Abstract

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.

Notes

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Graduation Date

2023

Semester

Summer

Advisor

Sun, Wei

Degree

Master of Science in Electrical Engineering (M.S.E.E.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Electrical Engineering

Identifier

CFE0009702; DP0027809

URL

https://purls.library.ucf.edu/go/DP0027809

Language

English

Release Date

August 2024

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Campus-only Access)

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Restricted to the UCF community until August 2024; it will then be open access.

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