The texture or patterning of soil on PV surfaces may influence light capture at various angles of incidence (AOI). Accumulated soil can be considered a microshading element, which changes with respect to AOI. Laboratory deposition of simulated soil was used to prepare test coupons for simultaneous AOI and soiling loss experiments. A mixed solvent deposition technique was used to consistently deposit patterned test soils onto glass slides. Transmission decreased as soil loading and AOI increased. Dense aggregates significantly decreased transmission. However, highly dispersed particles are less prone to secondary scattering, improving overall light collection. In order to test AOI losses on relevant systems, uniform simulated soil coatings were applied to split reference cells to further examine this effect. The measured optical transmission and area coverage correlated closely to the observed I SC . Angular losses were significant at angles as low as 25°.

We present a method for measuring the series resistance of the PV module, string, or array that does not require measuring a full IV curve or meteorological data. Our method relies only on measurements of open circuit voltage and maximum power voltage and current, which can be readily obtained using standard PV monitoring equipment; measured short circuit current is not required. We validate the technique by adding fixed resistors to a PV circuit and demonstrating that the method can predict the added resistance. Relative prediction accuracy appears highest for smaller changes in resistance, with a systematic underestimation at larger resistances. Series resistance is shown to vary with irradiance levels with random errors below 1.5% standard deviation.

The objective of this paper was to determine if three different direct normal irradiance (DNI) models were sufficiently accurate to determine if concentrating solar power (CSP) plants could meet the utility electrical load. DNI data were measured at three different laboratories in the United States and compared with DNI calculated by three DNI models. In addition, utility electrical loading data were obtained for all three locations. The DNI models evaluated were: the Direct Insolation Simulation Code (DISC), DIRINT, and DIRINDEX. On an annual solar insolation (e.g. kW h/m(2)) basis, the accuracy of the DNI models at all three locations was within: 7% (DISC), 5% (DIRINT), and 3% (DIRINDEX). During the three highest electrical loading months at the three locations, the monthly accuracy varied from: 0% to 16% (DISC), 0% to 9% (DIRINT), and 0% to 8% (DIRINDEX). At one location different pyranometers were used to measure GHI, and the most expensive pyranometers did not improve the DNI model monthly accuracy. In lieu of actually measuring DNI, using the DIRINT model was felt to be sufficient for assessing whether to build a CSP plant at one location, but use of either the DIRINT or DIRINDEX models was felt to be marginal for the other two locations due to errors in modeling DNI for utility peak electrical loading days - especially for partly cloudy days. Published by Elsevier Ltd.

Sandia National Laboratories (Sandia) has observed an increased demand for high accuracy outdoor photovoltaic (PV) module characterization using Sandia's Photovoltaic Array Performance Model [1]. To meet this demand, Sandia entered into a competitively-bid agreement in May 2009 with TÜV Rheinland Photovoltaic Testing Laboratory (TÜV-PTL) to transfer Sandia's capability to fully characterize standard, commercial-scale PV modules. Sandia and TÜV-PTL worked closely on two round-robin experiments and months of subsequent work and discussions that resulted in module performance output calculations agreeing to within +/−2.5%.

The Sandia Array Performance Model (SAPM) [1] describes the power performance of photovoltaic (PV) modules under variable irradiance and temperature conditions. Model parameters are estimated by regressions involving measured module voltage and current, module and air temperature, and solar irradiance. Measurements are made under test conditions chosen to isolate subsets of parameters and which improve the quality of the regression estimates. Uncertainty in model parameters results from uncertainty in each measurement as well as from the number of measurements. Uncertainty in model parameters can be propagated through the model to determine its effect on model output. In this paper we summarize the process for estimating uncertainty in model parameters for flat-plate, crystalline silicon (cSi) modules from measurements, present example results, and illustrate the effect of parameter uncertainty on model output. Finally, we comment on how analysis of parameter uncertainty can inform model developers about the presence and impacts of model uncertainty.

In the last decade, c-Si module degradation rates of <1%/year have been reported. It is unclear if this degradation rate extends directly to the string level and what is the expected statistical spread of degradation rates. Nine photovoltaic (PV) arrays totaling nearly 100 kW at Standard Reporting Conditions are currently being used at Sandia National Laboratories (SNL) primarily for inverter testing. The measured power degradation of these arrays at the string level varied from no change over three years within measurement error to greater than 25% in three years. This paper outlines the methodology used to test the DC output, outlines analysis techniques used to evaluate the array performance, provides a current reliability assessment, presents the comparative data for up to five years of use and exposure, and discusses the methods used to track down the causes of unexpected string-level degradation.

The U.S. Department of Energy has supported development of the Solar Advisor Model (SAM) to provide a common platform for evaluation of the solar energy technologies being developed with the support of the Department. This report describes a detailed comparison of performance-model calculations within SAM to actual measured PV system performance in order to evaluate the ability of the models to accurately predict PV system energy production. This was accomplished by using measured meteorological and irradiance data as an input to the models, and then comparing model predictions of solar and PV system parameters to measured values from co-located PV arrays. The submodels within SAM which were examined include four radiation models, three module performance models, and an inverter model. The PVWATTS and PVMod models were also evaluated.

Computer simulation tools used to predict the energy production of photovoltaic systems are needed in order to make informed economic decisions. These tools require input parameters that characterize module performance under various operational and environmental conditions. Depending upon the complexity of the simulation model, the required input parameters can vary from the limited information found on labels affixed to photovoltaic modules to an extensive set of parameters. The required input parameters are normally obtained indoors using a solar simulator or flash tester, or measured outdoors under natural sunlight. This paper compares measured performance parameters for three photovoltaic modules tested outdoors at the National Institute of Standards and Technology (NIST) and Sandia National Laboratories (SNL). Two of the three modules were custom fabricated using monocrystalline and silicon film cells. The third, a commercially available module, utilized triple-junction amorphous silicon cells. The resulting data allow a comparison to be made between performance parameters measured at two laboratories with differing geographical locations and apparatus. This paper describes the apparatus used to collect the experimental data, test procedures utilized, and resulting performance parameters for each of the three modules. Using a computer simulation model, the impact that differences in measured parameters have on predicted energy production is quantified. Data presented for each module includes power output at standard rating conditions and the influence of incident angle, air mass, and module temperature on each module’s electrical performance. Measurements from the two laboratories are in excellent agreement. The power at standard rating conditions is within 1% for all three modules. Although the magnitude of the individual temperature coefficients varied as much as 17% between the two laboratories, the impact on predicted performance at various temperature levels was minimal, less than 2%. The influence of air mass on the performance of the three modules measured at the laboratories was in excellent agreement. The largest difference in measured results between the two laboratories was noted in the response of the modules to incident angles that exceed 75deg.

This paper deals with the technology transfer of a specific photovoltaic (PV) module characterization procedure from Sandia National Laboratories (Sandia) to Arizona State University Photovoltaic Testing Laboratory (ASU-PTL). This effort was intended to meet industry requests for independent module performance testing that provides the parameters (coefficients) required by the Sandia performance model. The objective of this work was two fold: (i) implement Sandia's experimental methodology at ASU-PTL to collect and analyze sunrise-to-sunset module performance data; and (ii) validate Sandia's performance model by comparing the modeled performance based on analysis of daylong data sets with performance determined using traditional standardized procedures. This paper reports lessons learned as well as the successful completion of this effort.

This document summarizes the equations and applications associated with the photovoltaic array performance model developed at Sandia National Laboratories over the last twelve years. Electrical, thermal, and optical characteristics for photovoltaic modules are included in the model, and the model is designed to use hourly solar resource and meteorological data. The versatility and accuracy of the model has been validated for flat-plate modules (all technologies) and for concentrator modules, as well as for large arrays of modules. Applications include system design and sizing, 'translation' of field performance measurements to standard reporting conditions, system performance optimization, and real-time comparison of measured versus expected system performance.

We study the universality of some recent observations concerning clear-day direct beam solar spectra, of possible relevance to a future standard for CPV testing. Ratios of direct beam to normal hemispherical solar spectra were measured at 12 sites around the world, and the first results of their comparisons are discussed here.

The successful commercialization of any new photovoltaic technology is difficult. Understanding the product's performance and aging characteristics is a prerequisite for the manufacturer. Amorphous-silicon thin-film modules are now in commercial production, and their market penetration is being limited to some degree by a lack of understanding of environmental influences that impact system design and operation. This paper summarizes our detailed performance characterization of multiple modules from four different manufacturers over several years of continuous outdoor exposure in Albuquerque, NM. Common stabilization characteristics have been observed for both tandem and triple-junction modules of recent vintage, and the influences of solar spectrum and seasonal (thermal) annealing have been clearly identified. Implications for system performance modeling are presented.

Accurate measurements of broadband (full spectrum) solar irradiance are fundamental to the successful implementation of solar power systems, both photovoltaic and solar thermal. Historically, acceptable measurement accuracy has been achieved using expensive thermopile-based pyranometers and pyrheliometers. The measurement limitations and sensitivities of these expensive radiometers are a topic that has been addressed elsewhere. This paper demonstrates how to achieve acceptable accuracy ({+-}3) in irradiance measurements using photodiodes or photovoltaic cells as sensors, and in addition to low-cost, have several operational advantages.

An electrical simulation model for photovoltaic cells, modules, and arrays has been developed that will be useful to a wide range of analysts in the photovoltaic industry. The Microsoft{reg_sign} Windows{trademark} based program can be used to analyze individual cells, to analyze the effects of cell mismatch or reverse bias(`hot spot`) heating in modules and to analyze the performance of large arrays of modules including bypass and blocking diodes. User defined statistical variance can be applied to the fundamental parameters used to simulate the cells and diodes. The model is most appropriate for cells that can be accurately modeled using a two-diode equivalent circuit. This paper describes the simulation program and illustrates its versatility with examples.