Publications

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Solar spectral data for all parts of the US is limited due in part to the high cost of commercial spectrometers. Solar spectral information is necessary for accurate photovoltaic (PV) performance forecasting, especially for large utility-scale PV installations. A low-cost solar spectral sensor would address the obstacles and needs. In this report, a novel low-cost, discrete- band sensor device, comprised of five narrow-band sensors, is described. The hardware is comprised of commercial-off-the-shelf components to keep the cost low. Data processing algorithms were developed and are being refined for robustness. PV module short-circuit current ( I sc ) prediction methods were developed based on interaction-terms regression methodology and spectrum reconstruction methodology for computing I sc . The results suggest the computed spectrum using the reconstruction method agreed well with the measured spectrum from the wide-band spectrometer (RMS error of 38.2 W/m 2 -nm). Further analysis of computed I sc found a close correspondence of 0.05 A RMS error. The goal is for ubiquitous adoption of the low-cost spectral sensor in solar PV and other applications such as weather forecasting.

This work investigates balance of systems (BOS) connector reliability from the perspective of arc fault risk. Accelerated tests were performed on connectors for future development of a reliability model. Thousands of hours of damp heat and atmospheric corrosion tests found BOS connectors to be resilient to corrosion-related degradation. A procedure was also developed to evaluate new and aged connectors for arc fault risk. The measurements show that arc fault risk is dependent on a combination of materials composition as well as design geometry. Thermal measurements as well as optical emission spectroscopy were also performed to further characterize the arc plasma. Together, the degradation model, arc fault risk assessment technique, and characterization methods can provide operators of photovoltaic installations information necessary to develop a data-driven plan for BOS connector maintenance as well as identify opportunities for arc fault prognostics.

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The solar spectrum varies with atmospheric conditions and composition, and can have significant impacts on the output power performance of each junction in a concentrating solar photovoltaic (CPV) system, with direct implications on the junction that is current-limiting. The effect of changing solar spectrum on CPV module power production has previously been characterized by various spectral performance parameters such as air mass (AM) for both single and multi-junction module technologies. However, examinations of outdoor test results have shown substantial uncertainty contributions by many of these parameters, including air mass, for the determination of projected power and energy production. Using spectral data obtained from outdoor spectrometers, with a spectral range of 336nm-1715nm, this investigation examines precipitable water (PW), aerosol and dust variability effects on incident spectral irradiance. This work then assesses air mass and other spectral performance parameters, including a new atmospheric component spectral factor (ACSF), to investigate iso-cell, stacked multijunction and single-junction c-Si module performance data directly with measured spectrum. This will then be used with MODTRAN5® to determine if spectral composition can account for daily and seasonal variability of the short-circuit current density Jsc and the maximum output power Pmp values. For precipitable water, current results show good correspondence between the modeled atmospheric component spectral factor and measured data with an average rms error of 0.013, for all three iso-cells tested during clear days over a one week time period. Results also suggest average variations in ACSF factors with respect to increasing precipitable water of 8.2%/cmH2O, 1.3%/cmH2O, 0.2%/cmH2O and 1.8%/cmH2O for GaInP, GaAs, Ge and c-Si cells, respectively at solar noon and an AM value of 1.0. For ozone, the GaInP cell had the greatest sensitivity to increasing ozone levels with an ACSF variation of 0.07%/cmO3. For the desert dust wind study, consistent ACSF behavior between all iso-cells and c-Si was found, with only significant reductions beyond 40mph.

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Accurate performance and reliability evaluation of utility-scale photovoltaic (PV) systems requires accountability of solar gain contributions. A novel solar gain utility-scale inverter model has been developed to characterize inverter efficiency with respect to solar resource, general ambient conditions and thermal system losses. A sensitivity analysis was performed to evaluate the robustness of the model based on four assumed material properties. This analysis revealed 22.9% modeled internal inverter temperature sensitivity to surface absorptivity, with significantly less sensitivity to other parameters studied, indicating the impact of proper surface coating material selection on solar thermal absorption. This analysis was applied to a large utility-scale PV plant, assessing performance data from twelve 500kW inverters, and environmental data from twelve respective meteorological test stations. An RMSE value of 6.1% was found between the model and measured inner inverter temperatures. The results also suggest a negative 3.6×10-4 [W/m2] -1 normalized inverter efficiency correspondence with solar gain heat adsorption across the twelve inverters for a one-day, clear-sky time period. © 2013 IEEE.