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.
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Characterization and analysis of long term field aged photovoltaic modules and encapsulant materials
The accelerated UV testing was performed in a UV chamber equipped with UV lights at an ambient temperature of 50°C, little or no humidity and total UV dosage of 400 kWh/m2. The mini-modules were maintained at three different temperatures through UV light heating by placing different thickness of thermal insulation sheets over the backsheet. Also, prior to thermal insulation sheet placement, the backsheet and laminate edges were fully covered with aluminum tape to prevent oxygen diffusion into the module and hence the photobleaching reaction.
The characterization results showed that mini-modules with UV-cut EVA suffered from discoloration while the modules with UV-pass EVA suffered from delamination. UVf imaging technique has the capability to identify the discoloration region in the UVC modules in the very early stage when the discoloration is not visible to the naked eyes, whereas Isc measurement is unable to measure the performance loss until the color becomes visibly darker. YI also provides the direct evidence of yellowing in the encapsulant. As expected, the extent of degradation due to discoloration increases with the increase in module temperature. The Isc loss is dictated by both the regions – discolored area at the center and non-discolored area at the cell edges, whereas the YI is only determined at the discolored region due to low probe area. This led to the limited correlation between Isc and YI in UVC modules.
In case of UVP modules, UV radiation has caused an adverse impact on the interfacial adhesion between the EVA and solar cell, which was detected from UVf images and severe Isc loss. No change in YI confirms that the reason for Isc loss is not due to yellowing but the delamination.
Further, the activation energy of encapsulant discoloration was estimated by using Arrhenius model on two types of data, %Isc drop and ΔYI. The Ea determined from the change in YI data for the EVA encapsulant discoloration reaction without the influence of oxygen and humidity is 0.61 eV. Based on the activation energy determined in this work and hourly weather data of any site, the degradation rate for the encaspulant browning mode can be estimated.
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aged modules also show that humidity accelerates the formation of IMC as they showed thicker AgxSny layer and weak interconnect-contact interfaces as compared to Arizona modules. It is also shown that climatic conditions have different effects on rate at which CuxSny and AgxSny intermetallic compounds are formed.
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.