Solar-based converter design is of paramount importance in 2023 due to the rapidly increasing demand for renewable energy sources and the need to reduce carbon emissions to mitigate the effects of climate change. As the world continues to shift towards a sustainable future, solar power is expected to play a critical role in meeting the growing energy demand. A multiport converter with renewable energy sources and storage unit must be able to regulate the power output from the panels and ensure that it is compatible with the grid or other energy storage systems. In this dissertation, different multiport systems have been designed and analyzed along with advanced control methods for solar battery integration. An LLC converter-based design has been developed to efficiently convert and regulate energy from solar panels and battery storage. This converter is designed to have multiple ports to enable the simultaneous charging and discharging of multiple batteries, making it suitable for both residential and commercial applications. A multiport single LLC tank-based converter is an efficient and versatile solution for energy storage and management in solar systems. Its multiple ports and resonant LLC topology make it suitable for a range of applications, from small-scale residential systems to larger commercial systems. Additionally, other MPC grid-integrated topologies are also investigated in this dissertation. All these circuits aim to track maximum power from the energy sources and require reliable control strategies. In this regard, multiple advanced hybrid control methods based on fuzzy logic and neural network have been developed as a part of this dissertation. All the simulation studies have been performed matlab/Simulink as well as plecs platform and the experimental prototypes have been tested to verify the concepts.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2886 |
| Date | 01 January 2023 |
| Creators | Ghosh, Sumana |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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