W.E. Boyson’s research while affiliated with Sandia National Laboratories and other places

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 ISC. Angular losses were significant at angles as low as 25°.

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.

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

Improvements in the methods used for photovoltaic (PV) system design, performance rating, and long-term monitoring are needed by the rapidly growing industry, as well as by the U.S. Department of Energy in evaluating progress by solar technology development initiatives. This paper describes an improved model for rating and monitoring PV array performance, discusses initial results from an outdoor laboratory designed to assist industry in optimizing system components and integration, and provides a brief discussion of the system performance metrics currently being used by the PV community