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The volume of end-of-life photovoltaic (PV) modules is increasing as the global PV market increases, and the global PV waste streams are expected to reach 250,000 metric tons by the end of 2020. If the recycling processes are not in place, there would be 60 million tons of end-of-life PV

The volume of end-of-life photovoltaic (PV) modules is increasing as the global PV market increases, and the global PV waste streams are expected to reach 250,000 metric tons by the end of 2020. If the recycling processes are not in place, there would be 60 million tons of end-of-life PV modules lying in the landfills by 2050, that may not become a not-so-sustainable way of sourcing energy since all PV modules could contain certain amount of toxic substances. Currently in the United States, PV modules are categorized as general waste and can be disposed in landfills. However, potential leaching of toxic chemicals and materials, if any, from broken end-of-life modules may pose health or environmental risks. There is no standard procedure to remove samples from PV modules for chemical toxicity testing in the Toxicity Characteristic Leaching Procedure (TCLP) laboratories as per EPA 1311 standard. The main objective of this thesis is to develop an unbiased sampling approach for the TCLP testing of PV modules. The TCLP testing was concentrated only for the laminate part of the modules, as they are already existing recycling technologies for the frame and junction box components of PV modules. Four different sample removal methods have been applied to the laminates of five different module manufacturers: coring approach, cell-cut approach, strip-cut approach, and hybrid approach. These removed samples were sent to two different TCLP laboratories, and TCLP results were tested for repeatability within a lab and reproducibility between the labs. The pros and cons of each sample removal method have been explored and the influence of sample removal methods on the variability of TCLP results has been discussed. To reduce the variability of TCLP results to an acceptable level, additional improvements in the coring approach, the best of the four tested options, are still needed.
ContributorsLeslie, Joswin (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Kuitche, Joseph (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Distributed Renewable energy generators are now contributing a significant amount of energy into the energy grid. Consequently, reliability adequacy of such energy generators will depend on making accurate forecasts of energy produced by them. Power outputs of Solar PV systems depend on the stochastic variation of environmental factors (solar irradiance,

Distributed Renewable energy generators are now contributing a significant amount of energy into the energy grid. Consequently, reliability adequacy of such energy generators will depend on making accurate forecasts of energy produced by them. Power outputs of Solar PV systems depend on the stochastic variation of environmental factors (solar irradiance, ambient temperature & wind speed) and random mechanical failures/repairs. Monte Carlo Simulation which is typically used to model such problems becomes too computationally intensive leading to simplifying state-space assumptions. Multi-state models for power system reliability offer a higher flexibility in providing a description of system state evolution and an accurate representation of probability. In this study, Universal Generating Functions (UGF) were used to solve such combinatorial problems. 8 grid connected Solar PV systems were analyzed with a combined capacity of about 5MW located in a hot-dry climate (Arizona) and accuracy of 98% was achieved when validated with real-time data. An analytics framework is provided to grid operators and utilities to effectively forecast energy produced by distributed energy assets and in turn, develop strategies for effective Demand Response in times of increased share of renewable distributed energy assets in the grid. Second part of this thesis extends the environmental modelling approach to develop an aging test to be run in conjunction with an accelerated test of Solar PV modules. Accelerated Lifetime Testing procedures in the industry are used to determine the dominant failure modes which the product undergoes in the field, as well as predict the lifetime of the product. UV stressor is one of the ten stressors which a PV module undergoes in the field. UV exposure causes browning of modules leading to drop in Short Circuit Current. This thesis presents an environmental modelling approach for the hot-dry climate and extends it to develop an aging test methodology. This along with the accelerated tests would help achieve the goal of correlating field failures with accelerated tests and obtain acceleration factor. This knowledge would help predict PV module degradation in the field within 30% of the actual value and help in knowing the PV module lifetime accurately.
ContributorsKadloor, Nikhil (Author) / Kuitche, Joseph (Thesis advisor) / Pan, Rong (Thesis advisor) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2017