In recent years, solar photovoltaic (PV) industry has seen lots of improvements in technology and of growth in market with crystalline silicon PV modules being the most widely used technology. Plant inspections are gaining much importance to identify and quantitatively determine the impacts of various visual defects on performance. There are about 86 different types of defects found in the PV modules installed in various climates and most of them can be visually observed. However, a quantitative determination of impact or risk of each of identified defect on performance is challenging. Thus, it is utmost important to quantify the risk for each of the visual defects without any human subjectivity. The best way to quantify the risk of each defect is to perform current-voltage measurements of the defective modules installed in the plant but it requires disruption of plant operation, expensive measuring equipment and intensive human resources. One of the most riskiest and dominant visual defects is encapsulant browning which affects the PV module performance in the form of current degradation. The present study deals with developing an automated image processing tool which can address the issues of human subjectivity on browning level impacting performance. The image processing tool developed in this work can be directly used to quantify the impact of browning on performance without intrusively disconnecting the modules from the plant. In this work, the quantified browning level impact on performance has also been experimentally validated through a correlation study using short-circuit current and reflectance/transmittance measurements of browned PV modules retrieved from aged plants/systems installed in diverse climatic conditions. The primary goal of the image processing tool developed in this work is to determine the performance impact of encapsulant browning without interrupting the plant operation for I-V measurements. The use of image processing tool provides a single numerical value, called browning index (BI), which can accurately quantify browning levels on modules and also correlate with the performance and reflectance/transmittance parameters of the modules.

This is a two part thesis:

Part – I

This part of the thesis involves automation of statistical risk analysis of photovoltaic (PV) power plants. Statistical risk analysis on the field observed defects/failures in the PV power plants is usually carried out using a combination of several manual methods which are often laborious, time consuming and prone to human errors. In order to mitigate these issues, an automated statistical risk analysis (FMECA) is necessary. The automation developed and presented in this project generates about 20 different reliability risk plots in about 3-4 minutes without the need of several manual labor hours traditionally spent for these analyses. The primary focus of this project is to automatically generate Risk Priority Number (RPN) for each defect/failure based on two Excel spreadsheets: Defect spreadsheet; Degradation rate spreadsheet. Automation involves two major programs – one to calculate Global RPN (Sum of Performance RPN and Safety RPN) and the other to find the correlation of defects with I-V parameters’ degradations. Based on the generated RPN and other reliability plots, warranty claims for material defect and degradation rate may be made by the system owners.

Part – II

This part of the thesis involves the evaluation of Module Level Power Electronics (MLPE) which are commercially available and used by the industry. Reliability evaluations of any product typically involve pre-characterizations, many different accelerated stress tests and post-characterizations. Due to time constraints, this part of the project was limited to only pre-characterizations of about 100 MLPE units commercially available from 5 different manufacturers. Pre-characterizations involve testing MLPE units for rated efficiency, CEC efficiency, power factor and Harmonics (Vthd (%) and Ithd (%)). The pre-characterization test results can be used to validate manufacturer claims and to evaluate the product for compliance certification test standards. Pre-characterization results were compared for all MLPE units individually for all tested parameters listed above. The accelerated stress tests are ongoing and are not presented in this thesis. Based on the pre-characterizations presented in this report and post-characterizations performed after the stress tests, the pass/fail and time-to-failure analyses can be carried out by future researchers.

This study evaluates two 16 year old photovoltaic power (PV) plants to ascertain degradation rates and various failure modes which occur in a "hot-dry" climate. The data obtained from this study can be used by module manufacturers in determining the warranty limits of their modules and also by banks, investors, project developers and users in determining appropriate financing or decommissioning models. In addition, the data obtained in this study will be helpful in selecting appropriate accelerated stress tests which would replicate the field failures for the new modules and would predict the lifetime for new PV modules. The two power plants referred to as Site 4A and -4B with (1512 modules each) were initially installed on a single axis tracking system in Gilbert, Arizona for the first seven years and have been operating at their current location in Mesa, Arizona for the last nine years at fixed horizontal tilt Both sites experience hot-dry desert climate. Average degradation rate is 0.85%/year for the best modules and 1.1%/year for all the modules (excluding the safety failed modules). Primary safety failure mode is the backsheet delamination though it is small (less than 1.7%). Primary degradation mode and reliability failure mode may potentially be attributed to encapsulant browning leading to transmittance/current loss and thermo-mechanical solder bond fatigue (cell-ribbon and ribbon-ribbon) leading to series resistance increase. Average soiling loss of horizontal tilt based modules is 11.1%. About 0.5-1.7% of the modules qualify for the safety returns under the typical 20/20 warranty terms, 73-76% of the modules qualify for the warranty claims under the typical 20/20 power warranty terms and 24-26% of the modules are meeting the typical 20/20 power warranty terms.

This study evaluates two photovoltaic (PV) power plants based on electrical performance measurements, diode checks, visual inspections and infrared scanning. The purpose of this study is to measure degradation rates of performance parameters (Pmax, Isc, Voc, Vmax, Imax and FF) and to identify the failure modes in a "hot-dry desert" climatic condition along with quantitative determination of safety failure rates and reliability failure rates. The data obtained from this study can be used by module manufacturers in determining the warranty limits of their modules and also by banks, investors, project developers and users in determining appropriate financing or decommissioning models. In addition, the data obtained in this study will be helpful in selecting appropriate accelerated stress tests which would replicate the field failures for the new modules and would predict the lifetime for new PV modules. The study was conducted at two, single axis tracking monocrystalline silicon (c-Si) power plants, Site 3 and Site 4c of Salt River Project (SRP). The Site 3 power plant is located in Glendale, Arizona and the Site 4c power plant is located in Mesa, Arizona both considered a "hot-dry" field condition. The Site 3 power plant has 2,352 modules (named as Model-G) which was rated at 250 kW DC output. The mean and median degradation of these 12 years old modules are 0.95%/year and 0.96%/year, respectively. The major cause of degradation found in Site 3 is due to high series resistance (potentially due to solder-bond thermo-mechanical fatigue) and the failure mode is ribbon-ribbon solder bond failure/breakage. The Site 4c power plant has 1,280 modules (named as Model-H) which provide 243 kW DC output. The mean and median degradation of these 4 years old modules are 0.96%/year and 1%/year, respectively. At Site 4c, practically, none of the module failures are observed. The average soiling loss is 6.9% in Site 3 and 5.5% in Site 4c. The difference in soiling level is attributed to the rural and urban surroundings of these two power plants.