Sandia’s research in PV performance and reliability focuses on improving the ability of PV systems to consistently meet intended performance metrics under specific environmental conditions. Reliability testing at Sandia includes five primary tasks:
- Predictive model development
- Real-time reliability studies
- Accelerated and diagnostic testing
- Industry outreach and standards support
- Mitigation and failure analysis efforts
The lab uses field operations and maintenance (O&M), degradation studies, failure data from integrators and utility partners, and detailed statistical models to develop systems-level models. These models can be applied by researchers and industry to help determine ways to overcome reliability issues and accelerate high penetration of PV technologies. Sandia also conducts real-time degradation studies such as Accelerated Life Testing and Failure Modes and Effects Analysis. Sandia has also partnered with a utility to create a data-driven Reliability Block Diagram and gather O&M data to generate failure statistics. This input contributes to the Labs’ PV Reliability and Availability Predictive Model (PVRAM). Some key activities include the PV Performance Modeling Collaborative, Sandia PV Array Performance Model, the U.S. Department of Energy’s Regional Test Centers, and PV System Modeling and Analysis.
Bifacial PV technologies are developing rapidly and are predicted to be a dominant PV technology very soon. Current bifacial PV system designs are based on monofacial concepts and may not be optimized. Existing performance models are only beginning to be able to predict performance of very simple bifacial systems, yet they still lack many important details. This project will (1) develop and validate advanced bifacial performance models capable of simulating a wide range of system designs, (2) perform designoptimization studies of a range of bifacial system types utilizing high performance computing resources and tools available at Sandia and NREL, (3) deploy and monitor typical bifacial systems for model validation, and (4) work with industry to improve standards and best practices in the areas of module and system rating, capacity testing, site prospecting and safety.
Joshua S. Stein, PhD, Principal Investigator
- Rodríguez-Gallegos, C. D., H. Liu, O. Gandhi, J. P. Singh, V. Krishnamurthy, A. Kumar, J. S. Stein, S. Wang, L. Li, T. Reindl and I. M. Peters (2020). “Global techno-economic performance of bifacial and tracking PV systems.” Joule. DOI: 10.1016/j.joule.2020.05.005.
- Deline, C., S. A. Pelaez, S. MacAlpine and C. Olalla (2020). “Estimating and parameterizing mismatch power loss in bifacial photovoltaic systems.” Progress in Photovoltaics. https://doi.org/10.1002/pip.3259
- Pelaez, S. A., C. Deline, S. MacAlpine, B. Marion, J. S. Stein and R. K. Kostuk (2019). “Comparison of bifacial solar irradiance model predictions with field validation ” Journal of Photovoltaics 9(1): 82-88, DOI: 10.1109/JPHOTOV.2018.2877000.
- Liang, T. S., M. Pravettoni, C. Deline, J. S. Stein, R. Kopecek, J. P. Singh, W. Luo, Y. Wang, A. G. Aberle and Y. S. Khoo (2019). “A review of crystalline silicon bifacial photovoltaic performance characterisation and simulation.” Energy & Environmental Science 12(1): 116-148. DOI: https://doi.org/10.1039/C8EE02184H
- Ayala Pelaez, S., C. Deline, P. Greenberg, J. S. Stein and R. K. Kostuk (2019). “Model and Validation of Single-Axis Tracking with Bifacial PV.” Journal of Photovoltaics 9: 715-721. DOI: 10.1109/JPHOTOV.2019.2892872
bifacial_radiance: Contains a series of Python wrapper functions from NREL to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance.
bifacialvf: A self-contained view factor (or configuration factor) model from NREL which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row.
3Dbifacial_VF: Matlab functions and example scripts to model rearside irradiance using a 3D view factor approach. Able to simulate variations across individual modules in an array. Code is available here: Sandia_Bifacial-PV_View-Factor-code_0.2-1.zip (428 downloads)
Bifacial Workshops (click on links to access information and presentations)
|2018||6th Bifacial (BiFi) Workshop||Denver, USA||Workshop webpage|
This core capability includes development, implementation, and validation of new performance submodels in the areas of module thermal behavior, dynamic soiling, performance degradation and stakeholder engagement through the PV Performance Modeling Collaborative (PVPMC) and IEA PVPS Task 13. PVPMC brings together researchers from academia and industry to share the latest ideas on how to accurately model and predict the performance of PV systems in the field. The PVPMC has hosted 13 workshops in four countries, hosts a website (https://pvpmc.sandia.org), and offers open-source software to users worldwide.
Joshua S. Stein, PhD
Recent Publications and Software:
- Prilliman, M., J. S. Stein and D. Riley (2020). “Transient Weighted Moving Average Model of Photovoltaic Module Back-Surface Temperature.” Journal of Photovoltaics doi: 10.1109/JPHOTOV.2020.2992351.
- Driesse, A. and J. S. Stein (2020). From IEC 61853 power measurements to PV system simulations, Sandia National Laboratories. SAND2020-3877.
- Holmgren, W. F., C. W. Hansen and M. A. Mikofski (2018). “pvlib python: a python package for modeling solar energy systems ” The Journal of Open Source Software 3(29): 3.
- pvlib-python GitHub repository: https://github.com/pvlib/pvlib-python
- MATLAB_PV_LIB GitHub repository: https://github.com/sandialabs/MATLAB_PV_LIB
Bruce King, Principal Investigator
National Renewable Energy Lab (NREL)
Florida Solar Energy Center (FSEC)
University of Nevada Las Vegas (UNLV)
- J. Stein, C. Robinson, B. King, C. Deline, S. Rummel, B. Sekulic: “PV Lifetime Project: Measuring PV Module Performance Degradation: 2018 Indoor Flash Testing Results,” 7th WCPEC, 2018.
- B. H King and C. D. Robinson, “Differential Analysis of the Angle of Incidence Response of Utility-Grade PV Modules,” 46th IEEE-PVSC, Chicago, IL, 2019.
- M. Theristis, A. Livera, C. B. Jones, G. Makrides, G. E. Georghiou, and J. S. Stein, “Non-linear photovoltaic degradation rates: modeling and comparison against conventional methods,” IEEE Journal of Photovoltaics, 2020.
Recent projections indicate the world will have 1 trillion watts of installed photovoltaic (PV) capacity within the next four years, with significant growth across diverse climates and geographic regions. Yet much remains unknown about the specific variables that contribute to the long-term performance and reliability of PV systems in different operating environments. The “PhotoVoltaic Collaborative to Advance Multiclimate Energy Research” project or PV CAMPER, represents a global research platform dedicated to cross-climate research and to building a repository of high-fidelity meteorological and PV performance data. To date, the organization has 11members and 17 field sites representing the planet’s main climate zones.
Learn more at the PV CAMPER webpage.
Laurie Burnham, Principal Investigator
Anhalt University of Applied Sciences
Fraunhofer Center for Silicon Photovoltaics
Institut de Recherche en Energie Solaire et Energies Nouvelles
Korea Institute of Energy Research
Korea Testing Laboratory
National University of Singapore
Qatar Environment and Energy Institute
Korea Testing Laboratory
Universidade Federal de Santa Catarina
- Braga, M., de Oliveira, K.A., Burnham, L., Dittmann, S., Betts, T., Rodriguez-Gallegos, C.D., Reindl, T., Ruther, R. Over-irradiance events: preliminary results from a global study, IEEE 47th PVSC, June 15-August 21, 2020, virtual meeting, 7pp.
- Braga, M., de Oliveira, K.A., Burnham, L., Dittmann, S., Gottschalg, R., Figgis, B. Benlarabi, A., Betts, T., Reindl, T., Ph, S., Choi, J., Kim, K. and Ruther, R. Comparative analysis of module temperature measurements and estimation methods for various climate zones across the globe, 37th EU PVSEC 2020, (in prep.)
- Burnham, L., Dittmann, S., Gottschlag, R., Benlarabi, A., Figgis, B., Reindl, T., Oh, S., Kim, K., Choi, J., Ruther, R., Fell, C. Photovoltaic Collaborative to Advance Multi-climate Energy and Performance Research (PV CAMPER), poster, 36th EUPVSEC Conference, Marseille, France, Sept, 2019.
- Dittmann, S., Sanchez, H., Burnham, L., Gottschalg, R., Oh, S., Benlarabi, A., Figgis, B., Abdallah, A., Rodriguez, C., Ruther, R., Fell, C. Analysis of albedo measurements (plane-of-array and horizontal) at multiple sites worldwide, Proc. 36th EUPVSEC Conference, Marseille, France, Sept, 2019: 188-1390.
Implement advanced PV system monitoring down to the string and module level and quantify the value different monitoring techniques have within a PV system.
- Implement advanced algorithms, machine learning
- Monitoring to provide diagnostics
- Monitoring to provide prognostics
- Quantify value system has in terms of LCOE
Joshua S. Stein, PhD
Name: Joseph Walters, Univ. of Central FL
- Walters, J., H. Seigneur, E. Schneller, M. Matam and M. Hopwood (2019). Experimental Methods to Replicate Power Loss of PV Modules in the Field for the Purpose of Fault Detection Algorithm Development. 46th IEEE PV Specialist Conference. Chicago, IL.
- Matam, M. and J. Walters (2019). Data-integrity checks and balances in monitoring of solar PV system. 46th IEEE PV Specialists Conference. Chicago, IL.
Jones, C. B. and C. W. Hansen (2019). Single Diode Parameter Extraction from In-Field Photovoltaic I-V Curves on a Single Board Computer. 46th IEEE PV Specialists Conference. Chicago, IL.
The Regional Test Center (RTC) program supports a network of field sites across the US that enable cross-climate performance and reliability research as well as product validation.
Learn more at the Regional Test Centers website.
With the rapid growth of solar across northern regions, the impact of snow shading on modules is a growing concern. Published estimates of energy losses attributable to snow range from 1 to 12 percent annually, with monthly losses as high as 100 percent, depending on location and weather conditions; in addition, snow creates excessive and uneven stress on modules, cells and systems, the long-term impact of which is unknown.
This project aims to increase solar performance in northern regions of the US by identifying the multiple contributors to snow losses; modifying predictive models to more accurately reflect those contributors; and proposing mitigation strategies that boost both performance and reliability. Ultimately, this project aims to further the adoption, integration and optimal operation of the nation’s solar resources.
To learn more, visit the Snow webpage.
Laurie Burnham, Principal Investigator
Michigan Technical University
University of Alaska, Fairbanks
University of Michigan
- Braid, J., Riley, D., Pearce, J. and Burnham, L. Image Analysis Method for Quantifying Snow Losses on PV Systems, IEEE 47th PVSC, June 15-August 21 virtual meeting; 7pp.
- Burnham, L., Riley, D., Walker, B. and Pearce, J. Electroluminescent Imaging of Modules Exposed to Snow and Ice Loading: a Preliminary Analysis. 2019 Photovoltaic Reliability Workshop, Denver CO.
- Burnham, L., Riley, D., Walker, B., and Pearce, J. Performance of Bifacial Photovoltaic Modules on a Dual-Axis Tracker in a High-Latitude, High-Albedo Environment, Proc. IEEE PVSC-46 Conference, Chicago, IL, 8pp.
- Riley, D., Burnham, L., Walker, B. and Pearce, J. Differences in Snow Shedding in Photovoltaic Systems with Framed and Frameless Modules, Proc. IEEE PVSC-46 Conference, Chicago, IL, 4pp.