PV Mismatch loss study using flash test datasets

Confidential | © 2016 SunPower Corporation
Quantification of System
Level Mismatch Losses
using PVMismatch
Flash test results
Mismatch at STC
Annual Energy Loss due to Mismatch
Authors:
Chetan Chaudhari
Gregory M. Kimball
Raymond Hickey
Ben Bourne

2Confidential | © 2016 SunPower Corporation |
Introduction
• What is Mismatch loss ?
–Differences in the current-voltage characteristics of photovoltaic (PV)
modules connected in series and parallel combinations lead to a loss in the
system level power referred to as “mismatch loss” or “electrical mismatch
loss”.
• Pmpp@system < Pmpp@module

Contributing factors to mismatch loss
• Manufacturing variability
• Shading
• Operating temperature non-uniformity
• Varying DC wiring lengths
• Uneven degradation

Need
• Literature survey shows guidance on mismatch loss from 0.01% to 2%
• Mismatch loss typically used as a flat derating factor for system capacity

Goal
• Create a framework that can be utilized to model various factors that contribute to
mismatch loss for
–a given population of flash test results

Goal
mismatch loss for
–system configuration

Goal
mismatch loss for
–system configuration,
–site location

Goal
mismatch loss for
–system configuration,
–site location
–impact on annual Energy

Quick overview of PVMismatch
• Core framework for the study
• An explicit IV curve calculator
• Written in Python
• Go Open Source! (https://github.com/SunPower/PVMismatch)
• PVMismatch Model chain
–Cell > Cell string > Module > String > System
–Capability to set ”Suns” and temperature for each cell (individually or
collectively)
–Capability to configure cell string layout and bypass diodes
• Former work using PVMismatch
– Accurate Modeling of Partially Shaded PV Arrays [2]
– A fast parameterized model for predicting PV system performance under partial shade conditions. [3]

Datasets behind the study
• Dpvmod1 represents normal distribution
from factory data
• 1000+ unique IV curves from modules
• Dpvmod2 represents a synthesized
multimodal distribution
• 1000+ representative IV curves

Mismatch loss at STC – case study Ns=3 by Nm=8
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Ns = 3
Nm = 8

Calculations
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
P 𝑚𝑝𝑚𝑜𝑑
Ns = 3
Nm = 8

Calculations
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Ns = 3
Nm = 8
𝑃𝑟𝑒𝑓 =
0
𝑁𝑠∗𝑁𝑚
𝑃 𝑚𝑝𝑚𝑜𝑑

Calculations
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
P 𝑚𝑝𝑠𝑦𝑠
Ns = 3
Nm = 8
𝑃𝑟𝑒𝑓 =
0
𝑁𝑠∗𝑁𝑚

Calculations
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
𝑃𝑟𝑒𝑓 =
0
𝑁𝑠∗𝑁𝑚
P 𝑚𝑝𝑠𝑦𝑠
𝑆𝑇𝐶 𝑀𝑖𝑠𝑚𝑎𝑡𝑐ℎ 𝑙𝑜𝑠𝑠 =
𝑃𝑚𝑝𝑠𝑦𝑠 − 𝑃𝑟𝑒𝑓
𝑃𝑟𝑒𝑓
× 100
Ns = 3
Nm = 8

Monte Carlo Simulations
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Simulation 1000
Ns=3 by Nm=8
2 111 2
String1
141 378
8
33
3 988 55
String2
String3
Ns = 3
Nm = 8

Mismatch loss at STC - resulting distribution
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Simulation 1000
Ns=3 by Nm=8
2 111 2
String1
141 3788 33
3 988 55
String2
String3
Mismatch loss
distribution
Ns = 3
Nm = 8

Annual Energy Loss
due to
Mismatch

Annual Energy Loss due to Mismatch (Tucson AZ)
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Ns = 3
Nm = 8

Annual Energy Loss due to Mismatch (Tucson AZ)
Simulation 1
Ns=3 by Nm=8
Tcell = Dry Bulb Temperature (°C)
Suns = normalized GHI (W/m2)
68 111 332
String1
256 3 65
122 999 112
String2
String3
𝐴𝑛𝑛𝑢𝑎𝑙 𝐸𝑛𝑒𝑟𝑔𝑦 𝐿𝑜𝑠𝑠 𝑑𝑢𝑒 𝑡𝑜 𝑀𝑖𝑠𝑚𝑎𝑡𝑐ℎ % =
0
𝑁
𝑃𝑚𝑝𝑠𝑦𝑠 − 0
𝑁
𝑃𝑟𝑒𝑓 × 100
0
𝑁
𝑃𝑟𝑒𝑓
TMY3
Tucson,
AZ
Ns = 3
Nm = 8

Annual Energy Loss due to Mismatch
Annual Energy Loss
due to Mismatch
Simulation 1
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
Simulation 200
Ns=3 by Nm=8
68 111 332
String1
256 3 65
122 999 112
String2
String3
TMY3
Tucson,
AZ
Ns = 3
Nm = 8

Mismatch loss at STC across system sizes
• With non-normal distribution of module characteristics, the mismatch
increases
• Case for importance of binning methods

Concluding remarks
• P95 mismatch loss decreases with system size
• Annual energy loss > STC mismatch loss
• Mismatch loss calculated agrees with other lower estimates found in the
literature
• and is << 1-2% industry practice

Future scope
• Introducing other contributing factors to the mismatch model
–Operating temperature non-uniformity
–Varying DC wiring lengths
–Uneven degradation

Thank You
Let’s change the way our world is powered.

Appendix A

References
1. J. W. Bishop, “Computer simulation of the effects of electrical mismatches in photovoltaic cell interconnection circuits,” Sol. Cells, vol. 25, no.
1, pp. 73–89, Oct. 1988.
2. Meyers, B., & Mikofski, M. (2017). Accurate Modeling of Partially Shaded PV Arrays. In 44th IEEE Photovoltaic Specialists Conference.
3. Meyers, B., Mikofski, M., & Anderson, M. (2016). A fast parameterized model for predicting PV system performance under partial shade
conditions. In Conference Record of the IEEE Photovoltaic Specialists Conference (Vol. 2016–November, pp. 3173–3178). Institute of
Electrical and Electronics Engineers Inc. https://doi.org/10.1109/PVSC.2016.7750251

Method – Mismatch loss at STC
• Select Ns * Nm count of modules from the flash test distribution (Ns = number of strings, Nm = number of
modules in a string)
• Using PVMismatch, generate IV curves for each of the flash test results
• Configure a PV system of desired configuration with Ns strings of Nm modules each
• Calculate mismatch loss at STC using equation 1 and 2
– 𝑃𝑟𝑒𝑓 = 0
𝑁𝑠∗𝑁𝑚
𝑃 𝑚𝑝𝑚𝑜𝑑 1
– 𝑆𝑇𝐶 𝑀𝑖𝑠𝑚𝑎𝑡𝑐ℎ 𝑙𝑜𝑠𝑠 =
𝑃 𝑚𝑝𝑠𝑦𝑠− 𝑃 𝑟𝑒𝑓
𝑃 𝑟𝑒𝑓
× 100 (2)
• Pref is the sum of module level powers each at its maximum power point
• Pmpsys is the system level power of the configuration at the system’s maximum power point
• Repeating this method for 1000 unique scenarios yields a distribution of mismatch losses for
each PV system configuration

PV Mismatch loss study using flash test datasets

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