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Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Contract No. DE-AC36-08GO28308

Results and Comparison from 

the SAM Linear Fresnel 

Technology Performance Model

Preprint

Michael J. Wagner 

To be presented at the 2012 World Renewable Energy Forum

Denver, Colorado

May 13–17, 2012

Conference Paper

NREL/CP-5500-54758

April 2012
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WREF 2012: RESULTS AND COMPARISON FROM THE SAM LINEAR
 

FRESNEL TECHNOLOGY PERFORMANCE MODEL
 

Michael J. Wagner

National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401

michael.wagner@nrel.gov

ABSTRACT 

This paper presents the new Linear Fresnel technology 

performance model in NREL’s System Advisor Model. 

The model predicts the financial and technical 

performance of direct-steam-generation Linear Fresnel 

power plants, and can be used to analyze a range of 

system configurations. This paper presents a brief 

discussion of the model formulation and motivation, and 

provides extensive discussion of the model performance 

and financial results. The Linear Fresnel technology is 

also compared to other concentrating solar power 

technologies in both qualitative and quantitative 

measures. 

The Linear Fresnel model - developed in conjunction 

with the Electric Power Research Institute - provides 

users with the ability to model a variety of solar field 

layouts, fossil backup configurations, thermal receiver 

designs, and steam generation conditions. This 

flexibility aims to encompass current market solutions 

for the DSG Linear Fresnel technology, which is seeing 

increasing exposure in fossil plant augmentation and 

stand-alone power generation applications. 

Keywords: System Advisor Model; SAM; Linear Fresnel; 

CLFR; Annual Simulation; CSP; NREL; EPRI; Direct 

Steam Generation 

1 INTRODUCTION 

The Linear Fresnel Reflector (LFR) technology is of 

growing interest to US utilities as a candidate for 

combined-cycle integration through direct steam 

generation (DSG) [1]. The LFR concept uses a set of 

long mirror facets that reflect light to a linear receiver 

where it can be directly absorbed by the receiver [2] or 

concentrated a second time with a compound parabolic 

reflector [3]. The optical performance of the LFR system 

is limited by the angle at which the sunlight strikes the 

reflectors, and because the mirrors must be oriented to 

reflect the irradiation to the receiver, they most often do 

Fig. 1: Angles associated with the optical performance of the 

LFR technology, including transversal incidence φT , longitudinal 

incidence φL, solar zenith θz, and solar azimuth γs. 

not directly face the sun. This non-normal orientation 

towards the incoming sunlight is the primary optical loss 

for LFR, and the loss is incurred both with respect to 

the transversal plane (perpendicular to the axis of the 

collector) and longitudinal plane (parallel with the axis 

of the collector). This concept is illustrated in Figure 1. 

Optical performance for the LFR system varies 

significantly throughout the year, with peak 

performance in the summer months. Figure 2 shows the 

variation in total optical efficiency for a sample LFR 

field over the course of the year. 

This annual productivity variation has several 

important implications in terms of plant integration, 

and it is consequently important to have performance 

modeling capability for the technology. Several models 

have been developed previously for various applications 

[4] [5] [6] [7] [8] [2], but no detailed annual-hourly 

performance model has yet been made public. Recently, 

1 
Fig. 2: LFR optical efficiency as a function of the time of day 

(vertical axis) and day of the year (horizontal axis) for a sample 

geometry. Peak optical efficiency at solar noon varies from 30% 

in the winter months to above 60% in the summer. 

a new hourly-annual techno-economic model was 

implemented to address this gap in System Advisor 

Model (SAM) developed by the National Renewable 

Energy Laboratory, Sandia National Laboratory, and 

supported by the US Department of Energy. This model 

is presented in detail in [9] where a more thorough 

review of previous work is also discussed. 

The current document provides a review of the main 

features and capabilities of the LFR model in System 

Advisor and provides the results of a study comparing 

the performance of the LFR technology with other CSP 

systems. 

2 MODEL DESCRIPTION 

This section discusses the main features of the System 

Advisor LFR model in light of the variety of technology 

options that are currently available. The current 

technology solutions available in the market use 

water/steam as the heat transfer fluid, as represented by 

[3] and others, and are thus referred to as “Direct Steam 

Generation” (DSG) systems. The solar field is arranged 

into a number of parallel loops, where each loop is 

composed of a series of collector modules, as shown in 

Figure 3. 

Once steam is generated, it can be used to drive a 

stand-alone power cycle, to displace fuel usage by 

integration with an existing fossil fuel plant [10], or to 

Fig. 3: A simplified example LFR plant layout with two loops in 

parallel and an auxiliary fossil heater in series after the field 

outlet. 

provide industrial process heat. Because of the modular 

nature of the technology, a relatively wide range of 

steam outlet conditions are achievable, with the current 

upper limit of superheated steam at 500◦C [3]. The 

System Advisor LFR model is capable of modeling 

direct-steam systems with various geometry 

arrangements and outlet temperature requirements. 

2.1 Loop Configurations 

Two loop configurations are considered in System 

Advisor. The first option uses a recirculated boiler, as 

shown in Figure 4. The recirculated boiler is similar in 

concept to traditional pulverized coal boilers. Water 

enters the boiler section as a high-pressure subcooled 

liquid and absorbs energy as it converts from liquid to 

steam. The partially evaporated mixture exits the boiler 

section and passes through a separator device that 

removes the liquid phase from the mixture. The liquid is 

recirculated back to the inlet of the boiler and the 

saturated vapor is sent to the superheater section for 

additional heating. 

The recirculated arrangement has several advantages, 

including the ability to maintain stable heat transfer 

between the hot pipe wall and the liquid/steam mixture. 

Good heat transfer prevents overheating of the tube 

walls, which can reduce the lifetime of the tubing and 

lead to material failure. However, recirculation increases 

the flow requirement in the boiler section, requiring 

additional pumping power and increased annual 

parasitics. The steam temperature at the outlet of the 

superheater is also constrained since the mass flow rate 

through the superheater is determined by the boiling 

rate and cannot be controlled with pumping. This 

2 
Fig. 4: The recirculated boiler arrangement. In a recirculation 

system, partially boiled steam passes through a separator where 

the liquid portion is returned to the loop inlet and the vapor 

portion is sent to the superheater section. 

introduces additional complexity in maintaining suitable 

steam temperatures that accommodate both solar field 

and high-pressure turbine material limitations. Previous 

work in [9] presents modeled behavior of a recirculated 

system in more detail. 

The second loop configuration is the once-through 

system as shown in Figure 5, where liquid water is 

heated up to superheated steam in a single pass without 

recirculation. This option has been proposed for both 

LFR and Parabolic Trough technologies [11] [12], but 

has not yet been demonstrated because of control 

complexity. Nonetheless, System Advisor includes this 

option for purposes of comparison and analysis of future 

technology options. Potential advantages of the 

once-through design are reduced pumping parasitics, 

reduced equipment and piping cost (from removing the 

separator and return piping), and improved steam outlet 

temperature control. However, boiling stability remains 

a concern and must be addressed before commercial 

implementation. 

One model limitation given the mixed applications 

available in the LFR market is System Advisor’s 

inability to model low-temperature saturated steam 

systems. In industrial heat and fossil plant integration 

applications, steam leaves the solar field in a saturated 

Fig. 5: The once-through boiler arrangement. Liquid water 

enters the loop and is heated through to superheated steam in a 

single pass without recirculation. 

rather than superheated state. The CSP technology 

suite in System Advisor assumes stand-alone power 

generation, and some of the models (including LFR) 

share common algorithms for power cycle performance 

calculations. The power cycle formulation uses the most 

common steam conditions - namely, superheated 

subcritical steam. Saturated steam can therefore not be 

modeled directly. 

2.2 The Optical Model 

Optical modeling of an LFR system can be complex, 

requiring detailed information on the reflector geometry, 

error distributions, and receiver dimensions. The most 

practical method for analyzing optical performance of a 

given geometry is with computational methods such as 

ray tracing. In balancing complexity of user-supplied 

input with ease of use, System Advisor does not include 

detailed specifications for collector and receiver 

geometry, so the model defines optical performance 

using a table of efficiency values that are defined by the 

user. This input can be generated externally in a ray 

tracing package such as SolTrace [13] for a variety of 

solar positions. 

While optical performance can be specified in terms of 

solar position, it is more common with the LFR and 

technology to express it in terms of the transversal and 

3 
Fig. 6: Incidence angle modifier curves for both the longitudinal 

(φL) and transversal (φT ) plane effects. 

longitudinal angles (as defined previously in Figure 1). 

System Advisor allows the user to define optical 

performance using either method by filling in the optical 

table accordingly. A third option is to specify the 

angularly-dependent performance with Incidence Angle 

Modifier (IAM) equations, which are simple polynomial 

relationships. IAM behavior depends strongly on the 

collector and receiver geometry and optical properties; 

however, the general trends are shown with a sample 

system based on the Novatec Solar design in Figure 6. 

The polynomial-based curves when multiplied together 

are equivalent to the two-dimensional optical efficiency 

table. 

2.3 The Receiver Heat Loss Model 

Several varied LFR receiver designs have been proposed 

and are currently used in marketed designs. The two 

most well-known design concepts are the “oven-box” 

concept that uses a set of small parallel absorber tubes 

nested within a trapezoidal insulated cavity [14], and 

the compound parabolic secondary concentrator tubular 

receiver presented by Morin [3]. Other receiver concepts 

have been proposed including those by Goswami [4] and 

Mills & Morrison [2]. 

Considering the diversity and geometric complexity of 

the available receiver options, developing an enveloping 

thermal performance model from heat transfer and fluid 

mechanics first-principles is not practical. Whereas the 

parabolic trough evacuated tube receiver is rotationally 

symmetric and can easily be modeled and validated 

using heat transfer first principles [15], thermal 

Fig. 7: Default behavior of the receiver thermal losses in the 

System Advisor LFR model as a function of local temperature 

difference (steam temperature minus ambient temperature). 

performance models for LFR receivers tend to use 

computationally intensive two or three-dimensional CFD 

analyses (see for example [14] [16] [17]) that are not 

feasible as part of an annual-hourly simulation tool. 

The primary means for determining receiver thermal 

performance in the System Advisor LFR is a simplified 

set of polynomials curves that express heat loss as a 

function of the difference between local steam 

temperature and ambient temperature. The equation of 

the form shown in Eq. [1] returns a heat loss factor in 

units of W/m. 

 W W W

q ̇ = C0 +C1 ΔT +C2 ΔT2+... hl m m · K m · K2

(1) 

ΔT = Tsteam,local − Tambient (2) 

 The heat loss in watts per meter of collector length (  ̇q ) hl

is multiplied by the collector length that is described by 

the local temperature difference in Eq. [2] to determine 

the full receiver thermal loss. The default heat loss 

correlation in System Advisor is plotted in Figure 7. A 

second polynomial equation is provided to scale heat 

loss as a function of wind velocity, though the default 

behavior modeled in System Advisor does not include 

this sensitivity. 

For purposes of comparison, and because 

high-performance receivers have been proposed for 

high-temperature applications, System Advisor also 

includes an evacuated tube receiver model as an 

alternative to the polynomial model. The model is the 

4 
same as described in Forristall [15] and implemented in 

[18]. 

2.4 Power Cycle and Balance of Plant 

In DSG systems where the solar field heat transfer fluid 

also serves as the working fluid in the power cycle, the 

behavior and response of the power cycle to various 

effects more directly impacts operating conditions in the 

solar field. This interdependency results in a highly 

coupled system, and model accuracy depends on 

capturing the power cycle behavior. Described elsewhere 

in detail [19] [20], the power cycle model contains 

relationships describing how heat input to the cycle and 

gross power output depend on three independent 

variables - namely, hot steam inlet temperature, steam 

mass flow rate from the solar field, and condenser 

pressure (affected by ambient temperature and heat 

rejection technology). The reader is referred to the 

above-cited material for a more detailed discussion of 

this model. 

One interesting aspect of the DSG technology is the 

potential for integrating an auxiliary fossil backup boiler 

to assist in steam generation. System Advisor provides 

three configuration options for the auxiliary boiler: 

Minimum Backup Level engages fossil backup 

when the solar field output falls below the 

user-specified fraction of design-point power cycle 

heat input. 

Supplemental Operation adds fossil energy to 

bring the total thermal input to the power cycle up 

to the design-point level. The maximum amount of 

fossil energy supplied at any given time step is 

equal to the user-defined fraction times the 

design-point power cycle thermal energy. 

Topping Mode puts the auxiliary heater in series 

after the solar field (unlike the previous two parallel 

options), and the boiler is used to boost the steam 

temperature during time periods where the solar 

field cannot supply steam at temperature. 

3 TECHNOLOGY COMPARISON 

One role of the System Advisor tool is to facilitate 

technology comparisons within a consistent framework. 

With the addition of the LFR model, an extensive CSP 

Fig. 8: Possible arrangements for the auxiliary fossil boiler: 

parallel (top) used in the Minimum Backup Level and 

Supplemental Operation mode, and series (bottom) used in 

Topping Mode. 

technology comparison can be made that investigates 

both performance and economic factors. Similar 

comparisons appear frequently in literature, including 

[16], [21], [22], [23], and [24]. The current analysis differs 

from previously published results in the extent of the 

included technologies and/or in the modeling of a DSG 

LFR system as opposed to a sensible-heat HTF. The 

four technologies included in this comparison are the 

DSG LFR, DSG Power Tower, Molten Salt Power 

Tower, and Parabolic Trough (Therminol with solar 

salt thermal storage). 

3.1 Study Methodology 

In comparative studies where the goal is to analyze 

different technologies on equal footing, the choice of 

design-point parameters can have a significant impact 

on the final conclusions, even leading to technology bias 

under certain conditions. For CSP technologies that can 

include thermal storage, design parameter definition is 

even more challenging. Several different system design 

features can be chosen to be held constant for each 

technology, such as design-point electrical output, solar 

field mirror area (or aperture area), plant cost, land 

5 
TABLE 1: FIXED DESIGN PARAMETERS TABLE 2: TECHNOLOGY-SPECIFIC DESIGN 

PARAMETERS 

Item Units Value 

Plant location 

Federal ITC 

Debt service coverage ratio 

Project IRR 

Annual electricity production 

Heat rejection 

Dispatch market 

Fossil backup 

-

% 

-

% 

GW-hr 

-

-

-

Phoenix, AZ 

0 

Optimized 

15 

300 

Dry cooling 

Flat rate 

None 

area, etc. The most likely candidates for common 

comparison are power block rating and solar field 

aperture area, but - as shown in the work currently 

presented - unnecessarily constrains the technologies. 

The current study uses total annual electricity 

production as the “design” metric, adjusting the other 

plant design parameters until the goal output is reached. 

Each system was optimized for the Phoenix, AZ, 

location to produce the minimum levelized cost of 

energy (LCOE). The process for defining the system 

design follows the general procedure: 

1. Define the fixed design-point parameters as

established in Table 1

2. Parametrically optimize the solar multiple (the 

ratio of design-point solar field thermal output to 

power cycle thermal input) 

3. For systems with thermal storage, parametrically 

optimize the equivalent hours of thermal storage. 

4. Adjust the power cycle design-point rating until the 

annual output matches the target production. 

The other design-point values for the various 

technologies were left at their default System Advisor 

values. Some notable items are presented in Table 2. 

The LFR solar field is modeled as a recirculated boiler 

with a boiler outlet quality (vapor mass fraction) of 

75%. The LFR case also uses the polynomial heat loss 

model and optical performance table based on published 

information from Novatec Solar [3]. All technologies 

define design-point cycle efficiency assuming a condenser 

pressure of 8,000 Pa, corresponding to an ambient dry 

bulb temperature of 20◦C. 

3.2 Analysis Results 

This procedure allows for optimization within each 

unique CSP technology and frees systems with thermal 

Item Units LFR PT-dsg PT-ms Tr 

Outlet temp. 

Cycle eff. 

Boiler Pres. 

◦C 

% 

bar 

440 

38.0 

110 

565 

42.5 

160 

565 

42.5 

100 

390 

37.8 

100 

storage to reach a substantially different optimum than 

systems without. The results of the optimization 

exercise are shown in Table 3, with the design 

parameters for each optimized technology reported. 

The most notable (but perhaps expected) result from 

the optimization exercise is the stark difference in rated 

power block size. While the LFR technology without 

storage finds an optimal power block size at 158 MW e

gross, the thermal storage-heavy molten salt tower finds 

an optimal LCOE with a power block of 55 MW e. The 

high cost of thermal storage per unit energy for the 

Parabolic Trough leads to an LCOE optimum at very 

low storage capacity - one hour - to assist in riding 

through weather transients. Another interesting result 

from the plant design is that the total aperture area for 

the Parabolic Trough and Power Tower technologies is 

approximately the same near 850,000 square meters, 

while the LFR plant requires nearly 40% more aperture 

area to achieve the same annual output. However, the 

compact nature of LFR requires only approximately 1/2

of the land area compared to Parabolic Trough and 1/3

of the land area required for Power Towers. 

If the primary goal of installing a CSP facility is to 

offset fossil fuel generation, then aside from practical 

implementation issues, the most important metric in 

assessing candidate technologies is the LCOE1. However, 

some market environments may value consistent output 

throughout the year, dispatchability, or other 

considerations. Figure 9 shows electric output by month 

for the various technologies. 

Notably, the LFR and Parabolic Trough systems excel 

during summer months compared to Tower technologies 

but are optically inferior during winter months. The 

LFR system nearly coincides with the Trough plant over 

the year even considering the fact that it has 40% more 

aperture area. Thus we conclude (as have others [24] 

that with the significant optical penalty for LFR, 

collector cost must be significantly lower than for other 

1Assuming a flat-rate market without peak production incentives, etc. 

6 
TABLE 3: SUMMARY OF OPTIMIZED INPUT PARAMETERS AND SIMULATION RESULTS 

Description Units LFR PT-DSG PT-MS Trough 

Design gross power output 

Solar multiple 

Design solar field thermal power 

Field aperture area 

Land area 

Hours of thermal storage 

Total installed cost 

MWe

-

MWt

m2

acres 

hr

$M

158 

1.7 

706.4 

1,208,000 

478 

None 

592.3 

140.5 

1.35 

446.3 

886,714 

1,326 

None 

550.1 

55 

3.36 

434.8 

836,075 

1,360 

16 

474.6 

150 

1.46 

580.3 

850,302 

883 

1 

624.3 

Net annual energy 

LCOE (real) 

Average parasitic loss 

Capacity factor 

Annual water usage 

GWe · hr

/kW·hr

% 

% 

m3

299.7 

20.80 

6 

23.0 

31,560 

299.6 

19.22 

6 

25.9 

58,721 

300 

15.34 

9 

68.4 

60,541 

299.7 

21.54 

8 

24.8 

72,237 

Fig. 9: Electric output by month for the systems described in

Table 3.

CSP technologies in order for it to compete. 

4 SUMMARY AND CONCLUSIONS 

This paper presents an overview of the recently added 

LFR model in System Advisor and provides an 

LCOE-optimized plant comparison between various CSP 

technologies. The analysis results show that while LFR 

is cost-competitive with other CSP technologies ­

especially Parabolic Troughs, the leading low-LCOE 

candidate is the molten salt Power Tower. LFR offers a 

number of potential advantages, including low-cost 

collectors and simplified receiver piping that facilitate 

relatively high-temperature operation. Because of the 

low solar field cost, ability to generate steam directly, 

and low land usage, LFR lends itself to integrated solar 

combined cycle (ISCC) projects. 

As grid penetration of renewables increases, thermal 

storage adds value to the electricity a plant generates 

[25]. This seems to encourage LFR to pursue solar fields 

that operate with molten salt or some other medium 

that is compatible with thermal storage. In this regard, 

the System Advisor model will continue development by 

adding a sensible-HTF solar field model in the near 

future. 

ACKNOWLEDGEMENTS 

This work was supported by the U.S. Department of 

Energy under Contract No. DE-AC36-08-GO28308 with 

the National Renewable Energy Laboratory and with 

funding from the Electric Power Research Institute 

under Cooperative Research And Development 

Agreement (CRADA) WRE5-11-430. The author 

gratefully acknowledges support from both EPRI and 

Novatec Solar. 

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8