0
Technical Brief

Comparative Performance and Model Agreement of Three Common Photovoltaic Array Configurations

[+] Author and Article Information
Matthew T. Boyd

National Institute of Standards and Technology (NIST),
100 Bureau Drive,
Gaithersburg, MD 20899
e-mail: matthew.boyd@nist.gov

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received March 3, 2017; final manuscript received September 26, 2017; published online November 14, 2017. Assoc. Editor: Geoffrey T. Klise.This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Sol. Energy Eng 140(1), 014503 (Nov 14, 2017) (6 pages) Paper No: SOL-17-1074; doi: 10.1115/1.4038314 History: Received March 03, 2017; Revised September 26, 2017

Three grid-connected monocrystalline silicon arrays on the National Institute of Standards and Technology (NIST) campus in Gaithersburg, MD have been instrumented and monitored for 1 yr, with only minimal gaps in the data sets. These arrays range from 73 kW to 271 kW, and all use the same module, but have different tilts, orientations, and configurations. One array is installed facing east and west over a parking lot, one in an open field, and one on a flat roof. Various measured relationships and calculated standard metrics have been used to compare the relative performance of these arrays in their different configurations. Comprehensive performance models have also been created in the modeling software pvsyst for each array, and its predictions using measured on-site weather data are compared to the arrays' measured outputs. The comparisons show that all three arrays typically have monthly performance ratios (PRs) above 0.75, but differ significantly in their relative output, strongly correlating to their operating temperature and to a lesser extent their orientation. The model predictions are within 5% of the monthly delivered energy values except during the winter months, when there was intermittent snow on the arrays, and during maintenance and other outages.

FIGURES IN THIS ARTICLE
<>
Copyright © 2018 by ASME
Your Session has timed out. Please sign back in to continue.

References

Peel, M. C. , Finlayson, B. L. , and McMahon, T. A. , 2007, “ Updated World Map of the Köppen-Geiger Climate Classification,” Hydrol. Earth Syst. Sci., 11(5), pp. 1633–1644. [CrossRef]
NREL, 2016, “ NREL: Dynamic Maps, GIS Data, and Analysis Tools,” National Renewable Energy Laboratory, Golden, CO, accessed Sept. 19, 2016, https://www.nrc.gov/docs/ML1409/ML14093A281.pdf
Dougherty, B. , and Boyd, M. , 2016, “ Model (at Least) Twice, Build Once: Experiences With the Design-Bid-Build Process for Solar Photovoltaic Arrays,” ASME J. Sol. Energy Eng., 139(3), p. 035001.
Boyd, M. , 2016, “ High-Speed Monitoring of Multiple Grid-Connected Photovoltaic Array Configurations and Supplementary Weather Station,” ASME J. Sol. Energy Eng., 139(3), p. 034502.
Boyd, M. , 2015, “High-Speed Monitoring of Multiple Grid-Connected Photovoltaic Array Configurations,” National Institute of Standards and Technology, Gaithersburg, MD, Technical Note No. 1896. http://nvlpubs.nist.gov/nistpubs/TechnicalNotes/NIST.TN.1896.pdf
Boyd, M. , 2016, “ NIST Weather Station for Photovoltaic and Building System Research,” National Institute of Standards and Technology, Gaithersburg, MD, Technical Note No. 1913. https://www.nist.gov/publications/nist-weather-station-photovoltaic-and-building-system-research
Smith, R. M. , Kurtz, S. , and Sekulic, B. , 2011, “ Back-of-Module Temperature Measurement Methods,” SolarPro, 4(6), pp. 90–104. http://solarprofessional.com/articles/products-equipment/modules/back-of-module-temperature-measurement-methods#.WgGQv1uCzZ4
Dierauf, T. , Growitz, A. , Kurtz, S. , Cruz, J. L. B., Riley, E. , and Hansen, C. , 2013, “ Weather-Corrected Performance Ratio,” National Renewable Energy Laboratory, Golden, CO, Technical Report No. NREL/TP-5200-57991. https://www.nrel.gov/docs/fy13osti/57991.pdf
Marion, B. , Adelstein, J. , Boyle, K. , Hayden, H. , Hammond, B. , Fletcher, T. , Canada, B. , Narang, D. , Shugar, D. , Wenger, H. , Kimber, A. , Mitchell, L. , Rich, G. , and Townsend, T. , 2005, “ Performance Parameters for Grid-Connected PV Systems,” IEEE Conference Record of the Thirty-First Photovoltaic Specialists Conference (PVSC), Lake Buena Vista, FL, Jan. 3–7, pp. 1601–1606.
Mermoud, A. , 2016, “ PVsyst v6.4.1,” PVsyst SA, Satigny, Switzerland.

Figures

Grahic Jump Location
Fig. 4

The data availability for the three arrays. The black bars show the percent of the available data that is needed for a complete performance analysis. The data have been filtered to exclude invalid values.

Grahic Jump Location
Fig. 5

Time series plots of selected measurements and metrics of the three arrays for the week starting on Apr. 26, 2015, when there were varying sky conditions, no array faults, and little to no precipitation. The AC power is normalized to the sum of the STC-rated DC power of the modules in the array.

Grahic Jump Location
Fig. 6

Hexagonally binned scatter plots of the same measurements and metrics shown in Fig. 5, but for the entire first year of monitoring, from Oct. 1, 2014 to Sept. 30, 2015. The AC power is normalized to the sum of the STC-rated DC power of the modules in the array, and the inverter efficiency is simply the AC power divided by the DC power. Note that the y-axis in the DC current versus DC power plot is scaled-up for the roof array.

Grahic Jump Location
Fig. 7

The temperature corrected PRs of the arrays during the first year of monitoring

Grahic Jump Location
Fig. 8

The monthly energies delivered to the local grid by the arrays for the first year of monitoring

Grahic Jump Location
Fig. 9

The CAD model for the canopy array used for modeling the effect of near shading on the array performance, showing shading on the east canopy at 09:30 am on the winter solstice. The gray triangular areas on the right of the far right canopy indicate shading, and along with the adjacent triangles indicate nonoperating modules.

Grahic Jump Location
Fig. 10

Modeled versus measured power delivered to the grid and their residuals (modeled minus measured) at an hourly time-step for the three arrays for the entire first year of monitoring, from Oct. 1, 2014 to Sept. 30, 2015. The residuals are normalized to the DC power of the arrays at STC, and these values are cropped to exclude when the arrays were either fully or partially offline.

Grahic Jump Location
Fig. 11

Model deviations for the monthly delivered energy predicted by pvsyst for the three arrays. Positive values indicate model over-prediction.

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In