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Description
Recent technology advancements in photovoltaics have enabled crystalline silicon (c-Si) solar cells to establish outstanding photoconversion efficiency records. Remarkable progresses in research and development have been made both on the silicon feedstock quality as well as the technology required for surface passivation, the two dominant sources of performance loss via

Recent technology advancements in photovoltaics have enabled crystalline silicon (c-Si) solar cells to establish outstanding photoconversion efficiency records. Remarkable progresses in research and development have been made both on the silicon feedstock quality as well as the technology required for surface passivation, the two dominant sources of performance loss via recombination of photo-generated charge carriers within advanced solar cell architectures.

As these two aspects of the solar cell framework improve, the need for a thorough analysis of their respective contribution under varying operation conditions has emerged along with challenges related to the lack of sensitivity of available characterization techniques. The main objective of my thesis work has been to establish a deep understanding of both “intrinsic” and “extrinsic” recombination processes that govern performance in high-quality silicon absorbers. By studying each recombination mechanism as a function of illumination and temperature, I strive to identify the lifetime limiting defects and propose a path to engineer the ultimate silicon solar cell.

This dissertation presents a detailed description of the experimental procedure required to deconvolute surface recombination contributions from bulk recombination contributions when performing lifetime spectroscopy analysis. This work proves that temperature- and injection-dependent lifetime spectroscopy (TIDLS) sensitivity can be extended to impurities concentrations down to 109 cm-3, orders of magnitude below any other characterization technique available today. A new method for the analysis of TIDLS data denominated Defect Parameters Contour Mapping (DPCM) is presented with the aim of providing a visual and intuitive tool to identify the lifetime limiting impurities in silicon material. Surface recombination velocity results are modelled by applying appropriate approaches from literature to our experimentally evaluated data, demonstrating for the first time their capability to interpret temperature-dependent data. In this way, several new results are obtained which solve long disputed aspects of surface passivation mechanisms. Finally, we experimentally evaluate the temperature-dependence of Auger lifetime and its impact on a theoretical intrinsically limited solar cell. These results decisively point to the need for a new Auger lifetime parameterization accounting for its temperature-dependence, which would in turn help understand the ultimate theoretical efficiency limit for a solar cell under real operation conditions.
ContributorsBernardini, Simone (Author) / Bertoni, Mariana I (Thesis advisor) / Coletti, Gianluca (Committee member) / Bowden, Stuart (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2018
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Description
This thesis examines using thermal energy storage as a demand side management tool for air-conditioning loads with the goal of increasing photovoltaic penetration. It uses Arizona State University (ASU) as a case study. The analysis is completed with a modeling approach using typical meteorological year (TMY) data, along with ASU’s

This thesis examines using thermal energy storage as a demand side management tool for air-conditioning loads with the goal of increasing photovoltaic penetration. It uses Arizona State University (ASU) as a case study. The analysis is completed with a modeling approach using typical meteorological year (TMY) data, along with ASU’s historical load data. Sustainability, greenhouse gas emissions, carbon neutrality, and photovoltaic (PV) penetration are all considered along with potential economic impacts.

By extrapolating the air-conditioning load profile from the existing data sets, it can be ensured that cooling demands can be met at all times under the new management method. Using this cooling demand data, it is possible to determine how much energy is required to meet these needs. Then, modeling the PV arrays, the thermal energy storage (TES), and the chillers, the maximum PV penetration in the future state can be determined.

Using this approach, it has been determined that ASU can increase their solar PV resources by a factor of 3.460, which would amount to a PV penetration of approximately 48%.
ContributorsRouthier, Alexander F (Author) / Honsberg, Christiana (Thesis advisor) / Fraser, Matthew (Committee member) / Bowden, Stuart (Committee member) / Arizona State University (Publisher)
Created2016
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Description
The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial

The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial viability of the system installations as well as the purchase price. The research was conducted using PPAs and historical solar power production data from the ASU's Energy Information System (EIS). The results indicate that most PPAs slightly underestimate the annual energy yield. However, the modeled power output from PVsyst indicates that higher energy outputs are possible with better system monitoring.
ContributorsVulic, Natasa (Author) / Bowden, Stuart (Thesis director) / Bryan, Harvey (Committee member) / Sharma, Vivek (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12