This is a two-part thesis. Part 1 presents the seasonal and tilt angle dependence of soiling loss factor of photovoltaic (PV) modules over two years for Mesa, Arizona (a desert climatic condition). Part 2 presents the development of an indoor artificial soil deposition chamber replicating natural dew cycle. Several environmental factors affect the performance of PV systems including soiling. Soiling on PV modules results in a decrease of sunlight reaching the solar cell, thereby reducing the current and power output. Dust particles, air pollution particles, pollen, bird droppings and other industrial airborne particles are some natural sources that cause soiling. The dust particles vary from one location to the other in terms of particle size, color, and chemical composition. The thickness and properties of the soil layer determine the optical path of light through the soil/glass interface. Soil accumulation on the glass surface is also influenced by environmental factors such as dew, wind speeds and rainfall. Studies have shown that soil deposition is closely related to tilt angle and exposure period before a rain event. The first part of this thesis analyzes the reduction in irradiance transmitted to a solar cell through the air/soil/glass in comparison to a clean cell (air/glass interface). A time series representation is used to compare seasonal soiling loss factors for two consecutive years (2014-2016). The effect of tilt angle and rain events on these losses are extensively analyzed. Since soiling is a significant field issue, there is a growing need to address the problem, and several companies have come up with solutions such as anti-soiling coatings, automated cleaning systems etc. To test and validate the effectiveness of these anti-soiling coating technologies, various research institutes around the world are working on the design and development of artificial indoor soiling chambers to replicate the natural process in the field. The second part of this thesis work deals with the design and development of an indoor artificial soiling chamber that replicates natural soil deposition process in the field.

The primary goal of this thesis work is to determine the activation energy for encapsulant browning reaction of photovoltaic (PV) modules using outdoor field degradation data and indoor accelerated degradation data. For the outdoor field data, six PV modules fielded in Arizona (hot climate) over 21 years and four PV modules fielded in New York (cold climate) over 18 years have been analyzed. All the ten modules were manufactured by the same manufacturer with glass/EVA/cell/EVA/back sheet construction. The activation energy for the encapsulant browning is calculated using the degradation rates of short-circuit current (Isc, the response parameter), weather data (temperature, humidity, and UV, the stress parameters) and different empirical rate models such as Arrhenius, Peck, Klinger and modified Peck models. For the indoor accelerated data, three sets of mini-modules with the same construction/manufacturer as that of the outdoor fielded modules were subjected indoor accelerated weathering stress and the test data were analyzed. The indoor accelerated test was carried out in a weathering chamber at the chamber temperature of 20°C, chamber relative humidity of 65%, and irradiance of 1 W/m2 at 340nm using a xenon arc lamp. Typically, to obtain activation energy, the test samples are stressed at two (or more) temperatures in two (or more) chambers. However, in this work, it has been attempted to do the acceleration testing of eight mini-modules at multiple temperatures using a single chamber. Multiple temperatures in a single chamber were obtained using thermal insulators on the back of the mini-modules. Depending on the thickness of the thermal insulators with constant solar gain from the xenon lamp, different temperatures on the test samples were achieved using a single weathering chamber. The Isc loss and temperature of the mini-modules were continuously monitored using a data logger. Also, the mini-modules were taken out every two weeks and various characterization tests such as IV, QE, UV fluorescence and reflectance were carried out. Activation energy from the indoor accelerated tests was calculated using the short circuit current degradation rate and operating temperatures of the mini-modules. The activation energy for the encapsulant browning obtained from the outdoor field data and the indoor accelerated data are compared and analyzed in this work.

As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV) power plants is presented in two-part thesis. The first part of the thesis deals with the defect analysis and the second part of the thesis deals with the statistical degradation rate analysis. In the first part, a detailed analysis on the performance or financial risk related to each defect found in multiple PV power plants across various climatic regions of the USA is presented by assigning a risk priority number (RPN). The RPN for all the defects in each PV plant is determined based on two databases: degradation rate database; defect rate database. In this analysis it is determined that the RPN for each plant is dictated by the technology type (crystalline silicon or thin-film), climate and age. The PV modules aging between 3 and 19 years in four different climates of hot-dry, hot-humid, cold-dry and temperate are investigated in this study.

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.

The deposition of airborne dust, especially in desert conditions, is very problematic as it leads to significant loss of power of photovoltaic (PV) modules on a daily basis during the dry period. As such, PV testing laboratories around the world have been trying to set up soil deposition stations to artificially deposit soil layers and to simulate outdoor soiling conditions in an accelerated manner. This thesis is a part of a twin thesis. The first thesis, authored by Shanmukha Mantha, is associated with the designing of an artificial soiling station. The second thesis (this thesis), authored by Darshan Choudhary, is associated with the characterization of the deposited soil layers. The soil layers deposited on glass coupons and one-cell laminates are characterized and presented in this thesis. This thesis focuses on the characterizations of the soil layers obtained in several soiling cycles using various techniques including current-voltage (I-V), quantum efficiency (QE), compositional analysis and optical profilometry. The I-V characterization was carried out to determine the impact of soil layer on current and other performance parameters of PV devices. The QE characterization was carried out to determine the impact of wavelength dependent influence of soil type and thickness on the QE curves. The soil type was determined using the compositional analysis. The compositional data of the soil is critical to determine the adhesion properties of the soil layers on the surface of PV modules. The optical profilometry was obtained to determine the particle size and distribution. The soil layers deposited using two different deposition techniques were characterized. The two deposition techniques are designated as “dew” technique and “humidity” technique. For the same deposition time, the humidity method was determined to deposit the soil layer at lower rates as compared to the dew method. Two types of deposited soil layers were characterized. The first type layer was deposited using a reference soil called Arizona (AZ) dust. The second type layer was deposited using the soil which was collected from the surface of the modules installed outdoor in Arizona. The density of the layers deposited using the surface collected soil was determined to be lower than AZ dust based layers for the same number of deposition cycles.

Utility scale solar energy is generated by photovoltaic (PV) cell arrays, which are often deployed in remote areas. A PV array monitoring system is considered where smart sensors are attached to the PV modules and transmit data to a monitoring station through wireless links. These smart monitoring devices may be used for fault detection and management of connection topologies. In this thesis, a compact hardware simulator of the smart PV array monitoring system is described. The voltage, current, irradiance, and temperature of each PV module are monitored and the status of each panel along with all data is transmitted to a mobile device. LabVIEW and Arduino board programs have been developed to display and visualize the monitoring data from all sensors. All data is saved on servers and mobile devices and desktops can easily access analytics from anywhere. Various PV array conditions including shading, faults, and loading are simulated and demonstrated.

Additionally, Electrical mismatch between modules in a PV array due to partial shading causes energy losses beyond the shaded module, as unshaded modules are forced to operate away from their maximum power point in order to compensate for the shading. An irradiance estimation algorithm is presented for use in a mismatch mitigation system. Irradiance is estimated using measurements of module voltage, current, and back surface temperature. These estimates may be used to optimize an array’s electrical configuration and reduce the mismatch losses caused by partial shading. Propagation of error in the estimation is examined; it is found that accuracy is sufficient for use in the proposed mismatch mitigation application.

In the past 10 to 15 years, there has been a tremendous increase in the amount of photovoltaic (PV) modules being both manufactured and installed in the field. Power plants in the hundreds of megawatts are continuously being turned online as the world turns toward greener and sustainable energy. Due to this fact and to calculate LCOE (levelized cost of energy), it is understandably becoming more important to comprehend the behavior of these systems as a whole by calculating two key data: the rate at which modules are degrading in the field; the trend (linear or nonlinear) in which the degradation is occurring. As opposed to periodical in field intrusive current-voltage (I-V) measurements, non-intrusive measurements are preferable to obtain these two key data since owners do not want to lose money by turning their systems off, as well as safety and breach of installer warranty terms. In order to understand the degradation behavior of PV systems, there is a need for highly accurate performance modeling. In this thesis 39 commercial PV power plants from the hot-dry climate of Arizona are analyzed to develop an understanding on the rate and trend of degradation seen by crystalline silicon PV modules. A total of three degradation rates were calculated for each power plant based on three methods: Performance Ratio (PR), Performance Index (PI), and raw kilowatt-hour. These methods were validated from in field I-V measurements obtained by Arizona State University Photovoltaic Reliability Lab (ASU-PRL). With the use of highly accurate performance models, the generated degradation rates may be used by the system owners to claim a warranty from PV module manufactures or other responsible parties.

Photovoltaic (PV) module degradation is a well-known issue, however understanding the mechanistic pathways in which modules degrade is still a major task for the PV industry. In order to study the mechanisms responsible for PV module degradation, the effects of these degradation mechanisms must be quantitatively measured to determine the severity of each degradation mode. In this thesis multiple modules from three climate zones (Arizona, California and Colorado) were investigated for a single module glass/polymer construction (Siemens M55) to determine the degree to which they had degraded, and the main factors that contributed to that degradation. To explain the loss in power, various nondestructive and destructive techniques were used to indicate possible causes of loss in performance. This is a two-part thesis. Part 1 presents non-destructive test results and analysis and Part 2 presents destructive test results and analysis.

This is a two-part thesis.

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.

This is a two-part thesis:

Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the lower will be the photovoltaic (PV) module performance. Our research group has already reported the AOI investigation for cleaned modules of five different technologies with air/glass interface. However, the modules that are installed in the field would invariably develop a soil layer with varying thickness depending on the site condition, rainfall and tilt angle. The soiled module will have the air/soil/glass interface rather than air/glass interface. This study investigates the AOI variations on soiled modules of five different PV technologies. It is demonstrated that AOI effect is inversely proportional to the soil density. In other words, the power or current loss between clean and soiled modules would be much higher at a higher AOI than at a lower AOI leading to excessive energy production loss of soiled modules on cloudy days, early morning hours and late afternoon hours. Similarly, the spectral influence of soil on the performance of the module was investigated through reflectance and transmittance measurements. It was observed that the reflectance and transmittances losses vary linearly with soil density variation and the 600-700 nm band was identified as an ideal band for soil density measurements.

Part 2 of this thesis performs statistical risk analysis for a power plant through FMECA (Failure Mode, Effect, and Criticality Analysis) based on non-destructive field techniques and count data of the failure modes. Risk Priority Number is used for the grading guideline for criticality analysis. The analysis was done on a 19-year-old power plant in cold-dry climate to identify the most dominant failure and degradation modes. In addition, a comparison study was done on the current power plant (framed) along with another 18-year-old (frameless) from the same climate zone to understand the failure modes for cold-dry climatic condition.

To increase the deployment of photovoltaic (PV) systems, a higher level of performance for PV modules should be sought. Soiling, or dust accumulation on the PV modules, is one of the conditions that negatively affect the performance of the PV modules by reducing the light incident onto the surface of the PV module. This thesis presents two studies that focus on investigating the soiling effect on the performance of the PV modules installed in Metro Phoenix area.

The first study was conducted to investigate the optimum cleaning frequency for cleaning PV modules installed in Mesa, AZ. By monitoring the soiling loss of PV modules mounted on a mock rooftop at ASU-PRL, a detailed soiling modeling was obtained. Same setup was also used for other soiling-related investigations like studying the effect of soiling density on angle of incidence (AOI) dependence, the climatological relevance (CR) to soiling, and spatial variation of the soiling loss. During the first dry season (May to June), the daily soiling rate was found as -0.061% for 20o tilted modules. Based on the obtained soiling rate, cleaning PV modules, when the soiling is just due to dust on 20o tilted residential arrays, was found economically not justifiable.

The second study focuses on evaluating the soiling loss in different locations of Metro Phoenix area of Arizona. The main goal behind the second study was to validate the daily soiling rate obtained from the mock rooftop setup in the first part of this thesis. By collaborating with local solar panel cleaning companies, soiling data for six residential systems in 5 different cities in and around Phoenix was collected, processed, and analyzed. The range of daily soiling rate in the Phoenix area was found as -0.057% to -0.085% for 13-28o tilted arrays. The soiling rate found in the first part of the thesis (-0.061%) for 20o tilted array, was validated since it falls within the range obtained from the second part of the thesis.