ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Filtering by
- All Subjects: Photovoltaic power systems--Reliability.
- Creators: Rogers, Bradley
Part 1 presents an approach for working towards the development of a standardized artificial soiling method for laminated photovoltaic (PV) cells or mini-modules. Construction of an artificial chamber to maintain controlled environmental conditions and components/chemicals used in artificial soil formulation is briefly explained. Both poly-Si mini-modules and a single cell mono-Si coupons were soiled and characterization tests such as I-V, reflectance and quantum efficiency (QE) were carried out on both soiled, and cleaned coupons. From the results obtained, poly-Si mini-modules proved to be a good measure of soil uniformity, as any non-uniformity present would not result in a smooth curve during I-V measurements. The challenges faced while executing reflectance and QE characterization tests on poly-Si due to smaller size cells was eliminated on the mono-Si coupons with large cells to obtain highly repeatable measurements. This study indicates that the reflectance measurements between 600-700 nm wavelengths can be used as a direct measure of soil density on the modules.
Part 2 determines the most dominant failure modes of field aged PV modules using experimental data obtained in the field and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 744 poly-Si glass/polymer frameless modules fielded for 18 years under the cold-dry climate of New York was evaluated. Defect chart, degradation rates (both string and module levels) and safety map were generated using the field measured data. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is used to determine the dominant failure or degradation modes in the strings and modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives.
The indoor and outdoor soiling studies were jointly performed by two Masters Students, Sravanthi Boppana and Vidyashree Rajasekar. This thesis presents the indoor soiling study, whereas the other thesis presents the outdoor soiling study. Similarly, the statistical risk analyses of two power plants (model J and model JVA) were jointly performed by these two Masters students. Both power plants are located at the same cold-dry climate, but one power plant carries framed modules and the other carries frameless modules. This thesis presents the results obtained on the frameless modules.
In the second part, a statistical degradation analysis is performed to determine if the degradation rates are linear or not in the power plants exposed in a hot-dry climate for the crystalline silicon technologies. This linearity degradation analysis is performed using the data obtained through two methods: current-voltage method; metered kWh method. For the current-voltage method, the annual power degradation data of hundreds of individual modules in six crystalline silicon power plants of different ages is used. For the metered kWh method, a residual plot analysis using Winters’ statistical method is performed for two crystalline silicon plants of different ages. The metered kWh data typically consists of the signal and noise components. Smoothers remove the noise component from the data by taking the average of the current and the previous observations. Once this is done, a residual plot analysis of the error component is performed to determine the noise was successfully separated from the data by proving the noise is random.
Part 1 of this thesis determines the most dominant failure modes of field aged photovoltaic (PV) modules using experimental data and statistical analysis, FMECA (Failure Mode, Effect, and Criticality Analysis). The failure and degradation modes of about 5900 crystalline-Si glass/polymer modules fielded for 6 to 16 years in three different photovoltaic (PV) power plants with different mounting systems under the hot-dry desert climate of Arizona are evaluated. A statistical reliability tool, FMECA that uses Risk Priority Number (RPN) is performed for each PV power plant to determine the dominant failure modes in the modules by means of ranking and prioritizing the modes. This study on PV power plants considers all the failure and degradation modes from both safety and performance perspectives, and thus, comes to the conclusion that solder bond fatigue/failure with/without gridline/metallization contact fatigue/failure is the most dominant failure mode for these module types in the hot-dry desert climate of Arizona.
Part 2 of this thesis determines the best method to compute degradation rates of PV modules. Three different PV systems were evaluated to compute degradation rates using four methods and they are: I-V measurement, metered kWh, performance ratio (PR) and performance index (PI). I-V method, being an ideal method for degradation rate computation, were compared to the results from other three methods. The median degradation rates computed from kWh method were within ±0.15% from I-V measured degradation rates (0.9-1.37 %/year of three models). Degradation rates from the PI method were within ±0.05% from the I-V measured rates for two systems but the calculated degradation rate was remarkably different (±1%) from the I-V method for the third system. The degradation rate from the PR method was within ±0.16% from the I-V measured rate for only one system but were remarkably different (±1%) from the I-V measured rate for the other two systems. Thus, it was concluded that metered raw kWh method is the best practical method, after I-V method and PI method (if ground mounted POA insolation and other weather data are available) for degradation computation as this method was found to be fairly accurate, easy, inexpensive, fast and convenient.