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Device optimization using machine learning with hybrid heat pumps

Spil, Gino van (2021) Device optimization using machine learning with hybrid heat pumps.

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Abstract:With the switch to electric energy from renewable sources and the desire to stop using natural gas for heating the electricity gets loaded more. This can lead to congestion and overloading of the grid. Methods currently already exist to prevent overloading of the grid by changing the power consumption of appliances in the household. To optimally plan the energy usage of the heating system models are needed for the specific heating system. In this work a literature survey is done on existing models and machine learning techniques to improve the models. Simulations are performed to determine what model benefits most of improvement and what data need to be collected during the experiments. Experiments are performed with a heat pump to make models under ideal and non-ideal conditions. The model created in non-ideal conditions deviates up to a maximum 0f 1.6\% during the steady state operation compared to the model created in ideal conditions.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Embedded Systems MSc (60331)
Link to this item:https://purl.utwente.nl/essays/88651
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