Performance Model Documentation

SAM's performance models calculate the hourly output of a renewable energy system over a single year (except for the geothermal model that is based on monthly resource depletion over many years). The documents on this page are published articles and academic dissertations that describe the algorithms used by the different performance models.

For more general descriptions of the models and their implementation in SAM, and for instructional materials see SAM's Help system, or documents and links on the Learning page.

Photovoltaic Models

SAM's photovoltaic peformance model relies on separate component models to represent the performance of modules and inverters in the system. SAM's user interface allows you to choose from several component model options, which are described in the documents listed below. A photovoltaic model reference manual is forthcoming (as of February 2014) that describes how the component models are implemented in SAM, and the algorithms not described below such as sun position and incident irradiance calculations, near-object shading, soiling, etc.

Sandia Module Model

King, D.L.; Boyson, W.E.; and Kratochvil, J.A. (2004). "Photovoltaic Array Performance Model." 41 pp.; Sandia Report No. 2004-3535. (PDF 1.8 MB)

Sandia Inverter Model

King, D.L.; Gonzalez, S.; Galbraith, G.M.; and Boyson, W.E. (2007). "Performance Model for Grid Connected Inverters." 47 pp.; Sandia Report No. 2007-5036. (PDF 1.3 MB)

CEC Module Model

Dobos, A. P. (2012). "An Improved Coefficient Calculator for the CEC Photovoltaic Module Model." ASME Journal of Solar Energy Engineering. In Press.

De Soto, W.L. (M.S. 2004). "Improvement and Validation of a Model for Photovoltaic Array Performance." University of Wisconsin-Madison. (ZIP 1.8 MB)

Neises, T. (M.S., 2011). "Development and Validation of a Model to Predict the Temperature of a Photovoltaic Cell." University of Wisconsin-Madison. (ZIP 4.4 MB)

One-axis Tracking

Marion, W.; Dobos, A. (2013). "Rotation Angle for the Optimum Tracking of One-Axis Trackers." National Renewable Energy Laboratory. 10 pp.; NREL/TP-6A20-58891. (PDF 388 KB)

Self-shading Calculator for Fixed Tilt Arrays

Deline, C.; Dobos, A.; Janzou, S.; Meydbrey, J.; Donoval, M. (2013) A Simplified Model of Uniform Shading in Large Photovoltaic Arrays. Solar Energy Vol 96, October 2013, pp 274-282. Draft Preprint (PDF 1.3 MB)

PV Subarray Mismatch

Dobos, A. P. (2012). Modeling of Annual DC Energy Losses due to Off Maximum Power Point Operation in PV Arrays. [Proceedings] 38th IEEE Photovoltaic Specialists Conference (PVSC '12), 3-8 June 2012, Austin, Texas. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE) pp. 002967-002969; NREL Report No. CP-6A20-55362.


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.; Townsend, T. (2005). "Performance Parameters for Grid-Connected PV Systems." 9 pp.; NREL Report No. CP-520-37358. (PDF 816 KB)

Marion, W., Anderberg, M. (2000). PVWATTS - An Online Performance Calculator for Grid-Connected PV Systems. Proceedings of the ASES Solar Conference, June 15-21, Madison, WI.

Concentrating Solar Power (CSP) Models

The CSP models include models for parabolic trough, power tower, linear Fresnel, dish-Stirling systems, and a generic solar system model.

Empirical Trough (Based on Excelergy)

Price, H. (2003). Parabolic Trough Solar Power Plant Simulation Model. Proceedings of the ISEC 2003: International Solar Energy Conference, 15-18 March 2003, Kohala Coast, Hawaii. New York: American Society of Mechanical Engineers. 665-673 pp.; NREL Report No. CP-550-34742. (PDF 548 KB)

Physical Trough Model

Wagner, M. J.; Gilman, P. (2011). "Technical Manual for the SAM Physical Trough Model." 124 pp.; NREL Report No. TP-5500-51825. (PDF 3.7 MB)

Dish Stirling

Fraser, P. (M.S. 2008). "Stirling Dish System Performance Prediction Model." University of Wisconsin-Madison. (ZIP 1.8 MB)

Power Tower Molten Salt

Wagner, M. (M.S. 2008). "Simulation and Predictive Performance Modeling of Utility-Scale Central Receiver System Power Plants." University of Wisconsin-Madison. (ZIP 32.3 MB)

Power Tower Direct Steam

Neises, T.; Wagner, M. (2012). "Simulation of Direct Steam Power Tower Concentrated Solar Plant." ASME SE 2012 6th International Conference on Energy Sustainability July 23-26, 2012.

Power Tower Field Optimization

Kistler, B. (1986). "A User's Manual for DELSOL3: A Computer Code for Calculating the Optical Performance and Optimal System Design for Solar Thermal Central Receiver Plants." Sandia Report No. SAND86-8018. (PDF 10 MB)

Feierabend, L. (M.S., 2009). "Thermal Model Development and Simulation of Cavity-Type Solar Central Receiver Systems." University of Wisconsin-Madison. (ZIP 5.0 MB)

Linear Fresnel

Wagner, M.; Zhu, G. (2012). "A Direct-steam Linear Fresnel Performance Model for NREL's System Advisor Model." NREL Conference Paper CP-5500-55044. (PDF 647 KB)

Wagner, M. (2012). "Results and Comparison from the SAM Linear Fresnel Technology Performance Model: Preprint. NREL Conference Paper CP-5500-54758." (PDF 726 KB)

Generic Solar System Model

Wagner, M. J.; Zhu, G. (2011). "Generic CSP Performance Model for NREL's System Advisor Model: Preprint." 10 pp.; NREL Report No. CP-5500-52473. (PDF 729 KB)

Biomass Power

Jorgenson, J.; Gilman, P.; Dobos, A. (2011). Technical Manual for the SAM Biomass Power Generation Model. 40 pp.; NREL Report No. TP-6A20-52688. (PDF 728 kB)

Geothermal Power

SAM's geothermal power model is based on the U.S. Department of Energy's Geothermal Electricity Technology Evaluation Model (GETEM). GETEM Manuals and Revision Notes.

Wind Power

Freeman, J.; Gilman, P.; Jorgenson, J.; Ferguson, T. (DRAFT 2013). Reference Manual for the System Advisor Model's Wind Performance Model. (PDF 815 KB)

Quinlan, P. J. A., (M.S., 1996). "Time Series Modeling of Hybrid Wind Photovoltaic Diesel Power Systems". University of Wisconsin-Madison. (ZIP 2.1 MB)

Statistical Analysis

The following documents describe the Latin hypercube sampling (LHS) method that SAM uses for the statistical analysis simulation option (see SAM Help - Statistical).

For a description of the LHS method implemented in SAM, see Wyss, G; Jorgensen, K. (1998). "A user's Guide To LHS: Sandia's Latin Hypercube Sampling Software." Sandia National Laboratories.  SAND98-0210. 140 pp. (PDF 559 KB)

For a more general discussion of sampling-based uncertainty analysis, see Helton, J.; Davis, F.; (2000). "Sampling-Based Methods for Uncertainty and Sensitivity Analysis." SAND99-2240. 121 pp. (PDF 5 MB)

For a basic description of the Latin hypercube sampling method, see the Wikipedia article "Latin hypercube sampling."

For other publications about SAM, see Publications Featuring SAM.

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