| Abstract | This M.Tech Electrical Engineering topic focuses on Deep reinforcement learning using deep-Q-network for global maximum power point tracking in photovoltaic systems. It belongs to the Renewable Energy Converters area within Power Electronics. The work is suitable for research topic selection, synopsis preparation, literature review, converter modelling, MATLAB/Simulink or Python-based simulation, control design, hardware-oriented discussion, result analysis, and dissertation documentation. Students can use this 2023-onward open-access research reference as the base paper and then customize the implementation using suitable converter topology, switching strategy, controller design, efficiency analysis, THD analysis, power-quality metrics, and application requirements. |
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| Reference Paper | Deep reinforcement learning using deep-Q-network for global maximum power point tracking in photovoltaic systems |
| Year | 2024 |
| Domain | Power Electronics |
| Sub-Domain | Renewable Energy Converters |
| PDF Download | Download / View PDF |
| Get Help | Get Help on WhatsApp
Message: Hi FE, I need help with "Deep reinforcement learning using deep-Q-network for global maximum power point tracking in photovoltaic systems" in "Power Electronics" |
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