Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77760
Title: Reinforcement learning-base DC/DC converter for DC microgrid applications
Authors: Koh, Alvin Kai Kiat
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: DC/DC power converters are used widely to convert voltage for various equipment. Some examples include personal computers, office equipment, telecommunication equipment, dc motor drives, as well as DC microgrid applications. In the case of DC microgrids, the output load varies with respect to time. Hence, to maximise the efficiency of the converter, a predictive control method of the discrete-time state-space model must first be formulated. Due to the complexity of a practical system, it is difficult to model the controlled plant. Therefore, with the help of reinforcement learning (RL), the need for a model is eradicated.
URI: http://hdl.handle.net/10356/77760
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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