A national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

National Renewable Energy Laboratory 

Innovation for Our Energy Future 

Modeling Photovoltaic and 

Concentrating Solar Power 

Trough Performance, Cost, 

and Financing with the Solar 

Advisor Model 

Preprint 

Nathan Blair, Mark Mehos, and Craig Christensen 

National Renewable Energy Laboratory 

Craig Cameron 

Sandia National Laboratories

Presented at SOLAR 2008 - American Solar Energy Society (ASES) 

San Diego, California 

May 3–8, 2008 

Conference Paper 

NREL/CP-670-42922 

May 2008 

NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 
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MODELING PHOTOVOLTAIC AND CONCENTRATING SOLAR POWER TROUGH 

PERFORMANCE, COST, AND FINANCING WITH SOLAR ADVISOR MODEL 

Nathan Blair 

National Renewable Energy Laboratory 

1617 Cole Blvd 

Golden, CO 80401 

Nate_Blair@nrel.gov 

Mark Mehos 

National Renewable Energy Laboratory 

1617 Cole Blvd 

Golden, CO 80401 

Mark_Mehos@nrel.gov 

Craig Christensen 

National Renewable Energy Laboratory 

1617 Cole Blvd 

Golden CO 80401 

Craig_christensen@nrel.gov 

Chris Cameron 

Sandia National Laboratories, New Mexico 

PO Box 5800 

Albuquerque, NM 87185- 1033 

cpcamer@sandia.gov 

ABSTRACT

A comprehensive solar technology systems analysis model, 

the Solar Advisor Model (SAM), has been developed to 

support the federal R&D community and the solar industry 

by staff at the National Renewable Energy Laboratory 

(NREL) and Sandia National Laboratory. This model is 

able to model the finances, incentives, and performance of 

flat-plate photovoltaic (PV), concentrating PV, and 

concentrating solar power (specifically, parabolic troughs). 

The primary function of the model is to allow users to 

investigate the impact of variations in performance, cost, 

and financial parameters to better understand their impact 

on key figures of merit. Figures of merit related to the cost 

and performance of these systems include, but aren’t limited 

to, system output, system efficiencies, levelized cost of 

energy, return on investment, and system capital and O&M 

costs. 

SAM allows users to do complex system modeling with an 

intuitive graphical user interface (GUI). In fact, all tables 

and graphics for this paper are taken directly from the model 

GUI. This model has the capability to compare different 

solar technologies within the same interface, making use of 

similar cost and finance assumptions. Additionally, the 

ability to do parametric and sensitivity analysis is central to 

this model. 

There are several models within SAM to model the 

performance of photovoltaic modules and inverters. This 

paper presents an overview of each PV and inverter model, 

introduces a new generic model, and briefly discusses the 

concentrating solar power (CSP) parabolic trough model. A 

comparison of results using the different PV and inverter 

models is also presented. 

1. INTRODUCTION

Originally, the Solar Advisor Model (SAM) was developed 

to meet the needs of the systems driven approach (SDA) 

that was adopted by the U.S. Department of Energy’s 

(DOE) Solar Energy Technologies Program (SETP) (1). 

By clearly establishing the connection between market 

requirements and R&D efforts (and how specific R&D 

improvements contribute to the overall system cost and 

performance), the SDA approach was designed to allow 

managers to allocate resources more efficiently. The DOE 

SETP has chosen SAM for its Solar America Initiative 

(SAI). Some applicants for SAI funding opportunities use 

SAM to calculate benchmark and projected performance 

and cost metrics. The SAI Merit Review Committee also 

uses SAM to both evaluate applications, and to track 

successful applicants' progress toward meeting their cost 

and technical goals (2). 

SAM is able to integrate the financing, costing, and 

performance of systems, and makes it possible to apply 

consistent financing and cost assumptions across all solar 

technologies. This is done by providing a set of financial 

assumptions that are appropriate for the three typical solar 

1
markets: residential, commercial, and utility-scale. For 

example, the model can show how levelized cost of energy 

for the same PV technology varies when it is purchased and 

installed by a homeowner, commercial building developer, 

or utility-scale power generation company. Finally, because 

financial incentives are so critical for all solar technologies, 

a detailed incentives approach has been developed. 

Although SAM was originally developed for DOE planning 

and the SAI, interest in the model from industry 

stakeholders has resulted in a change of focus. Valuable 

feedback from users in both the PV and CSP industries is 

shaping model development, especially in the area of 

performance modeling described in this paper. As of 

February 2008, more than 1,000 people have downloaded 

SAM, which is available for free on the SAM Web site (3). 

2. Basic Performance Model

To calculate the levelized cost of energy (LCOE) and other 

system-level metrics, SAM needs to know the annual and 

hourly energy production from the system. For DOE 

program planning purposes, researchers need to show how 

their technology improvements will impact the final systemlevel metrics. For industry analysts, the output of the 

specific PV system that they are planning to develop in the 

particular location is desired. Therefore, the SAM model 

needs to have an hourly, detailed performance model of the 

system. Behind the SAM user interface, a series of 

TRaNsient SYstem Simulation Program TRNSYS (4)

models are being run. TRNSYS was chosen for its prior 

validation, extensive library of solar-system simulation 

models, and execution speed (compiled Fortran executes an 

annual simulation in a few seconds). 

TRNSYS has the capability to use a variety of weather file 

formats. SAM can handle TMY2 formats (5) and 

EnergyPlus formats (6). Additional input data formats will 

be added in future versions. The necessary hourly weather 

data variables (including global, direct and diffuse radiation, 

temperature, wind speed, etc.) are obtained from these 

weather files and processed to be appropriate for the 

selected solar technology. The SAM user can select from 

several standard models for calculating the plane of array 

irradiance based on the horizontal radiation data including 

the isotropic sky model, the Hay and Davies Model, the 

Reindl Model, and the Perez Model (see Fig. 1). 

Additionally, the SAM user can select one of two different

sets of radiation inputs to use from the weather file. Due to 

inconsistencies between total, beam, and diffuse radiation 

present in some weather data, using either the total and 

beam radiation from the file (and calculating the diffuse 

radiation internally) or starting with the beam and diffuse 

radiation (and summing them to the total internally) can 

give statistically different hourly outputs. This is especially 

important when attempting to match SAM results with other 

programs or measured output data. Therefore, the settings in 

SAM allow the user to select either set of inputs to use. For 

all of the model comparison analysis in this paper, the Perez 

tilted surface model and the “total and beam” data inputs 

options, which are the current default values, were selected. 

SAM also allows the user to site the PV array (or parabolic 

trough field) by adjusting the tilt of the array and azimuth 

orientation, as well as selecting from three tracking modes 

(fixed, single-axis, or two-axis). 

Fig. 1: Radiation processing settings inputs 

3. PV Module Models

The SAM model currently includes four different models 

for representing the performance of a photovoltaic module. 

These include the Sandia Photovoltaic Array Performance 

Model, the five-parameter model, and the single-point 

efficiency model for both flat plate and concentrating 

systems. All models have different methods and use 

scenarios. 

3.1 Sandia Photovoltaic Array Performance Model

The Sandia Photovoltaic Array Performance model was 

developed by Sandia National Laboratories-Albuquerque 

(7). The model is empirically based and includes electrical, 

thermal, solar spectral, and optical effects. The model 

consists of 10 different inter-related empirical equations that 

take a variety of inputs including the ambient temperature, 

direct and diffuse radiation, module characteristics (for 

calculating the cell temperature), and array layout. The 

2
model has been extensively tested and compared to 

measured data on a large variety of different module 

technologies. SAM uses the empirical equations to calculate 

the maximum-power-point (MPP) power at each hour of the 

simulation, but the model can also be used to calculate 

power levels at other voltage levels. 

Within the SAM GUI, a user need only select an actual 

module type, and the proper set of roughly 30 inputs to the 

model are selected from a database. This data comes from 

extensive outdoor performance tests on commercially 

available modules. The database is available at the Sandia 

PV Web site at no charge (8). Several other simulation tools 

also make use of this database. 

The extensive testing of a new, commercially available PV 

module before entering it into the database takes time and 

resources to do objectively and independently. Therefore, 

the primary drawback to using the Sandia PV Array 

Performance model in SAM is that the Sandia database may 

not contain the recently released module that the user 

desires to model, especially with the accelerating pace of 

products being released into the marketplace. However, for 

commercial modules present in the database, this is the 

recommended model to use in SAM – primarily because of 

the independent nature of the testing and the detailed 

responsiveness of the model. 

3.2 The CEC Performance Model

A second PV module model has recently been added to 

SAM called the “CEC Performance Model” (CEC stands for 

California Energy Commission). This model is also known 

as the “five parameter” model, originally developed at the 

University of Wisconsin-Madison Solar Energy Laboratory 

(9). This model was developed specifically to allow for the 

use of standard manufacturers' data, which are the primary 

parameters to the model. This requirement allows any 

manufacturer’s module to be modeled within this model. 

The model is called the “CEC Performance Model” because 

the CEC uses this model for their free tool titled “CECPV 

Calculator” as part of their New Solar Homes Partnership 

program (10). The CEC provides the five parameters for all 

modules approved for the program. 

The CEC model is based on a theoretical circuit that 

represents the PV module (Fig. 2 from Ref. 9). The five 

parameters are shown in the circuit including: 

IL the light current 

Io the diode reverse saturation current 

Rs the series resistance 

Rsh the shunt resistance 

A a modified ideality factor 

Fig. 2: Theoretical circuit showing the five parameters 

These five parameters to represent the circuit can be derived 

from several typical items of manufacturer’s data at 

standard test conditions (STC) including: 

• the short-circuit current 

• the open-circuit voltage 

• the current and voltage at the maximum power point 

• the temperature coefficient of the open-circuit voltage 

• the temperature coefficient of the short-circuit current 

As manufacturers provide more standard information, 

efforts will be made to incorporate that data into the model 

to improve the accuracy – especially at conditions away 

from the STC. 

The advantage of using this model is that the CEC and 

individual users can quickly create the necessary parameters 

for the model based on a limited set of manufacturers’ data. 

The drawback to using this model is the lack of independent 

validation of the manufacturer’s performance claims over a 

wide range of conditions. 

Within SAM, this model should be used when the desired 

commercial module is in the SAM library. The database of 

existing parameters from the CEC is up-to-date and includes 

most commercial modules available in the marketplace. 

3.3 The Single-Point Efficiency Performance Model

As its name suggests, the single-point efficiency model 

requires only the overall module efficiency and the array 

size as inputs to calculate the hourly module power output. 

The equation is: 

Power = efficiency * module area * incident radiation 

In addition, the model includes a temperature correction 

algorithm based on that used in the Sandia Photovoltaic 

Array Performance Model. 

This model is best used in situations when the true behavior 

of the PV array is unknown, but sensitivities to module 

efficiency are desired. This is typical for analysis being 

done on potential future module improvements. For the 

most accurate results, the single-point efficiency model 

3
should be used only when the desired module is not 

available in the module libraries of either of the other two 

models. 

3.4 Concentrating Photovoltaics Module Model

SAM includes an extension of the single-point efficiency 

model for use in concentrating PV systems. This model 

extends the single-point efficiency model by allowing only 

two-axis tracking (removing the options for fixed or oneaxis tracking), and using only the direct normal component 

of solar radiation data to calculate the incident radiation on 

the module. The user then decides which costs and 

efficiencies to enter. Future plans include developing 

parameters for concentrating PV systems to be included in 

the Sandia model database. 

3.5 Comparison of Results between PV Models

The analysis described below compares the results of 

modeling a residential PV system using the three PV 

module models: Sandia PV Array model, CEC Performance 

model, and the single-point efficiency model. A module was 

chosen that is available in both the Sandia model and the 

CEC model. For the single-point efficiency model, the 

average module efficiency value from the Sandia model was 

used. For all three module models, the single-point 

efficiency inverter model was used with 90% efficiency. 

The same values were used for all of the other assumptions 

in SAM for each of the three cases. These assumptions were 

based on the values in the residential case included in the 

PV sample file distributed with SAM. 

Output Metrics Sandia CEC 5-Par. 1-Pt Eff.

LCOE (real)(¢/kWh) 22.4 21.6 22.0

kWh / kW - Year 1(h) 1,554 1,616 1,580

Capacity Factor(%) 17.7 18.4 18.0

Annual Output - Year 1(kWh) 6,467 6,723 6,575

Table 1: Comparison of different PV module models 

Table 1 shows a 4% difference in the total annual output in 

kWh between the same module as modeled by the Sandia 

model and the CEC model. This results in a difference of 

0.9 ¢/kWh in the LCOE. The hourly results in Figure 3 

show that the CEC model (shown in the lower graph) 

produces slightly higher output during the day. 

Fig. 3: Comparison of hourly results from the Sandia model 

(green-symbols) and CEC model (red-no symbols) 

One can also compare the Sandia PV Array model and the 

single-point efficiency model (Fig. 4). 

Fig. 4: Hourly comparison of Sandia (green-symbols) and 

single-point efficiency model (red-no symbols) 

4. PV Inverter Models

There are two PV inverter models available within SAM. 

The primary model is the Sandia Empirical Inverter 

Performance Model and a single-point efficiency model. 

4.1 Sandia Empirical Inverter Model

As with the Sandia PV Array Performance Model, the 

Sandia Empirical Inverter Model was developed by Sandia 

National Laboratories-Albuquerque (11). 

The model uses four equations that give the AC power out 

of the inverter as a function of several empirical 

coefficients, the DC power input, and the electric selfconsumption. The model is capable of handling several 

levels of input data. The minimal amount of information is 

4
the manufacturer's specifications of the inverter. Detailed 

field test data and laboratory test data add to the detail and 

accuracy of the model. The CEC has, in conjunction with 

Sandia, created a database of current, commercially 

available inverters that is available at no charge; this 

database is available within the SAM interface. The input 

sheet for the Sandia inverter model is shown in Figure 5, 

which only involves the user selecting an inverter from the 

drop-down menu. It displays the selected parameters and 

plots the inverter part-load efficiency. 

Fig. 5: Sandia Empirical Inverter data within SAM GUI 

The Sandia model has been extensively evaluated and 

validated at Sandia. As long as the inverter, or a similar 

inverter, is available in the database for the system that the 

user wants to model, then this is the best model to use 

within SAM. It works with any of the PV module models 

described above and provides accurate hourly results even 

in conditions far from the standard operating conditions. 

The number of inverters combined with the number of array 

strings impact the results. In the model, the array strings are 

divided evenly across one or more inverters. 

4.2 Single-Point Efficiency Inverter Model

The single-point efficiency inverter model works similarly 

to the single-point efficiency module model in that a single 

annual average efficiency number is provided. In addition to 

this, an inverter cutoff and minimum power levels are also 

provided. Only the inverter size and efficiency are inputs for 

this model. This model should be used to do sensitivity 

analysis for the system to the inverter efficiency. If a 

suitable inverter is not available for the Sandia Empirical 

model described above, this model also can be used. This 

model is also usable with any of the PV module models as 

shown in Section 3.4. 

4.3 Comparison of Results between Inverter Models 

To compare the impact of using the Sandia Empirical 

Inverter model or the single-point efficiency model, two 

cases were constructed that each used the Sandia PV Array 

Performance model but a different inverter model. The 

value of inverter efficiency used for the single-point 

efficiency was taken from the plotted Sandia model partload efficiency at 100% part load for Vnom shown in Fig. 5. 

The other assumptions were based on the default values in 

the residential PV case from the PV sample file. The 

inverter capacity was chosen to be larger than the PV array ( 

4,161 kW array output with a 5 kW inverter bank). Table 2 

shows the impact on the standard output metrics. The annual 

energy production by both systems is just less than 1% 

different resulting in an LCOE difference of 0.2 cents/Kwh 

or roughly 1%. These differences are within the larger 

uncertainty of the model and the expected uncertainty of the 

associated weather data. These differences are a function of 

the entire set of input assumptions and would vary with sets 

of inputs other than this typical system. 

Output Measure Sandia Inverter 1-pt eff. Inverter

LCOE (real)(¢/kWh) 23.1 23.3

kWh / kW - Year 1(h) 1,622 1,606

Capacity Factor(%) 18.5 18.3

Annual Output - Year 1(kWh) 6,747 6,683

Table 2: Comparison of standard outputs for inverter models 

Although the total annual output is similar for the two 

models, the hourly data looks very different. Figure 6 shows 

how the two models represent the inverter's efficiency. The 

single-point efficiency model assumes a constant efficiency, 

while the Sandia model represents the efficiency's response 

to inverter throughput. 

Fig. 6: Hourly comparison of inverter efficiency for Sandia 

model (green-symbols) and single-point efficiency (red-no 

symbols) 

5
5. CSP Model and “Generic” Model

SAM currently contains two other solar models that are not 

photovoltaic models. The first is the parabolic trough model 

used for utility-scale concentrating solar power (CSP) 

trough plants (12). This model has a detailed solar field 

model including optical efficiencies of the receiver and 

empirical heat losses from the receiver. The model allows 

for thermal storage with the plant before using an empirical 

power plant curve-fit model to calculate the hourly 

generated electricity. The model also allows the user to 

determine the appropriate hourly dispatch strategy for the 

system. Additional CSP system models are being developed 

for future implementation into SAM. 

Another non-PV model within SAM is the “generic” model, 

which allows the user to enter basic information about an 

electric generation plant, including anything from a dish 

Stirling engine-based CSP system to a coal power plant. 

Figure 7 shows the necessary inputs for the “generic” 

model. Only the nameplate capacity, efficiency, availability, 

derate, degradation, and heat rate are system inputs. The 

cost of fuel is included on the cost page. This simple model 

calculates a first-year average annual output based on the 

assumptions; and, unlike the PV and CSP system models, 

does not perform an hourly simulation. 

Fig. 7: “Generic” model input values and calculated annual 

output 

A SAM user would choose the “generic” model primarily 

when the user does not have a lot of detail about the system, 

is not concerned with the hourly performance of the system, 

or to model a system that is not represented in more detail 

within SAM. The model makes it possible to take advantage 

of SAM's financing, incentive, and cost capabilities to 

determine the levelized cost or other output metrics when 

detailed performance assumptions are not available. The 

model also provides a way to compare utility-scale solar 

systems to conventional fossil fuel-based power plants. This 

model was developed in response to solar industry analysts 

requests for a capability to compare their PV or CSP 

technologies with fossil technologies with the same 

financial parameters. 

6. CONCLUSIONS

The Solar Advisor Model allows for a variety of detailed 

simulations of photovoltaic and other solar (and non-solar) 

energy systems using several models developed by the 

national laboratories, which are being used by several 

organizations. There are four PV module models and two 

PV inverter models within SAM. Using the best option for 

each particular user and use scenario will achieve the most 

accurate results – but all models produce “reasonable” 

results. The existing database of modules within SAM 

continues to grow and includes the most current commercial 

modules available. The ability to compare PV systems 

across markets with CSP and non-solar technologies within 

the same tool is unique. 

SAM is a tool that serves a multitude of users for a variety 

of analysis needs in different technologies and markets. 

7. ACKNOWLEDGMENTS

The authors would like to thank the entire SAM 

development team for input to this paper and the program 

itself including Chris Cameron, Craig Christensen, Mark 

Mehos, Steve Janzou, Paul Gilman, Hank Price, and others. 

8. REFERENCES

1. http://www.eere.energy.gov/solar/systems_driven.html

2. http://www1.eere.energy.gov/solar/solar_america/

3. http://www.nrel.gov/analysis/sam

4. Klein et al., 2003 TRNSYS 16, A Transient Simulation 

Program. Solar Energy Laboratory, University of Wisconsin, 

Madison, Wisconsin, WI.

5. Marion, W. , Urban, K., “User’s Manual for TMY2s”, 

June 1995, 

http://rredc.nrel.gov/solar/old_data/nsrdb/tmy2/

6. http://www.eere.energy.gov/buildings/energyplus/cfm/

weather_data.cfm

7. King D. L., Boyson W. E., Kratochvil J. A.,

”Photovoltaic Array Performance Model”, Aug. 2004, 

SAND2004-3535

8. http://photovoltaics.sandia.gov/docs/Database.htm

9. De Soto, W., Klein S.A., Beckman W.A., Improvement 

and validation of a model for photovoltaic array 

performance 

Solar Energy, Volume 80, Issue 1, January 2006, Pages 

78-88

6
10. http://www.gosolarcalifornia.ca.gov/nshpcalculator/

11. King, D. L., Gonzalez, S., Galbraith, G.M., Boyson, W. 

“Performance Model for Grid-Connected Photovoltaic 

Inverters”, Sept. 2007, SAND2007-5036, 

http://www.prod.sandia.gov/cgi-bin/techlib/accesscontrol.pl/2007/075036.pdf

12. Blair, N., Mehos, M., Christensen, C., “Sensitivity of 

Concentrating Solar Power Trough Performance, Cost 

and Financing With the Solar Advisor Model, 2008 CSP 

SolarPaces Symposium 

7
F1146-E(12/2004) 

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Modeling Photovoltaic and Concentrating Solar Power Trough 

Performance, Cost, and Financing with the Solar Advisor Model: 

Preprint 

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14. ABSTRACT (Maximum 200 Words)

A comprehensive solar technology systems analysis model, the Solar Advisor Model (SAM), has been developed to 

support the federal R&D community and the solar industry by staff at the National Renewable Energy Laboratory 

(NREL) and Sandia National Laboratory. This model is able to model the finances, incentives, and performance of 

flat-plate photovoltaic (PV), concentrating PV, and concentrating solar power (specifically, parabolic troughs). The 

primary function of the model is to allow users to investigate the impact of variations in performance, cost, and 

financial parameters to better understand their impact on key figures of merit. Figures of merit related to the cost and 

performance of these systems include, but aren’t limited to, system output, system efficiencies, levelized cost of 

energy, return on investment, and system capital and O&M costs. There are several models within SAM to model 

the performance of photovoltaic modules and inverters. This paper presents an overview of each PV and inverter 

model, introduces a new generic model, and briefly discusses the concentrating solar power (CSP) parabolic trough 

model. A comparison of results using the different PV and inverter models is also presented. 

15. SUBJECT TERMS

NREL; Nathan Blair; Mark Mehos; Craig Christensen; Solar Advisor Model; SAM; photovoltaic; PV; concentrating 

solar power; CSP; concentrating PV; solar energy 

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