- As solar capacity increases, better understanding performance in the field is needed as PV systems often underperform models due to various factors like defects, installation issues, and weather events. - Novel methods are required to characterize field performance as current approaches have limitations due to signal-to-noise ratios in production and weather data. - Remote performance analysis and on-site inspection/testing provide different insights and both play a role in properly diagnosing underperformance through high-resolution data analysis and visualization of system issues.

1. Novel Methods for Characterizing the
Performance of Operating PV Systems
Brian Grenko
Chief Executive Officer
October 20, 2015

2. As the installed capacity of solar matures, so does our
understanding of how to characterize its performance
2
U.S. Cumulative Installed Solar Production Capacity
0
2
4
6
8
10
12
14
16
18
20
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
CumulativeInstalledCapacity,GW
Source: Greentech Media

3. But we are years behind other sources of power when
it comes to understanding field performance
3
U.S. Cumulative Installed Production Capacity of Various Non-Fossil Fuels
Source: Greentech Media, EIA (US DOE)
0
10
20
30
40
50
60
70
80
90
100
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
CumulativeInstalledCapacity,GW
Solar Wind Hydro Nuclear

4. The reality is that PV systems do not perform as modeled,
in part due to modeling variation…
4
Range in Estimate Values For Various Energy Simulation Input Parameters
Source: SolarPro Magazine, Sep/Oct ‘15

5. Millions of PV modules have been
recalled in recent years due to defects in
design, materials, and workmanship
…and also because things can and do go wrong in the field
Equipment Quality
Most industry experts agree that quality
of system design and installation is the
leading indicator of long-term system
performance
Design & Installation
Damage from lightning strikes is among
the top reasons why PV modules fail
prematurely, and is difficult to detect
Site Events/Issues
5

6. Problem: IV curve tracing confirmed underproduction at this installation
located close to the Aegean Sea, and field EL imaging identified potential-
induced degradation (PID) as the root cause of underperformance.
Value: Opportunity cost of lost production ≈$9,200/yr (and increasing).
Our Solution: Coordinated warranty claim with PV module manufacturer to
replace product, and recommended $900 charge mitigation device proven
to prevent PID from reoccurring on similar floating ground configurations.
Complex system-level performance issues like PID
reinforce the need for a holistic, field-based approach
6
Case Study: Potential-Induced Degradation (PID)
Location Paros, Greece
System Size 102kWAC
Owner Land Owner (Consumer)
Issue Noted 1 Year After Installation
400
300
200
100
0
Ground
-100
-200
-300
-400
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
String Position
16
8
14
1

7. What is the value of underperformance?
7
Commercial Rooftop
Morristown, NJ
Assuming $0.12/kWhr offset
and $0.20/kWhr SREC value,
256 MWhr/year
10%
Production loss
$34,250
5 Year NPV
0.2 MW
Industrial Ground-Mount
Concord, NC
Assuming $0.05/kWhr PPA rate,
2,821 MWhr/year
5%
Production loss
$29,500
5 Year NPV
2 MW
Utility 1-Axis Tracking
Rosamond, CA
Assuming $0.05/kWhr PPA rate,
46,275 MWhr/year
1%
Production loss
$96,500
5 Year NPV
20 MW
Small changes in performance can make a big difference in utility-scale plants

8. Efforts to better characterize field performance have been
limited mainly by problems with signal-to-noise ratio
8
Resolution Measurement Error Cost

9. 9
What are some novel ways to address these challenges?
Remote Performance Analysis Site Inspection & Testing

10. Performance audits can be done remotely but require
good data and a methodical approach to data processing
10
Scrubbing: Before key performance indicators
can be calculated, production and weather data
must be processed to account for:
• Bad data (duplicates, time shifts, errors)
• Downtime events (full and partial)
• Met station issues (drift, shading, error)
• Filtration (irradiance, variation, etc.)
Insights: Analysis of residuals, among other
methods, helps to visualize problems that may
otherwise go undetected
• Correlation coefficients
• Modeled/measured run charts
• Frequency distribution
True Up: Based on actual performance results,
Proforma energy simulation input parameters
can be corrected for more accurate forecasting
• Tilt and azimuth
• Thermal and IAM values
• .PAN file
Software should be able to analyze data at any sampling frequency or time period
Full System Downtime
Partial
Downtime
Pyranometer
Shading
Array
Shading

11. Problem: Shortly after installation, system production was noted to be
underperforming expectations by over 4%, and getting worse with time
Value: Opportunity cost of lost production ≈$25,000/yr (and increasing)
Our Solution: Comparing production data to as-built drawings and images
revealed that inter-row shading was improperly modeled by system design
team; presented alternative PV module stringing configuration options
A meticulous approach can sometimes identify root causes
of underperformance without ever traveling to the site
11
Case Study: Inter-Row Shading
Location Norfolk County, England
System Size 8 MWDC
Owner Independent Power Producer
Issue Noted 2 Months After Installation

12. Onsite inspection and testing enables a more
granular approach to PV module characterization
12
Rapid Thermography
Efficiency: UAV with GPS receiver enables pre-site mission
planning and minimizes time and labor in the field
Insights: Analysis at PV module level reveals parasitic
losses and potential safety issues not otherwise found
Automation: Post-processing software recognizes defect
types and stitching images together

13. Problem: During commissioning process, Buyer discovered PV module frame
drilling as result of rushed construction and poorly designed carport system.
Our Solution: Amplify team conducted on-site analysis including mass IR
imaging and EL testing on representative sample. Results compared with
field IV testing and analysis of production data to validate extent of damage.
Value: Analysis enabled PV module manufacturer to extend original
warranty so project sales transaction could be completed.
Sometimes remote analysis can be misleading; on-site
visual inspection is a simple and meaningful exercise
13
Case Study: PV Module Frame Drilling
Location Los Angeles County, CA
System Size 650 kWAC
Seller Commercial Developer
Issue Noted 1 Month After Installation

14. 4/25/2016
- Solar is still young
- PV Modules often don’t perform as expected
- Even small improvements can mean big savings
- A proper diagnosis requires the proper tools
14

15. 4/25/2016
15
Amplify Energy evaluates and improves the performance
of PV systems in order to maximize financial returns for
owners, buyers, and developers
Inspection & Testing Consulting Services
 Acquire, clean, and process
production and weather data
 Compare actual vs. expected
performance and identify gaps
 Ability to “true-up” production
model for revenue forecasting
Performance Analysis
 Comprehensive suite of on-site
test capabilities (IR, EL, IV, etc.)
 Indoor PV module durability and
characterization test laboratory
 72kW rooftop array designed for
outdoor exposure testing
 Performance optimization
 Forensic engineering and RCA
 Field repair of PV modules
 Warranty administration
 Technology review

16. Thank you!
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