Publications

Hansen, Clifford H.; Riley, Daniel R.; Deline, Chris D.; Toor, Fatima T.; Stein, Joshua S.

Abstract not provided.

Stein, Joshua S.; Riley, Daniel R.; Lave, Matthew S.; Deline, Chris D.; Toor, Fatima T.; Hansen, Clifford H.

Abstract not provided.

Stein, Joshua S.; Riley, Daniel R.; Lave, Matthew S.; Deline, Chris D.; Toor, Fatima T.; Hansen, Clifford H.

Abstract not provided.

Stein, Joshua S.; Riley, Daniel R.; Lave, Matthew S.; Hansen, Clifford H.; Deline, Chris D.; Toor, Fatima T.

Abstract not provided.

Marion, Bill M.; MacAlpine, Sara M.; Deline, Chris D.; Asgharzadeh, Amir A.; Toor, Fatima T.; Riley, Daniel R.; Stein, Joshua S.; Hansen, Clifford H.

Abstract not provided.

Conference Record of the IEEE Photovoltaic Specialists Conference

Hansen, Clifford H.; Gooding, Renee L.; Guay, Nathan G.; Riley, Daniel R.; Kallickal, Johnson J.; Ellibee, Donald E.; Asgharzadeh, Amir A.; Marion, Bill M.; Toor, Fatima T.; Stein, Joshua S.

Abstract not provided.

Conference Record of the IEEE Photovoltaic Specialists Conference

Stein, Joshua S.; Riley, Daniel R.; Lave, Matthew S.; Hansen, Clifford H.; Deline, Chris D.; Toor, Fatima T.

Abstract not provided.

Hansen, Clifford H.; Riley, Daniel R.; Stein, Joshua S.

Abstract not provided.

Hansen, Clifford H.; Gooding, Renee L.; Guay, Nathan G.; Riley, Daniel R.; Kallickal, Johnson J.; Ellibee, Donald E.; Asgharzadeh, Amir A.; Marion, Bill M.; Toor, Fatima T.; Stein, Joshua S.

Abstract not provided.

Riley, Daniel R.; Hansen, Clifford H.; Stein, Joshua S.; Lave, Matthew S.; Kallickal, Johnson J.; Marion, Bill M.; Toor, Fatima T.

Abstract not provided.

Hansen, Clifford H.; Riley, Daniel R.

Abstract not provided.

Conference Record of the IEEE Photovoltaic Specialists Conference

King, Bruce H.; Hansen, Clifford H.; Riley, Daniel R.; Robinson, Charles D.; Pratt, Larry

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.

Stein, Joshua S.; Lave, Matthew S.; Riley, Daniel R.

Abstract not provided.

Riley, Daniel R.; Stein, Joshua S.

The Regional Test Centers are a group of several sites around the US for testing photovoltaic systems and components related to photovoltaic systems. The RTCs are managed by Sandia National Laboratories. The data collected by the RTCs must be transmitted to Sandia for storage, analysis, and reporting. This document describes the methods that transfer the data between remote sites and Sandia as well as data movement within Sandia’s network. The methods described are in force as of September, 2016.

IEEE Journal of Photovoltaics

Burton, Patrick D.; Hendrickson, Alex; Ulibarri, Stephen S.; Riley, Daniel R.; Boyson, William E.; King, Bruce H.

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°.

Riley, Daniel R.; Fleming, Jeffrey F.; Gallegos, Gerald R.

The Roof Asset Management Program (RAMP) is a DOE NNSA initiative to manage roof repairs and replacement at NNSA facilities. In some cases, installation of a photovoltaic system on new roofs may be possible and desired for financial reasons and to meet federal renewable energy goals. One method to quantify the financial benefits of PV systems is the payback period, or the length of time required for a PV system to generate energy value equivalent to the system's cost. Sandia Laboratories created a simple spreadsheet-based solar energy valuation tool for use by RAMP personnel to quickly evaluate the estimated payback period of prospective or installed photovoltaic systems.

King, Bruce H.; Hansen, Clifford H.; Riley, Daniel R.; Robinson, Charles D.; Pratt, Larry P.

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented comparisons of measurements and analysis results among laboratories, detailed procedures for determining model coefficients have not yet been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. Here we present a standard procedure for calibrating the SAPM using outdoor electrical and meteorological measurements. Analysis procedures are illustrated with data measured outdoors for a 36-cell silicon photovoltaic module.

King, Bruce H.; Hansen, Clifford H.; Riley, Daniel R.; Robinson, Charles D.; Pratt, Larry P.

Abstract not provided.

2015 IEEE 42nd Photovoltaic Specialist Conference, PVSC 2015

Driesse, Anton; Stein, Joshua S.; Riley, Daniel R.; Carmignani, Craig K.

Accurate photovoltaic system performance monitoring is critical for profitable long-term operation. Irradiance, temperature, power, current and voltage signals contain rapid fluctuations that are not observable by typical monitoring systems. Nevertheless these fluctuations can affect the accuracy of the data that are stored. We closely examine electrical signals in one operating PV system recorded at 2000 samples per second. Rapid fluctuations are analyzed, caused by line-frequency harmonics, anti-islanding detection, MPPT and others. The operation of alternate monitoring systems is simulated using a wide range of sampling intervals, archive intervals and filtering options to assess how these factors influence final data accuracy.

King, Bruce H.; Hansen, Clifford H.; Stein, Joshua S.; Riley, Daniel R.; Gonzalez, Sigifredo G.

The Characterizing Emerging Technologies project focuses on developing, improving and validating characterization methods for PV modules, inverters and embedded power electronics. Characterization methods and associated analysis techniques are at the heart of technology assessments and accurate component and system modeling. Outputs of the project include measurement and analysis procedures that industry can use to accurately model performance of PV system components, in order to better distinguish and understand the performance differences between competing products (module and inverters) and new component designs and technologies (e.g., new PV cell designs, inverter topologies, etc.).

Riley, Daniel R.

Abstract not provided.

Stein, Joshua S.; Hansen, Clifford H.; Riley, Daniel R.

Abstract not provided.

King, Bruce H.; Riley, Daniel R.; Robinson, Charles D.; Pratt, Larry P.

Abstract not provided.

Riley, Daniel R.

Abstract not provided.

Armijo, Kenneth M.; Yang, Benjamin B.; Riley, Daniel R.; Lavrova, Olga A.; Gonzalez, Sigifredo G.

Abstract not provided.