Building Applied Photovoltaics (BAPV) form an essential part of today's solar economy. This thesis is an effort to compare and understand the effect of fan cooling on the temperature of rooftop photovoltaic (PV) modules by comparing two side-by-side arrays (test array and control array) under identical ambient conditions of irradiance, air temperature, wind speed and wind direction. The lower operating temperature of PV modules due to fan operation mitigates array non uniformity and improves on performance. A crystalline silicon (c-Si) PV module has a light to electrical conversion efficiency of 14-20%. So on a cool sunny day with incident solar irradiance of 1000 W/m2, a PV module with 15% efficiency, will produce about only 150 watts. The rest of the energy is primarily lost in the form of heat. Heat extraction methods for BAPV systems may become increasingly higher in demand as the hot stagnant air underneath the array can be extracted to improve the array efficiency and the extracted low-temperature heat can also be used for residential space heating and water heating. Poly c-Si modules experience a negative temperature coefficient of power at about -0.5% /o C. A typical poly c-Si module would experience power loss due to elevation in temperature, which may be in the range of 25 to 30% for desert conditions such as that of Mesa, Arizona. This thesis investigates the effect of fan cooling on the previously developed thermal models at Arizona State University and on the performance of PV modules/arrays. Ambient conditions are continuously monitored and collected to calculate module temperature using the thermal model and to compare with actually measured temperature of individual modules. Including baseline analysis, the thesis has also looked into the effect of fan on the test array in three stages of 14 continuous days each. Multiple Thermal models are developed in order to identify the effect of fan cooling on performance and temperature uniformity. Although the fan did not prove to have much significant cooling effect on the system, but when combined with wind blocks it helped improve the thermal mismatch both under low and high wind speed conditions.

The photovoltaic (PV) modules are primarily characterized for their performance with respect to incident irradiance and operating temperature. This work deals with data collection and automation of data processing for the performance and thermal characterizations of PV modules. This is a two-part thesis: The primary part (part-1) deals with the software automation to generate performance matrix as per IEC 61853-1 standard using MPPT (maximum power point tracking) data at the module or system level; the secondary part (part-2) deals with the software automation to predict temperature of rooftop PV modules using the thermal model coefficients generated in the previous studies of the Photovoltaic Reliability Laboratory (PRL). Part 1: The IEC 61853-1 standard published in January 2011 specifies the generation of a target performance matrix of photovoltaic (PV) modules at various temperatures and irradiance levels. In a conventional method, this target matrix is generated using all the data points of several measured I-V curves and the translation procedures defined in IEC 60891 standard. In the proposed method, the target matrix is generated using only three commonly field measured parameters: Module temperature, Incident irradiance and MPPT (Maximum Peak Power Tracking) value. These parameters are loaded into the programmed Excel file and with a click of a button, IEC 61853-1 specified Pmppt matrix is displayed on the screen in about thirty seconds. Part 2: In a previous study at PRL, an extensive thermal model to predict operating temperature of rooftop PV modules was developed with a large number of empirical monthly coefficients for ambient temperature, irradiance and wind speed. Considering that there is large number of coefficients for each air gap of rooftop modules, it became necessary to automate the entire data processing to predict the temperature of rooftop PV modules at different air gaps. This part of the work was dedicated to automatically predict the temperature of rooftop modules at different air gaps for any month in a year just using only four input parameters: Month, Irradiance, Ambient temperature and Wind speed.

Photovoltaic (PV) modules appear to have three classifications of failure: Infant mortality, normal-life failure, and end-of-life failure. Little is known of the end-of-life failures experienced by PV modules due to their inherent longevity. Accelerated Life Testing (ALT) has been at the crux of this lifespan prediction; however, without naturally failing modules an accurate acceleration factor cannot be determined for use in ALT. By observing modules that have been aged in the field, a comparison can be made with modules undergoing accelerated testing. In this study an investigation on about 1900 aged (10-17 years) grid-tied PV modules installed in the desert climatic condition of Arizona was undertaken. The investigation was comprised of a check sheet that documented any visual defects and their severity, infrared (IR) scanning, and current-voltage (I-V) curve measurements. After data was collected on modules, an analysis was performed to classify the failure modes and to determine the annual performance degradation rates.

Thermal modeling and investigation into heat extraction methods for building-applied photovoltaic (BAPV) systems have become important for the industry in order to predict energy production and lower the cost per kilowatt-hour (kWh) of generating electricity from these types of systems. High operating temperatures have a direct impact on the performance of BAPV systems and can reduce power output by as much as 10 to 20%. The traditional method of minimizing the operating temperature of BAPV modules has been to include a suitable air gap for ventilation between the rooftop and the modules. There has been research done at Arizona State University (ASU) which investigates the optimum air gap spacing on sufficiently spaced (2-6 inch vertical; 2-inch lateral) modules of four columns. However, the thermal modeling of a large continuous array (with multiple modules of the same type and size and at the same air gap) had yet to be done at ASU prior to this project. In addition to the air gap effect analysis, the industry is exploring different ways of extracting the heat from PV modules including hybrid photovoltaic-thermal systems (PV/T). The goal of this project was to develop a thermal model for a small residential BAPV array consisting of 12 identical polycrystalline silicon modules at an air gap of 2.5 inches from the rooftop. The thermal model coefficients are empirically derived from a simulated field test setup at ASU and are presented in this thesis. Additionally, this project investigates the effects of cooling the array with a 40-Watt exhaust fan. The fan had negligible effect on power output or efficiency for this 2.5-inch air gap array, but provided slightly lower temperatures and better temperature uniformity across the array.