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 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.
The Snow as a Factor in Photovoltaic Performance and Reliability project aims to increase solar performance in regions of the US that regularly experience below-freezing precipitation 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.
Our specific research objectives are to:
- Quantify PV snow losses across multiple locations, module technologies and system configurations
- Identify topological and other component features that either impede or accelerate snow-shedding
- Develop advanced snow models, which include such variables as adhesion and surface-roughness measurements, for more accurate estimates of snow shedding
- Identify and mitigate reliability issues specific to snow and ice adhesion
Our investigation zeroes in on the following research areas, all of which are focused on increasing the performance and reliability of photovoltaic (PV) systems in snowy environments.
1) quantify actual snow losses across multiple locations and technologies
2) identify system parameters that minimize snow losses
3) develop an economic baseline against which various mitigation options can be compared.
A core focus of our work is to collect high-frequency images of snow-shedding for multiple PV systems, correlated with module/cell types, surface characteristics, frame and rack architectures, module angles, and meteorological data.
Sandia is collecting data from experimental systems that will inform and improve the accuracy of snow models. Variables of interest to the team include module architecture and system-design parameters that are not considered in published models.
Extreme weather events (record-breaking snowfall, low and extreme-swings in temperature and ferocious hail storms) that result in visible damage are well-documented; virtually unknown is the long-term impact of such events on solar-cell integrity and module reliability. This research activity will establish baseline and longitudinal data key to understanding long-term patterns of cell cracking.
The research objective here is to identify modifications in module and system design that result in accelerated snow shedding from PV arrays. A major focus of our research is 1) the development of snow-phobic coatings that are demonstrated to reduce snow losses and 2) the identification of components and other parameters, such as design specifics, that result in quantitative gains in performance over standard PV installations.
Field research for this project is currently taking place at the following sites:
- Michigan Technical University in Houghton, MI (N 47°, W 88°)
- University of Michigan, Ann Arbor, MI (N 42°, W84°)
- University of Alaska, Fairbanks, AK (N 64°, W147°)
- Willow Solar Farm in Willow, AK (N 62°, W150°)
Value to the US Solar Sector
Systems optimized for snowy climates will generate more electricity, lowering the levelized cost of energy (LCOE).
2. Lifetime Performance Modeling–
Increasing the accuracy of snow-loss models translates into more accurate LCOE calculations, which helps expand solar markets.
3. Resource Availability/Energy/Resilience–
Systems that shed snow quickly make more energy available to the grid, which increases grid resilience in the aftermath of severe storms.
4. Module and System Reliability–
Identification and mitigation of design weaknesses that contribute to snow and ice buildup leads to more robust and productive systems.
5. Grid Stability–
Predictive modeling of snow shedding increases the accuracy of solar-forecasting tools and allows electric utilities to plan for sudden oscillations in power.
Sandia welcomes industry partners willing to share data, provide sites and technologies for evaluation, and share field observations and experiences. Prospective partners should contact Laurie Burnham.
Led by Sandia National Lab, this multi-institutional project includes partnerships with Michigan Tech, University of Alaska, Fairbanks and the University of Michigan.
Laurie Burnham, Lead Investigator
Sandia National Laboratories
Daniel Riley, Research Engineer
Sandia National Laboratories
Thushara Gunda, Engineer/Data Scientist
Sandia National Laboratories
Richard Witte Professor of Materials Science and Engineering
Professor, Department of Electrical,Computer Engineering
Director: Michigan Tech Open Sustainability Technology Lab
Michigan Technological University
Associate Professor of Materials Science and Engineering
Chemical Engineering, and Macromolecular Science and Engineering
University of Michigan
Research Assistant Professor
Director, Solar Technologies Program
Director, Data Collection, Analysis Program
Alaska Center for Energy and Power (ACEP)
University of Alaska Fairbanks (UAF)
- Andrews, R. W., A. Pollard, J. M. Pearce, “The Effects of Snowfall on Solar Photovoltaic Performance, ” Solar Energy 92, (2013):8497. open access
- Andrews, R. W., A. Pollard, J. M. Pearce, “A new method to determine the effects of hydrodynamic surface coatings on the snow shedding effectiveness of solar photovoltaic modules,” Solar Energy Materials and Solar Cells 113 (2013): 71–78. open access
- Andrews, R. W. and J. M. Pearce. “Prediction of energy effects on photovoltaic systems due to snowfall events.” Presented at the 2012 38th IEEE Photovoltaic Specialists Conference (PVSC), June 3-8, 2012, Austin, TX. 003386 –003391. open access
- Burnham, L., D. Riley, B. Walker and J. Pearce. “Electroluminescent Imaging of Modules Exposed to Snow and Ice Loading: a Preliminary Analysis.” Photovoltaic Reliability Workshop, Denver CO, 2019.
- Burnham, L., D. Riley, B. Walker, J. and Pearce. “Performance of Bifacial Photovoltaic Modules on a Dual-Axis Tracker in a High-Latitude, High-Albedo Environment.” Proceedings of the IEEE PVSC-46 Conference, Chicago, IL, 2019. pp 8.
- Heidari, N., J. Gwamuri, T. Townsend, J. M. Pearce, “Impact of Snow and Ground Interference on Photovoltaic Electric System Performance,” IEEE Journal of Photovoltaics 5 no.6, (2015):1680-1685. doi: 10.1109/JPHOTOV.2015.2466448 open access
- Riley, D., Burnham, L., B. Walker, and J. Pearce. “Differences in Snow Shedding in Photovoltaic Systems with Framed and Frameless Modules.” Proceedings of the IEEE PVSC-46 Conference, Chicago, IL, 2019. pp 4.