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Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A. Klein, Professor Doug Reindl

Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

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Page 1: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

Modeling Cell Temperature and

Performance of Photovoltaic Systems

Ty Neises

Solar Energy Lab, UW-Madison

Professor S.A. Klein, Professor Doug Reindl

Page 2: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

2

Motivation for Adaptable Cell Temperature Model

Cell temperature affects panel efficiency:

PV performance models typically require cell temperature inputs.

The mounting of a panel can vary and affects the cell temperature.

Open rack

BIPV

Roof Integrated

Page 3: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

3

Steady State Energy Balance

Ground temperature

Open rack:

BIPV: amb cellAVE(T ,T )3 33

total forced freeh = h +h

abs conv,c conv,b rad,sky,c rad,sky,b rad,ground,c rad,ground,b mpS q q +q q q +q P

conv,cqconv,bq

rad,sky,cqrad,sky,bq

rad,ground,cq

rad,ground,bq

ambTskyT

groundT

cellT

groundT

ambT

skyT

absS

mpP

ambT

Absorbed radiation: HDKR model

Sky Temperature: Berdahl and Martin (1984)

Turbulent forced convection: Schlichting (2000)

Free convection: Raithby and Holland (1998)

Combining forced and free convection:

Power: 5-parameter model

Duffie and Beckman (2006)

Page 4: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

4

Validation Data

Building Integrated

NIST, Maryland

South wall vertical mounting, backside insulated

Mono-Si, 6 mm glass cover

Poly-Si, ETFE cover

Wind speed measured near panel

Open Rack

Sandia (NM) mono-Si panel

NREL (CO) HIT panel

Fixed tilt = latitude

Page 5: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

5

Additional Cell Temperature Models Evaluated

Duffie and Beckman (2006)

,

-- 9.5

- 5.7 3.8

mpcell amb

NOCT amb NOCT NOCT

S PT T

T T u S

cell amb m T

0.32T = T + G

8.91+2u

1 T ambT = G ×exp a+b×u +T

Tcell 1

T,ref

GT = T + T

G

Skoplaki (2008)

where ωm is dependent on the mounting of the panel

King (2004)

where a, b, and ΔT are empirically (mounting and panel specific) determined

coefficients.

Page 6: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

6

Cell Temperatuure Model Comparison:

Skoplaki vs. Duffie and Beckman

Assumptions and Inputs

Duffie & Beckman Skoplaki i

Installed NOCT Open-rack NOCT = 47

C

Mounting coefficient, ω = 2.4

Calculated Absorbed Radiation τα=0.9

Calculate power output from

5-parameter model Constant cell efficiency = 0.12

5.7 3.8h u8.91 2h u

Page 7: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

7

Simulation Procedure

Filter data, create hourly datasets

Apply selected cell temperature model

Input predicted cell temperature into

5-parameter PV performance model

Compare predicted to measured

power output

Iterate with calculated

maximum power, if necessary.

Page 8: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

8

Annual Simulation Results

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

7

Sandia NREL NIST - mono-Si NIST - poly-Si

Steady StateSteady State

Duffie and BeckmanDuffie and Beckman

SkoplakiSkoplaki

KingKing

Measured TemperatureMeasured Temperature

En

erg

y P

red

icti

on

Err

or

[%]

Measured Backside (not cell) Temperature

Input to 5-parameter model

RMSEPmp = 6.27% RMSEPmp = 10.7% RMSEPmp = 10.2% RMSEPmp = 10.2%

Page 9: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

9

Summary of Simulation Results

5-parameter model with measured cell temperature results in

<4.5% annual energy prediction error.

All cell temperature model results for open rack panels are

consistent and accurate when compared against 5-parameter

model with measured temperature (backside) input.

Greatest divergence of cell temperature model results

observed for BIPV panels.

Skoplaki & Duffie and Beckman results become less accurate.

Why?

Page 10: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

10

Explanation of Cell Temperature Model Divergence

Hypothesis: For integrated mountings, measured NOCT

becomes a less accurate estimate of cell temperature at testing

conditions.

Mounting conditions become more difficult to

replicate/predict

Correction factor chart becomes less accurate

Open Rack - Sandia Open Rack - NREL BIPV (mono-Si) BIPV (poly-Si)

Assumed NOCT (Skoplaki) [C] 47 47 85 85

Reported NOCT [C] 46 44 67 62

Predicted NOCT [C] 42 43 78 74

Standard Deviation [C] 2.6 1.9 9.0 11.2

Page 11: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

11

NOCT Correction Factor Plots

IEC NOCT Correction Factor

5 10 15 20 25 30 350.25

0.5

0.75

1

1.25

1.5

1.75

Ambient Temperature [C]

Win

d S

peed

[m

/s]

-7

-6

-5

-4

-3

-2

-1

0

12

3

45

6

7

8

5 10 15 20 25 30 350.25

0.5

0.75

1

1.25

1.5

1.75

Ambient Temperature [C]

Win

d S

peed

[m

/s]

-2

-1

0

1

2

3

Predicted c.f.

chart for open

rack mono-Si

Predicted c.f.

chart for BIPV

mono-Si

Correct Factor @ 1.75 m/s, 5

C:

IEC: 0-1°C

Predicted: 6-7°C

Page 12: Modeling Cell Temperature and Performance of Operating ......Modeling Cell Temperature and Performance of Photovoltaic Systems Ty Neises Solar Energy Lab, UW-Madison Professor S.A

12

Recommendations

NOCT values for integrated mountings are difficult to measure

and may be inaccurate due to

Correction factor charts

Inability to measure NOCT under intended mounting conditions

Improve model prediction by

Report actual conditions during NOCT test

Develop and use correction factor chart specific to panel mounting