The growing demand for renewable energy sources has prompted significant transformations in the electrical grid, leading to an increased uncertainty in both stability and reliability. Testbeds have become essential in testing new ideas and technologies under controlled conditions to address these challenges. This research focuses on the development of techniques and algorithms to facilitate ongoing testing of new technologies and scenarios, thereby enhancing efficiency, reliability, and deepening the understanding of current technologies. This thesis provides a comprehensive discussion of the various aspects involved in developing a testbed, including necessary calculations and considerations that need to be taken before a test is conducted. Specifically, it explores the utilization of a three phase three level inverter and programmable instrument within the testbed framework. The collected data from these experiments are harnessed to train a Hammerstein Wiener photovoltaic model, enabling an improved understanding and analysis of the system. By conducting an analysis of different frequencies and their effects on the values of various control variables (ud and uq), as well as examining DC and three-phase AC currents using electric loads in constant resistance mode, this research seeks to gain insights into the behavior and performance of the system. Through these efforts, this research contributes to the advancement of renewable energy technologies by providing a reliable and efficient platform for experimentation and generating reliable data for model development. By deepening our understanding of system dynamics and evaluating the impact of different variables, this research aims to enhance the stability and reliability of renewable energy systems, facilitating the transition towards a sustainable energy future.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2851 |
| Date | 15 August 2023 |
| Creators | Carroll, Maximilian |
| 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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