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.

Detailed Photovoltaic Model

SAM's detailed 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.

Photovoltaic Reference Manual

Gilman, P. (2015). SAM Photovoltaic Model Technical Reference. National Renewable Energy Laboratory.  59 pp.; NREL/TP-6A20-64102. (PDF 840 KB)

Errata for PV reference manual, 4/7/2017 (PDF 111 KB)

Module Models

CEC Module Model

Dobos, A. P. (2012). An Improved Coefficient Calculator for the CEC Photovoltaic Module ModelASME 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)

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)

IEC 61853 Module Model

Dobos, A.; Freeman, J. (2017) Significant Improvement in PV Module Performance Prediction Accuracy using a New Model Based on IEC-61853 Data. DRAFT. Photovoltaic Specialist Conference (PVSC), 2017 IEEE PVSC-44. (PDF 272 KB)

Dobos, A. P. (2015).  Procedure for applying IEC-61853 test data to a single diode mode. Photovoltaic Specialist Conference (PVSC), 2014 IEEE 40th.

Simple Efficiency Module Model

See Gilman (2015) PV reference manual cited above.

Inverter Models

Inverter CEC Database Inverter Model (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)

Inverter Datasheet and Inverter Part Load Curve Models

See Gilman (2015) PV reference manual cited above.

Battery Storage

DiOrio, N.; Dobos, A.; Janzou, S.; Nelson, A.; Lunstrom, B. (2015). Technoeconomic Modeling of Battery Energy Storage in SAM. 32 pp. NREL/TP-6A20-64641 (PDF 2.6 MB)

DiOrio, N.; Dobos, A.; Janzou, S. (2015). Economic Analysis Case Studies of Battery Energy Storage with SAM. 22 pp. NREL/TP-6A20-64987 (PDF 550 KB)


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)

Partial Shading of Photovoltaic Array

MacAlpine, S.; Deline, C. (2015) Simplified Method for Modeling the Impact of Arbitrary Partial Shading Conditions on PV Array Performance. National Renewable Energy Laboratory. 8 pp.; NREL/CP-5J00-64570. (PDF 699 KB)

Deline, C.; MacAlpine, S.; Hanson, A.; Stauth, J.; Sullivan, C. (2015) Partial-Shading Assessment of Photovoltaic Installations via Module-Level Monitoring. National Renewable Energy Laboratory. 7 pp. NREL/CP-5J00-63765. (PDF 816 KB)

POA Irradiance as Input

Freeman, J.; Freestate, D.; Hobbs, W.; Riley, C. (2016). Using Measured Plane-of-Array Data Directly in Photovoltaic Modeling: Methodology and Validation. National Renewable Energy Laboratory. 6 pp. NREL//CP-6A20-66465. (PDF 1.4 MB)

DC Losses

Self Shading

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)

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.

Snow Coverage

Ryberg, D.; Freeman, J. (2015). Integration, Validation and Application of a PV Snow Coverage Model in SAM. National Renewable Energy Laboratory. 21 pp. TP-6A20-64260. (PDF 2.1 MB)

Power Electronics

Freeman, J. (2015). Modeling Photvoltaic Module-Level Power Electronics in the System Advisor Model. National Renewable Energy Laboratory. 2 pp. FS-5400-64113 (273 KB)

Model Comparison

Yates, T.; Hibberd, B. (2010). Production Modeling for Grid-Tied PV Systems. SolarPro (Issue 3.3 Apr/May).


Dobos, A. (2014). PVWatts Version 5 Manual. 20 pp.; NREL Report No. TP-6A20-62641. (PDF 714 KB)

Dobos, A.; (2013). PVWatts Version 1 Technical Reference. 11 pp.; NREL Report No. TP-6A20-60272. (PDF 487 KB)

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.

Solar Water Heating Model

Christensen, C.; Maguire, J.; Burch, J.; DiOrio, N. (2014). Simplified Solar Water Heater Simulation Using a Multi-mode Tank Model. Solar 2014 Conference Presentation. (PDF 1.8 MB)

DiOrio, N.; Christensen, C.; Burch, J.; Dobos, A. (DRAFT 2014). Technical Manual for the SAM Solar Water Heating Model. (PDF 150 KB) NOTE: THIS DRAFT IS OUT OF DATE BUT PROVIDES USEFUL INFORMATION ABOUT THE MODEL.

Concentrating Solar Power (CSP) Models

SAM includes models for the following kinds of CSP systems: Parabolic trough, molten salt and direct steam power towers, molten salt and direct steam linear Fresnel, dish Stirling, a generic CSP model, integrated solar combined cycle. References for the solar process heat models are listed separately below.

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)

Turchi, C.; Neises, T. (2015). Parabolic Trough Solar-Thermal Output Model Decoupled from SAM Power Block Assumptions. Milestone report prepared for the U.S. Department of Energy. (PDF 542 KB)

Dish Stirling

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

Power Tower

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)

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)

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.

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)

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)

Bachelier, C. (2012). SAM Linear Fresnel solar boiler model: Novatec Solar Boiler Sample File. SAM Virtual Conference: June 20, 2012.

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)

Integrated Solar Combined Cycle

Turchi, C.; Ma, Z. (2014). Co-located Gas Turbine / Solar Thermal Hybrid Designs for Power Production. Renewable Energy Vol. 64 April 2014. 7 pp.

Zhu, G.; Nieses, T.; Turchi, C.; Bedillon, R. (2015). Thermodynamic Evaluation of Solar Integration into a Natural Gas Combined Cycle Power Plant. Renewable Energy Vol. 74 February 2015. 9 pp.

CSP Power Cycle Models

Neises, T. (DRAFT 2015). Description of SAM's CSP User-defined Power Cycle Model. (PDF 830 KB) The user-defined power cycle option is available as part of the physical trough, molten salt power tower, and molten salt linear Fresnel CSP models in SAM.

Neises, T.; Turchi, C. (2014). Supercritical CO2 Power Cycles: Design Considerations for Concentrating Solar Power. 8pp. NREL/CP-5500-62542. (PDF  567 KB). The type of technical comparison described in this paper can be performed using the molten salt power tower model in SAM 2015.6.30. The sCO2 cycle model was removed from later versions of SAM due to updates to the power tower model.

Thermal Energy Storage

Ma, Z.; Glatzmaier, G.; Wagner, M.; Neises, Ty. (2012). General Performance Metrics and Applications to Evaluate Various Thermal Energy Storage Technologies. ASME 2012 6th International Conference on Energy Sustainability, Parts A and B. San Diego, California, USA, July 23–26, 2012

CSP Modeling Approach

Dobos, A.; Neises, T.; Wagner, M. (2014). Advances in CSP Simulation Technology in the System Advisor Model. 7 pp. NREL/CP-6A20-61629.

Solar Industrial Process Heat

Kurup, P.; Turchi, C.; (2015). Initial Investigation into the Potential of CSP Industrial Process Heat for the Southwest United States. 78 pp. NREL/TP-6A20-64709. (PDF 5.3 MB)

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. (2014). Reference Manual for the System Advisor Model's Wind Performance Model. National Renewable Energy Laboratory, NREL/TP-6A20-60570. (PDF 738 KB)

Maness, M.; Maples, B.; Smith, A.; NREL Offshore Balance-of-System Model. National Renewable Energy Laboratory, NREL/TP-6A20-66874. (PDF 4.7 MB)

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)

Weather Data

Dobos, A.; Gilman, P.; Kasberg, M. (2012). P50/P90 Analysis for Solar Energy Systems Using the System Advisor Model. NREL Conference Paper Preprint No. CP-6A20-54488. (PDF 432 KB)

Habte, A.; Lopez, A.; Sengupta, M.; Wilcox, S. (2014). Temporal and Spatial Comparison of Gridded TMY, TDY, and TGY Data Sets. NREL Report No. TP-5D00-60866. (PDF 17.4 MB)

EnergyPlus Energy Simulation Software. (2014). Weather Data Format Definition. [EPW format description.]

National Solar Radiation Database. (1992). National Solar Radiation Data Base User's Manual (1961-1990). [TMY2 format description.]

Sengupta, M.; Habte, A.; Kurtz, S.; Dobos, A.; Wilbert, S.; Lorenz, E.; Stoffel, T.; Renne, D.; Myers, D.; Wilcox, S.; Blanc, P.; Perez, R. (2015). Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications. NREL Report No. TP-5D00-63112. (PDF 8.9 MB)

Wilcox, S.; Marion, W. (2008). Users Manual for TMY3 Data Sets (Revised). 58 pp.; NREL Report No. TP-581-43156. ( PDF 1.7 MB)

Stochastic Simulations

The following documents describe the Latin hypercube sampling (LHS) method that SAM uses for stochastic simulations.

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.


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