NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Improvements to PV

System Modeling in SAM

Sandia/EPRI PV Modeling Workshop

Aron P. Dobos

5 May 2014

2

What’s new in SAM for Photovoltaics?

We’ve been working on a number of projects that will help optimize the design of PV systems and more accurately model their performance.

In 2013, we held a technical review committee that recommended several areas for improvement.

• New “11 parameter” module model using IEC-61853 test data

• Much more flexible inverter models

• Validation work shows SAM and other models are able to predict performance well

• SAM Shade Calculator for 3D scenes

• Historical NSRDB database update for inter-annual variability (P50/P90) analysis

We are thankful for the support of DOE SunShot Systems Integration subprogram that facilitates these efforts.

3

IEC-61853 Module Model (1)

Problem:

• Sandia module model is accurate but requires complex testing, and predicts only 5

points on the IV curve

• 5/6 parameter single diode models can be inaccurate at low irradiances and for

some module technologies

Proposed solution:

• Create a backwards-compatible extension of the single diode model whose

additional parameters can be automatically calculated from IEC-61853 test data.

• Parameters measured at each test condition : Pmp, Vmp Voc, Isc

IRRADIANCE Spectrum Module Temperature

W-m-2 15 C 25 C 50 C 75 C

1100 AM1.5 NA 1000 AM1.5 800 AM1.5 600 AM1.5 400 AM1.5 NA

200 AM1.5 NA

100 AM1.5 NA NA

4

IEC-61853 Module Model (2)

Recall: single diode models consist of two parts:

o The nonlinear I-V curve equation defined by parameters: a, IL, Io, Rs, Rsh

o These five parameters are STC values (@ 1000 W/m2 & 25 C)

o A set of auxiliary equations that translate the five parameters from STC to

operating conditions (temperature & irradiance)

Rs is assumed constant!

OK

OK

OK

?

NOT OK

NOT OK

Egref is fixed at 1.121 eV

5

IEC-61853 Module Model (3)

Observation: the I-V curve equation can fit module

performance data quite well for many technologies. Auxiliary

translation equations for parameters however are not adequate.

Approach: define new auxiliary equations that fit the data better.

Procedure: at each IEC-61853 test condition:

IRRADIANCE Module Temperature

W-m-2 15 C 25 C 50 C 75 C

1100 NA 1000 800 600 400 NA

200 NA

100 NA NA

1. Estimate the diode factor a from Voc &

temperature coefficient

2. Numerically solve for the remaining 4

parameters IL, Io, Rs, Rsh given Pmp, Vmp, Voc, Isc

3. Fit the behavior of these parameters as a

function of temperature and irradiance

6

IEC-61853 Module Model (4)

Result: an 11 parameter model.

For a thin film module, these

parameter values were

obtained from the automated

solution procedure:

Improved auxiliary equations for Rs and Rsh:

7

IEC-61853 Module Model (5)

• For a First Solar thin film module, the

improved model reduces power

prediction error on average from 6.1%

with the 5 parameter model to 1.3%

• Next version of SAM (Autumn 2014)

will include an implementation of the

module model and solver

• This model can help you optimize

system design by having a more

accurate representation of module

performance based on measured test

data

8

Inverter Model Improvements (1)

By default, SAM uses the Sandia Model for Grid-connected Inverters in conjunction with the CEC inverter database.

We’ve added two options:

• Enter inverter weighted efficiency (European or CEC)

• Enter part-load inverter efficiency curve

Model uses operating range inputs to calculate clipping losses.

Voltage ranges are not enforced, but warnings are issued during simulation.

9

Model Validation and Intercomparison (1)

• Validation of SAM model against 9 systems with measured data

• Annual agreement* within ± 3%

• Hourly agreement*: o RMSE within 5.1%

o MBE within ± 1.0%

• Download report: http://www.nrel.gov/docs/fy14osti/60204.pdf

* Mesa Top and DeSoto excluded from these results. Annual numbers based on quality-controlled data, with system downtime, outages, snow hours, etc removed.

10

Model Validation and Intercomparison (2)

Using same measured datasets, compare SAM, PVsyst, PV*SOL, and PVWatts

Notes:

• PVWatts V1 underpredicts on average by 14% with default inputs (not shown)

• PV*SOL does not properly model 1 axis tracking systems

• Many thanks to PVsyst and PV*SOL teams for helping review this work

Full report forthcoming this year

Tool Error ranges for 6 systems

SAM -5.0% to 4.1%

PVsyst -1.7% to 5.5%

PV*SOL -5.5% to 1.4%

PVWatts -16.2% to -8.9%

11

Updated Weather Datasets/Formats (1)

The NREL TMY2 dataset is based on 30 years of measured and modeled hourly solar data from 1961-1990 at 239 locations in the United States.

The underlying actual year data hasn’t been freely available until recently, and there were significant gaps in temperature or other meteorological values which caused simulations to fail.

We’ve applied backfilling algorithms to fill missing data with representative values to enable simulations to run.

https://sam.nrel.gov/NSRDB

We’ve also developed a flexible

Excel-editable CSV-based

standard file format that will be

used in the next version of SAM.

• SAM will include 1619 locations • Much easier to import/edit your own weather files

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New SAM Desktop Application (1)

In Autumn 2014, we will

release a completely

revised SAM desktop

application.

• Significantly streamlines

the user experience

• Much better access to

hundreds of outputs

• Simulations like

parametric and Monte

Carlo analysis will use

parallel processing

• Libraries and weather

data in Excel-editable

CSV files

• Much more powerful

scripting language and

SAM SDK integration

13

Tonight’s Presentation

Upcoming major changes

to PVWatts algorithms

http://pvwatts.nrel.gov

Live demo of SAM Shade

Calculator Beta

http://sam.nrel.gov/shade

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Major Updates to PVWatts

Sandia/EPRI PV Modeling Workshop

Aron P. Dobos

5 May 2014

15

Why Update PVWatts?

• PVWatts V1/V2:

o Originally developed in the

late 90s based on algorithms

derived from performance

data measured in the 80s

• Turns out modern systems

perform better

• Our own validation work

shows that PVWatts

underpredicts

• Pretty consistent feedback

from users that PVWatts

underpredicts

The web tool also gets a

new modern look and feel.

http://pvwatts.nrel.gov

16

Key Model Changes

• Module type options: “Standard”, “Premium”, or “Thin-film”

• Option to specify a DC-to-AC nameplate sizing ratio

• System losses are specified as a percentage, default of 14%.

• Inverter performance curve updated

• One axis tracking systems: linear self-shaded or backtracked

17

Module Types and System Losses

• Default losses are roughly

equivalent to a V1 derate of 0.825,

which is about 7% higher

• Energy prediction is actually about

8-9% higher due to the revised

inverter performance curve.

18

Inverter

• Based on

statistically most

representative

actual inverter in

the CEC database

since 2010

• Nominal efficiency

can be set by the

user, default is 0.96.

19

Performance Summary

Old PVWatts is on average about 11.8% low.

New PVWatts is on average 1.8% low.

Notes: The 9 systems are well maintained and are generally considered

“unshaded”. The default shading loss of 3% in the new PVWatts was set to zero

to match the old PVWatts default.

-20

-15

-10

-5

0

5

10

1 2 3 4 5 6 7 8 9

Annual Energ

y Pre

dic

tio

n E

rro

r (%

)

PVWatts Annual Error for 9 Systems

New PVWatts

Old PVWatts

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What’s Next for PVWatts

• Draft technical manual available online (see survey link

below)

• Online survey to get feedback on these changes

https://www.surveymonkey.com/s/pvwattsv5

• Changes will be finalized and new algorithms will be

rolled out in the next couple of months

NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

SAM Shade Calculator

Sandia/EPRI PV Modeling Workshop

Aron P. Dobos

5 May 2014

22

SAM Shade Calculator Beta

Based on consistent and strong feedback from the user

community and our Technical Review Committee in 2013, the

Department of Energy funded work to develop a 3D shading loss

calculation tool.

Download from: http://sam.nrel.gov/shade

23

SAM Shade Calculator Overview

Our tool will: o Enable basic analysis of shading impacts for a particular scene

o Provide a relatively crude representation of a 3D scene with preprogrammed shapes

o Enable intercomparison of many shading tools

o Be able to read and write common file formats and ideally provide an open standard for PV shading geometry data

Our tool will not: o Render specific modules, racking systems, wiring conduits, or any

details of the balance of system

o Be able to display a realistic rendering or visualization of a particular PV installation

Full roadmap available online.