen
before. The paper will also discuss the steps taken to create a model, a working
algorithm and further work.
Beskrivning
Ämne/nyckelord
Reinforcement learning, Tensorflow, Python, Stable-Baselines, Thermal control system,, Temperature control, Room