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|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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|Reinforcement Learning-base DC:DC Converter for DC Microgrid Applications.pdf|
|Final Report||12.59 MB||Adobe PDF||View/Open|
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