.

National Renewable Energy Laboratory

1617 Cole Boulevard, Golden, Colorado 80401-3393 

303-275-3000 • www.nrel.gov

Operated for the U.S. Department of Energy 

Office of Energy Efficiency and Renewable Energy 

by Midwest Research Institute • Battelle 

Contract No. DE-AC36-99-GO10337 

B. Marion, J. Adelstein, and K. Boyle 

National Renewable Energy Laboratory 

H. Hayden, B. Hammond, T. Fletcher, B. Canada, 

and D. Narang 

Arizona Public Service Co. 

D. Shugar, H. Wenger, A. Kimber, and L. Mitchell 

PowerLight Corporation 

G. Rich and T. Townsend 

First Solar 

Prepared for the 31st IEEE Photovoltaics Specialists 

Conference and Exhibition 

Lake Buena Vista, Florida 

January 3-7, 2005 

February 2005 • NREL/CP-520-37358 

Performance Parameters for 

Grid-Connected PV Systems 
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Performance Parameters for Grid-Connected PV Systems 

B. Marion,1

 J. Adelstein,1 K. Boyle,1 H. Hayden,2 B. Hammond,2 T. Fletcher,2 B. Canada,2 D. Narang,2 

D. Shugar,3

 H. Wenger,3 A. Kimber,3 L. Mitchell,3 G. Rich,4 and T. Townsend4

1 National Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 80401 2 Arizona Public Service Co., 1500 E. University Dr., Tempe, AZ 85281 3 PowerLight Corporation, 2954 San Pablo Ave., Berkeley, CA 94702 4 First Solar, 4050 E. Cotton Center Blvd. #6-68, Phoenix. AZ 85040 

ABSTRACT

The use of appropriate performance parameters

facilitates the comparison of grid-connected photovoltaic

(PV) systems that may differ with respect to design, 

technology, or geographic location. Four performance

parameters that define the overall system performance 

with respect to the energy production, solar resource, and

overall effect of system losses are the following: final PV

system yield, reference yield, performance ratio, and

PVUSA rating. These performance parameters are

discussed for their suitability in providing desired

information for PV system design and performance

evaluation and are demonstrated for a variety of

technologies, designs, and geographic locations. Also

discussed are methodologies for determining system a.c.

power ratings in the design phase using multipliers 

developed from measured performance parameters. 

INTRODUCTION 

Accurate and consistent evaluations of photovoltaic

(PV) system performance are critical for the continuing

development of the PV industry. For component

manufacturers, performance evaluations are benchmarks

of quality for existing products. For research and

development teams, they are a key metric for helping to

identify future needs. For systems integrators and end

customers, they are vital tools for evaluating products and

product quality to guide future decision-making. 

As the industry has grown, a clear need has arisen for

greater use of and education about appropriate industrystandard performance parameters for PV systems. These

performance parameters allow the detection of operational

problems; facilitate the comparison of systems that may 

differ with respect to design, technology, or geographic

location; and validate models for system performance

estimation during the design phase. Industry-wide use of 

standard performance parameters and system ratings will

assist investors in evaluating different proposals and

technologies, giving them greater confidence in their own

ability to procure and maintain reliable, high-quality 

systems. Standard methods of evaluation and rating will 

also help to set appropriate expectations for performance 

with educated customers, ultimately leading to increased

credibility for the PV industry and positioning it for further

growth. 

Parameters describing energy quantities for the PV

system and its components have been established by the

International Energy Agency (IEA) Photovoltaic Power 

Systems Program and are described in the IEC standard

61724 [1]. (IEA task members have used these

performance parameters to develop a database of

operational and reliability performance [2]. The database

contains information for several hundred PV systems and

may be viewed at www.task2.org.) 

Three of the IEC standard 61724 performance

parameters may be used to define the overall system

performance with respect to the energy production, solar

resource, and overall effect of system losses. These 

parameters are the final PV system yield, reference yield,

and performance ratio. 

The final PV system yield Yf is the net energy output

E divided by the nameplate d.c. power P0 of the installed

PV array. It represents the number of hours that the PV 

array would need to operate at its rated power to provide 

the same energy. The units are hours or kWh/kW, with the

latter preferred by the authors because it describes the

quantities used to derive the parameter. The Yf normalizes

the energy produced with respect to the system size;

consequently, it is a convenient way to compare the 

energy produced by PV systems of differing size: 

0

f P

E Y = (kWh/kW) or (hours) (1) 

The reference yield Yr is the total in-plane irradiance

H divided by the PV’s reference irradiance G. It represents 

an equivalent number of hours at the reference irradiance.

If G equals 1 kW/m2

, then Yr is the number of peak sunhours or the solar radiation in units of kWh/m2

. The Yr

defines the solar radiation resource for the PV system. It is

a function of the location, orientation of the PV array, and 

month-to-month and year-to-year weather variability:

G

H Yr = (hours) (2) 

1
The performance ratio PR is the Yf divided by the Yr. 

By normalizing with respect to irradiance, it quantifies the

overall effect of losses on the rated output due to: inverter

inefficiency, and wiring, mismatch, and other losses when

converting from d.c. to a.c. power; PV module

temperature; incomplete use of irradiance by reflection

from the module front surface; soiling or snow; system

down-time; and component failures: 

r

f

Y

Y PR = (dimensionless) (3) 

PR values are typically reported on a monthly or

yearly basis. Values calculated for smaller intervals, such

as weekly or daily, may be useful for identifying

occurrences of component failures. Because of losses due

to PV module temperature, PR values are greater in the

winter than in the summer and normally fall within the

range of 0.6 to 0.8. If PV module soiling is seasonal, it

may also impact differences in PR from summer to winter. 

Decreasing yearly values may indicate a permanent loss

in performance.

The PVUSA rating method [3] uses a regression

model and system performance and meteorological data

to calculate power at PVUSA Test Conditions (PTC), 

where PTC are defined as 1000 W/m2

 plane-of-array

irradiance, 20°

C ambient temperature, and 1 m/s wind

speed. PTC differs from standard test conditions (STC) in 

that its test conditions of ambient temperature and wind

speed will result in a cell temperature of about 50°C,

instead of the 25°C for STC. This is for a rack-mounted PV

module with relatively good cooling on both sides of the

module. For PV modules mounted close to the roof or

integrated into the building with the airflow restricted, PTC

will yield greater cell temperatures. Nordmann and 

Clavadetscher [4] report that PV module temperatures rise

above ambient for fielded system ranging from 20°C to

52°C at 1000 W/m2

, with the largest temperature rise for

an integrated façade. The difference between the 

nameplate d.c. power rating and the system PVUSA rating

is an indication of the total system losses associated with

converting d.c. module energy to a.c. energy. As with

decreasing PR values, decreasing PVUSA ratings over

time may indicate a permanent loss in performance. 

D.C. AND A.C. RATINGS 

The Yf is calculated by dividing the energy yield 

recorded with a utility kWh meter by the nameplate d.c.

power rating. The nameplate d.c. power rating is 

determined by summing the module powers listed on the

nameplates on the backsides of the individual PV modules

in the PV array. The PV module power ratings are for STC

of 1000 W/m2

 solar irradiance and 25°C cell temperature.

Besides being easily determined, the nameplate d.c. 

power rating’s use in the equation for Yf offers the 

advantage, as compared to the use of an a.c. power rating

or conditions other than STC, of differentiating between

systems with different d.c. to a.c. conversion efficiencies

or different mounting-related PV module temperature 

environments. For example, if performance was with

respect to an a.c. power rating, two systems might report 

the same Yf, but have significantly different inverter

efficiencies, or other loss mechanisms. Similarly, if 

performance was with respect to PTC, two systems might

report the same Yf, but have significantly different PV

module temperature-related losses because of how the

PV modules are mounted or integrated into the building. 

Although a nameplate d.c. power rating is used in Yf

to report the normalized energy produced by an existing

system, an a.c. power rating is essential when attempting 

to predict the energy a PV system will produce using

models such as PVWATTS [5], PVDesignPro [6], or

PVGRID [7]. Accurate energy predictions are crucial to the

continued development of the photovoltaic industry 

because they set the investor’s expectations for system 

performance and the associated economic return. The

remainder of this section discusses a.c. power ratings and

considerations in their determination. 

PV systems may be assigned a.c. power ratings by

accounting for: (1) losses in converting from d.c. to a.c.

power, and (2) operating cell temperatures that are usually

greater than 25°C. In the first case, the nameplate d.c. 

power rating is multiplied by empirically determined derate

factors to calculate an a.c. power rating at STC. In the 

second case, an additional derate can be applied for 

temperature other than STC. Finally, the PVUSA rating

method may be used to assign an a.c. rating to an existing

system with historical data. 

To evaluate the accuracy of our empirical derate

factors, PVUSA ratings were determined for 24

PowerLight PV systems (twenty single-crystalline silicon,

two multicrystalline silicon, and two amorphous silicon)

located throughout the United States. These ratings were

then compared to the a.c. ratings for the same systems

calculated by using the derate method and the derate

factors from Table 1. All derate factors in Table 1 were

estimated from measured losses and component

specifications. The typical overall derate factor at nominal

operating cell temperature (NOCT) is 0.731, representing

a loss of 26.9% from the nameplate d.c. rating. 

Table 1. Derate Factors for A.C. Power Rating 

Item Typical Range

PV module nameplate d.c. rating 1.00 0.85 – 1.05 

Initial light-induced degradation 0.98 0.90 – 0.99 

d.c. cabling 0.98 0.97 – 0.99 

Diodes and connections 0.995 0.99 – 0.997 

Mismatch 0.98 0.97 – 0.985 

Power-conditioning unit (inverter) 0.96 0.93 – 0.96 

Transformers 0.97 0.96 – 0.98 

a.c. wiring 0.99 0.98 – 0.993 

Soiling 0.95 0.75 – 0.98 

Shading 1.00 0.0 – 1.00 

Sun-tracking 1.00 0.98 – 1.00 

Availability of system 0.98 0.0 – 0.995 

Overall at STC 0.804 0.62* – 0.92 

Temperature (at NOCT = 45°C) 0.91 

Overall at NOCT 0.731 

*Does not include soiling, shading, tracking, or availability losses 

2
For the initial comparison, all “typical” derate factors

from Table 1 were used, except for the temperature derate

factors that were determined using the manufacturers’

power correction factors for temperature and NOCTs of 

45°C. The results of the comparison using this derate

method are shown in Fig. 1. The derate method a.c. 

ratings were as much as 19% greater than the PVUSA

rating, and the standard deviation of the differences was

7%. In Fig. 1, the measured loss is the difference between

the nameplate d.c. rating and the PVUSA rating. The 

design loss is the difference between the nameplate d.c. 

rating and the a.c. rating calculated using the derate

method. For an accurate design, the measured loss and

design loss will be very close. The measured and design

losses are expressed as percentages for ease of

comparison. 

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

Overall Manufacturer 1 -

Single Crystalline

Manufacturer 2 -

Single Crystalline

Manufacturer 3 -

Single Crystalline

Manufacturer 4 -

Single Crystalline

Manufacturer 5 -

Multi- Crystalline

Manufacturer 5 -

Amorphous

System Loss

Average Measured Loss (% difference between the Array DC Rating and the PVUSA rating)

Design Loss (% difference between the Array DC Rating and the Design AC Rating from Derate Factors)

Fig. 1. Design and measured losses using typical derate factors,

except for the temperature derate factor, which was manufacturer

specific. 

Current-voltage (I-V) curve testing of PV modules

used in these 24 systems revealed that the accuracy of 

the nameplate ratings varied by manufacturer, and for

certain manufacturers the accuracy varied by product. 

Some PV modules produced as much as 4% more than

specified, whereas others were as much as 12% less than

specified [8]. 

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

Overall Manufacturer 1 -

Single Crystalline

Manufacturer 2 -

Single Crystalline

Manufacturer 3 -

Single Crystalline

Manufacturer 4 -

Single Crystalline

Manufacturer 5 -

Multi- Crystalline

Manufacturer 5 -

Amorphous

System Loss

Average Measured Loss (% difference between the Array DC Rating and the PVUSA rating)

Design Loss (% difference between the Array DC Rating and the Design AC Rating from Derate Factors)

Fig. 2. Design and measured losses using typical derate factors,

except for the temperature derate factor and the PV module

nameplate d.c. rating derate factor, which were manufacturer

specific. 

Consequently, for the second comparison, results

were significantly improved by using a derate factor to

account for the accuracy of the manufacturer’s nameplate

d.c. ratings, as detailed in the first row of Table 1.

Compared to the PVUSA ratings, the a.c ratings

calculated using a derate method including a factor for

manufacturer’s nameplate rating were within ±5%, with a

standard deviation of the differences of 2%. Figure 2

illustrates these results. Although not evaluated, still better

agreement might have been achieved by using systemspecific derate and NOCT values instead of typical values. 

INFLUENCE OF WEATHER 

Variations in solar radiation and ambient temperature

from month-to-month and year-to-year influence the

performance parameters. Therefore, it is important to

identify which performance parameters are suitable for

which system evaluations based on their weatherdependence. The Yf is influenced the most because of its

dependency on solar radiation. The PR is influenced less

because values are normalized with respect to solar

radiation, but values are influenced by seasonal variations

in temperature. The PVUSA a.c power ratings at PTC are 

influenced the least because the method performs the

regression using solar radiation, ambient temperature, and 

wind speed values. Small variations in PVUSA method

a.c power ratings can be attributed to the range of values

over which the regression is performed, nonlinearities in

PV module and inverter performance, and variations in

solar spectrum. 

To illustrate the extent to which the performance

parameters might be influenced by weather, PV system

performance was modeled using PVFORM [9] for a 30-

year period. The hourly solar radiation and meteorological

data input to PVFORM was for the Boulder, CO, station in

the National Solar Radiation Data Base [10]. PV system

specifications were the same as the PV system located on

the roof of the Solar Energy Research Facility (SERF) at

the National Renewable Energy Laboratory (NREL):

single-crystalline silicon PV modules, nameplate d.c. 

power rating of 7420 W, PV array tilt angle of 45°, and PV 

array azimuth angle of 22° east of south. Using modeled, 

instead of measured, data permitted the influence of

weather to be evaluated over a longer period of time and

eliminated the need to carefully screen erroneous data or

data collected when the system was inoperative, or to

account for any performance degradation that occurred. 

Using the modeled data for the 30-year period, 

monthly and yearly performance parameters and PVUSA

a.c power ratings at PTC were calculated. The results are

shown in Fig. 3. If weather had no influence, the values

would all reside on a horizontal line, but that is clearly not 

the case. As expected, Yf shows the greatest variability

and the PVUSA a.c power rating at PTC shows the least. 

Although not shown, the variability of Yr is similar to Yf

because of Yf’s dependence on solar irradiance. PR

values exhibit the influence of temperature, with smaller

values in summer than winter. For yearly values, 95%

confidence intervals, determined as twice the standard

3
deviations, are shown. The confidence interval of ±8.4%

for Yf means that 95% of the yearly values should be

within 8.4% of the average yearly value. As indicated by

the scatter of data, monthly values are more variable,

resulting in greater confidence intervals than for the yearly

values. Although PR varies from summer to winter, the

yearly values are consistent with a confidence interval of

±1.2%, which is only slightly greater than the confidence

interval of ±0.7% for yearly values of PVUSA a.c power

ratings at PTC. (Because the PVUSA ratings are

determined using a month of data, the yearly value was

determined as the average of the 12 monthly values.)

Consequently, both PVUSA a.c power ratings at PTC and

yearly PR values should be able to detect degradation of

system performance over time. 

J F M A M J J A S O N D Yr

3000

4000

5000

6000

PV

U

S

A

Rating (Wac)

0.5

0.6

0.7

0.8

0.9

PR

3

4

5

Yf (kWh/kW/day)

95% Confidence Interval for Yearly Values = Average 8.4%

95% Confidence Interval for Yearly Values = Average 1.2%

95% Confidence Interval for Yearly Values = Average 0.7%

Fig. 3. Monthly and yearly Yf, PR, and PVUSA a.c power rating at 

PTC from PV performance data modeled over a 30-year period

show the influence of weather variability.

EXAMPLE RESULTS FOR Yf

Arizona Public Service Co. operates numerous gridconnected PV systems within its service territory [11]. 

Table 2 contains a listing of some of these systems and

their Yf values for the 12-month period of September 2003

through August 2004. Because the solar resource (Yr) is

greater for the single-axis tracking systems, their Yf values

are larger than those for the non-tracking systems. 

For the single-axis tracking systems, Fig. 4 shows monthly 

and yearly Yf values for the 12-month period. Yf values

were largest for the Airport MTA2 and the Yucca power

plant systems, primarily because their PV modules’

performance met their nameplate expectations. The other

systems performed at a lower level because of a

combination of factors: PV module performance, inverter

efficiency, and operational problems. Specifically, for the

Airport MTB1 system, the inverter operated poorly until

August, when all its performance issues had been

resolved. The Gilbert Nature Center system experienced

frequent inverter faults, and in August a conductor failed,

rendering the system inoperable or operating at reduced

power for most of the month. 

Table 2. Arizona Public Service PV Systems and Their Yf for 

September 2003 Through August 2004. 

System Name Location Size 

(kWdc) 

Yf

(kWh/kW)

Single-Axis Tracking, North-South Horizontal Axis 

Embry Riddle Prescott 228.50 1906 

Gilbert Nature Ctr. Tempe/Mesa 144.00 1682 

Ocotillo 1 Tempe 94.47 1806 

Airport MTA2 Prescott 121.00 2118 

Airport MTA7 Prescott 151.20 1882 

Airport MTB1 Prescott 151.20 1406 

Airport MTB2 Prescott 151.20 1807 

Airport MTB3 Prescott 151.20 1861 

Airport MTB5 Prescott 117.60 1869 

Water Tanks-East Scottsdale 153.60 1986 

Water Tanks-West Scottsdale 144.00 2020 

Yucca Pwr. Plant Yuma 121.00 2147 

Non-Tracking, Horizontal 

Star Parking Tempe 5.04 1345 

Non-Tracking, South-Facing with Tilt Equal to Latitude

Challenger Peoria 2.28 1593

Desert Lake Pleasant 2.28 1461

The Yf normalizes performance with respect to

system size; consequently, it is useful for comparing 

systems of different size to quantify benefits of design,

components, or locations. But unlike the PR, the Yf values

do not correct for the variability of solar radiation, and

therefore, are not as useful for identifying operational

problems. The exception is side-by-side operation of

systems of identical design, such as the Arizona Public

Service single-axis trackers at the Prescott airport. For this

situation, we can assume that all systems have essentially

the same solar resource (Yr), and that any operational

problem may be detected by comparing a system’s Yf 

S O N D J F M A M J J A Yr

0

100

200

300

400

Month Yf (kWh/kW)

0

1000

2000

3000

4000

Year Yf (kWh/kW)

 Embry Riddle  Airport MTB2 Gilbert Nature Ctr Airport MTB3

Ocotillo 1 " Airport MTB5

Airport MTA2 ' Water-Tanks East Airport MTA7 ( Water-Tanks West

 Airport MTB1 3 Yucca Pwr. Plant

2003 2004

Fig. 4. Monthly and yearly Yf for Arizona Public Service singleaxis trackers for September 2003 through August 2004. 

4
against that of the other systems. For a single system, a 

similar strategy might be used by dividing it into two or

more subsystems, with each having their own inverter and

a.c. metering. 

EXAMPLE RESULTS FOR PR

The PR is a dimensionless quantity that indicates the

overall effect of losses on the rated output. By itself, it 

does not represent the amount of energy produced,

because a system with a low PR in a high solar resource

location might produce more energy than a system with a

high PR in a low solar resource location. However, for any

given system, location, and time; if a change in component

or design increases the PR, the Yf increases accordingly.

PR values are useful for determining if the system is

operating as expected and for identifying the occurrence 

of problems due to inverter operation (faults/failures, peakpower tracking, software/control), circuit-breaker trips, 

solder-bond failures inside PV module junction boxes,

diode failures, inoperative trackers, shading, snow, soiling, 

long-term PV system degradation, or other failures. Large

decreases in PR indicate events that significantly impact

performance, such as inverters not operating or circuitbreaker trips. Small or moderate decreases in PR indicate

that a less severe problem exists. The PR can identify the

existence of a problem, but not the cause. The cause of 

the problem requires further investigation, which may 

include a site visit by maintenance personnel. Decreases

in PR from soiling or long-term PV system degradation

may not be readily evident unless viewed over months, or

years in the case of the latter. Decreases from soiling are

site- and weather-dependent, with greater soiling (up to

25% for some California locations) for high-traffic, highpollution areas with infrequent rain. 

For 2001, Fig. 5 presents daily, weekly, and monthly 

PR values for the NREL SERF PV system described in a

previous section. For most of the year, the PR values are

consistent with those modeled for the same system and 

shown in Fig. 1. But for winter and spring months, PR

values are lower for days coinciding with 

J F M A M J J A S O N D

0.0

0.2

0.4

0.6

0.8

1.0

PR

Monthly

Weekly

Daily

Fig. 5. Daily, weekly, and monthly PR values for the NREL SERF

PV system for 2001. 

logbook entries reporting snowfall and for three days in

February when the system was off. Depending on the 

amount of snow, daily PR values as low as zero occurred. 

The influence of snow is also evident in the weekly and

monthly PR values, but to a lesser extent. 

As an example of using PR to measure long-term

changes in performance, Fig. 6 presents—for three PV 

systems—the linear least-square fits of monthly PR values

over a period of several years. For comparison, results 

using the PVUSA method are also shown. Both methods

show similar degradation rates, even though they use

somewhat different input data. Whereas the calculation of

PR uses all values of irradiance, the PVUSA method

restricts irradiance values to 800 W/m2

 or above. To

examine only the effects of long-term performance 

changes, both methods excluded data when the a.c. 

power value indicated the system was not operating. If

instead the intent had been to evaluate overall system

performance, data would not have been excluded and

values would have been less. The results depicted in Fig.

6 are an example of using PR to measure performance

changes over time, and are not meant as a definitive

analysis of a PV technology’s long-term performance for

Denver or any other location. The relative performance of 

the three systems was influenced by using inverters with 

different conversion efficiencies 

1994 1998 2002 2006

0.4

0.5

0.6

0.7

0.8

0.9

1.0

PR

4000

5000

6000

7000

8000

PVUS

A Rating (Wac

Single-crystal Si PV System, 7420 W )

dc

 PR, degradation = 0.9% per year PVUSA, degradation = 1.3% per year

0.4

0.5

0.6

0.7

0.8

0.9

1.0

PR

800

1000

1200

1400

PVUS

A Rating (Wac

CdS/CdTe PV System, 1200 W )

dc

 PR, degradation = 1.2% per year PVUSA, degradation = 1.4% per year

0.4

0.5

0.6

0.7

0.8

0.9

1.0

PR

800

1000

1200

1400

PV

U

S

A Rating (Wac

a-Si/a-Si/a-Si:Ge PV System, 1224 Wdc )

 PR, degradation = 1.5% per year  PVUSA, degradation = 1.1% per year

Fig. 6. Long-term degradation rates for three PV systems at

NREL from monthly values of PR and PVUSA ratings. Upper

regression lines from monthly PR values shown by + symbols. 

Lower regression lines from monthly PVUSA values shown by ∆

symbols.

5
and operating characteristics. Also, the reliability of these

small systems may not be representative of that of larger 

systems, and performance changes may have been

different if tested in a different climate or location. For the

system using the a-Si/a-Si/a-Si:Ge PV modules, data

collection began after being deployed for several months 

and their initial performance degradation had occurred. 

SUMMARY AND FUTURE WORK 

Three performance parameters may be used to define

the performance of grid-connected PV systems: final PV

system yield Yf, reference yield Yr, and performance ratio 

PR. The Yf and PR are determined using the nameplate

d.c. power rating. The Yf is the primary measure of

performance and is expressed in units of kWh/kW. It 

provides a relative measure of the energy produced and

permits comparisons of PV systems of different size, 

design, or technology. If comparisons are made for

different time periods or locations, it should be recognized

that year-to-year variations in the solar resource will

influence Yf. The PR factors out solar resource variations

by dividing Yf by the solar radiation resource, Yr. This 

provides a dimensionless quantity that indicates the

overall effect of losses and may be used to identify when 

operational problems occur or to evaluate long-term

changes in performance. As part of an operational and

maintenance program, the PR may be used to identify the

existence of performance issues. 

To further encourage the use of common reporting

and design practices for PV systems, future activities

should include: (1) additional work to gain support for an

industry-standard set of performance parameters and

system derating factors, (2) additional measurements for

verifying individual derate factors (e.g., inverter,

transformer, wiring, soiling,). Although using an overall 

derate factor yielded ratings close to that of the PVUSA

method, a better knowledge of the individual derate factors

would provide closer agreement and identify areas to

improve system performance, and (3) development of a

“Buyer’s Guide” to explain performance parameters and

system rating factors to potential investors and describe

which system aspects are the biggest drivers of 

performance (e.g., inverter efficiency, module efficiency, 

reliability, performance degradation rate, system siting). 

REFERENCES 

[1] IEC, “Photovoltaic System Performance Monitoring—

Guidelines for Measurement, Data Exchange, and 

Analysis, IEC Standard 61724,” Geneva, Switzerland, 

1998. 

[2] U. Jahn and W. Nasse, “Performance Analysis and

Reliability of Grid-Connected PV Systems in IEA 

Countries,” Proceedings of the 3rd World Conference on

PV Energy Conversion, Osaka, Japan, 2003. 

[3] R. Dows, “PVUSA Procurement, Acceptance, and 

Rating Practices for Photovoltaic Power Plants,” PG&E

Co. Report #95-30910000.1, Sept. 1995. 

[4] T. Nordmann and L. Clavadetscher, “Understanding

Temperature Effects on PV System Performance,”

Proceedings of the 3rd World Conference on PV Energy

Conversion, Osaka, Japan, 2003. 

[5] B. Marion and M. Anderberg. “PVWATTS—An Online

Performance Calculator for Grid-Connected PV Systems,”

Proceedings of the ASES Solar 2000 Conference, June 

16-21, 2000, Madison, WI. 

[6] “PVDesign Pro User’s Manual,” Maui Solar Software

Corporation, 1988. 

[7] H. Wenger, “PVGrid User’s Manual,” PowerLight

Corporation, 1990. 

[8] A. Detrick, A. Kimber, and L. Mitchell, “Performance

Evaluation Standards for Photovoltaic Modules &

Systems,” Proceedings of the 31st IEEE Photovoltaic

Specialists Conference, Lake Buena Vista, FL, 2005 (in

press).

[9] D. Menicucci and J. Fernandez, “User’s Manual for

PVFORM: A Photovoltaic System Simulation Program for

Stand-Alone and Grid-Interactive Applications,” SAND85-

0376, Albuquerque, NM: Sandia National Laboratories, 

1988. 

[10] NSRDB Vol. 1, “User’s Manual—National Solar

Radiation Data Base (1961-1990),” Golden, CO: National 

Renewable Energy Laboratory, 1992. 

[11] L. Moore, H. Post, H. Hayden, S. Canada, and D.

Narang, “Photovoltaic Power Plant Experience at Arizona

Public Service: A 5-Year Assessment,” Progress in

Photovoltaics: Research and Applications 2005; (in press). 

6
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4. TITLE AND SUBTITLE

Performance Parameters for Grid-Connected PV Systems 

5c. PROGRAM ELEMENT NUMBER

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NREL/CP-520-37358 

5e. TASK NUMBER

PVC57101 

6. AUTHOR(S) 

B. Marion, J. Adelstein, K. Boyle, H. Hayden, B. Hammond, 

T. Fletcher, B. Canada, D. Narang, D. Shugar, H. Wenger,

A. Kimber, L. Mitchell, G. Rich, and T. Townsend 

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7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

National Renewable Energy Laboratory, 1617 Cole Blvd., Golden, CO 

80401-3393 

 Arizona Public Service Co., 1500 E. University Dr., Tempe, AZ 85281 

PowerLight Corporation, 2954 San Pablo Ave., Berkeley, CA 94702 First Solar, 4050 E. Cotton Center Blvd. #6-68, Phoenix. AZ 85040 

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14. ABSTRACT (Maximum 200 Words)

The use of appropriate performance parameters facilitates the comparison of grid-connected photovoltaic (PV) 

systems that may differ with respect to design, technology, or geographic location. Four performance parameters that 

define the overall system performance with respect to the energy production, solar resource, and overall effect of 

system losses are the following: final PV system yield, reference yield, performance ratio, and PVUSA rating. These 

performance parameters are discussed for their suitability in providing desired information for PV system design and 

performance evaluation and are demonstrated for a variety of technologies, designs, and geographic locations. Also 

discussed are methodologies for determining system a.c. power ratings in the design phase using multipliers 

developed from measured performance parameters.

15. SUBJECT TERMS

PV; performance parameters; grid-connected systems; energy production; solar resource; system yield; reference 

yield; performance ratio; PVUSA rating; a.c. power ratings 

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