Power Processing Architectures for Sustainable Power and Energy
Ramyar, Alireza
2023
Abstract
Power processing transforms energy to be used for work, extracted from clean power generation, or stored effectively and sustainably. This thesis investigates (1) power processing architectures and methods to harvest power in solar photovoltaic (PV) systems efficiently, (2) power processing architectures and methods to employ second-use battery energy storage systems (2-BESS) optimally, and (3) temperature measurement of wide-bandgap power semiconductors, which are widely used in solar PV systems and battery energy storage systems (BESS). The first part of this thesis focuses on architectures and methods for differential diffusion charge redistribution (dDCR) solar PV modules. These modules enable maximum power point tracking (MPPT) with cell-level granularity, which extracts nearly all the accessible power from each solar PV cell and is the best solution in terms of MPPT efficiency in solar PV systems. Since dDCR solar PV modules have two output ports, the conventional one-port hardware cannot be integrated with them. This thesis presents a new two-port up/down dc-dc MPPT converter and a new two-port hardware emulator for dDCR solar PV modules. Additionally, a new method for measuring diffusion capacitance in solar PV cells (an important parameter in dDCR modules) is introduced. The second and third parts of this thesis investigate power processing architectures and methods in 2-BESSs for dc and ac applications. BESSs play important roles in grids, such as supporting renewable power systems like solar PV systems, voltage and frequency regulation for grid power quality improvement, and supporting electric vehicle (EV) fast charging. At the same time, second-use batteries from the exponential growth of EVs represent a challenge. Reusing the second-use EV batteries for stationary applications introduces a sustainable approach and adds economic value to these batteries. This thesis presents a new stochastic method for lite-sparse hierarchical partial power processing (LS-HiPPP) architecture to optimize 2-BESS power processing over the lifetime degradation of batteries. Additionally, a framework for optimizing multilevel ac battery energy storage systems (MAC-BESS) is introduced, which is particularly advantageous for 2-BESSs. The fourth/last part of this thesis focuses on the accurate temperature measurement of the active area for wide-bandgap power semiconductors. High breakdown voltage, low on-resistance, and high speed have made wide-bandgap power semiconductors suitable for many applications, such as solar PV systems, BESSs, EVs, hybrid/electric aircraft, and wireless power transfer. However, the maximum power density of these devices is limited by the channel temperature rise. Thus, accurate temperature measurement of the active area is essential in research on wide-bandgap power semiconductors, often hampered by packaging and cooling methods.Deep Blue DOI
Subjects
Power Electronics Solar Photovoltaic Systems Battery Energy Storage Systems Wide-Bandgap Power Semiconductors
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