The document discusses optimization of PV plant design based on analysis of performance data from 50 PV plants in India totaling 2GW of installations. It finds that CUF (capacity utilization factor) varies significantly between plants from 12.2% to 21.3% despite similar conditions, and that top performing plants have a CUF 6% higher than average. Further analysis shows performance is impacted not just by panels and inverters but also factors like civil works, string/combiner boxes, transformers, and mounting structures. The document advocates taking a holistic design approach and using performance ratio in addition to CUF for improved plant monitoring and optimization.
2. Performance Data
• For this presentation
• Sample of 50 plants
operational for at least
one year in Gujarat
• 28 with c-Si and 22 Thin
Film
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3. This is how the data
tables look like
?
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5. Frequency Distribution CUF Values
16
Highest CUF
21.3%
Lowest CUF
12.2%
14
6
3
2
3
3
2
1
0
12% to 13% 13.1% to 14% 14.1% to 15% 15.1% to 16% 16.1% to 17% 17.1% to 18% 18.1% to 19% 19.1% to 20% 20.1% to 21% Above 21%
The Difference:
Absolute: 9.1% | Factor: 1.75
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6. Frequency Distribution CUF Values
16
14
6
3
2
3
3
2
1
0
12% to 13% 13.1% to 14% 14.1% to 15% 15.1% to 16% 16.1% to 17% 17.1% to 18% 18.1% to 19% 19.1% to 20% 20.1% to 21% Above 21%
Top Performers vs. All Others
94.00%
6%
92.00%
60.00%
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8%
40%
8. No, it is not!
“Nevertheless, the PV systems evaluable per region showed
significant deviations in their respective yields. Although located
in a similar environment, the yield variation in some regions was
up to 20 %. Assessment of the quartiles revealed 75 % of the
plants underperforming compared to the top performing
plants. Another 5 % were included in the group of outliers
due to their overall yield being too low for this study. The
significance test proves that, due to the sufficiently high number
of evaluable PV plants, the statistical results of our study reflect
the actual yields of the PV systems to a high degree.”
- Source: Survey on yield of photovoltaic plants 2012 in Germany
by Meteocontrol (Prof. Dr. Henirk te Heesen et al.
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10. CUF vs. Technology
9
7
Note:
There are 28 c-Si, but
only 22 Thin Film
installations in this
sample!
7
7
5
3
2
1
1
1
1
2
1
1
1
1
0
12% to 13% 13.1% to 14% 14.1% to 15% 15.1% to 16% 16.1% to 17% 17.1% to 18% 18.1% to 19% 19.1% to 20% 20.1% to 21% Above 21%
Thin Film
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c-Si
11. CUF vs. Technology II
12% to 13% 13.1% to 14% 14.1% to 15% 15.1% to 16% 16.1% to 17% 17.1% to 18% 18.1% to 19% 19.1% to 20% 20.1% to 21% Above 21%
Thin Film
Bottom line:
There are very good and not so good
performing plants either with Thin Film
or c-Si!
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c-Si
13. CUF vs. Average Installed Capacity
17.55
15.40
14.59
11.73
11.67
14.14
11.67
10.22
6.67
12% to 13% 13.1% to 14% 14.1% to 15% 15.1% to 16% 16.1% to 17% 17.1% to 18% 18.1% to 19% 19.1% to 20% 20.1% to 21% Above 21%
Average Installed Capacity
Bottom line:
Do larger / smaller plants perform better?
One thing is for sure: The sample of 50
plants is too small to give an answer.
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14. ?
So what can we learn
from this?
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15. A Skeptical Thesis
• We do not have enough information, because
• Generation Data and CUF do not provide the
right or enough insights
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16. ?
Why have we done this
exercise?
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17. Reasons
• #1: To understand better the limitations of CUF and
generation data
• #2: To build awareness that there might be a
problem & that there is room for improvement
• #3: Not specific to India – happens also in Germany
/ Europe so it affects the whole industry
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18. CUF: What goes into the
equation…
• Units generated
• Installed Capacity
• Time (e.g. 1 year)
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CUF
Energy Measured (kWh )
Installed Capacity(kW ) 8760 h
19. CUF: What goes not into
the equation…
• Ambient
Temperature
• Panel Temperature
• Irradiation at Project
Site
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• Grid related aspects
• Availability
• Frequency
20. PR: A Different Approach
• Instead of asking:
What was achieved
without asking
about the frameconditions and
circumstances
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• Ask:
What could have
been achieved
considering all the
frame conditions?
21. Comparison of CUF and PR for a PV System in Germany
(2012)
77.58%
81.54%
78.90%
78.63%
76.00%
75.90%
72.03%
74.42%
76.39%
19%
21%
78.32%
10%
14%
21%
19%
February
March
April
May
June
July
Performance Ratio [%]
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3%
9%
4%
January
70.60%
4%
25%
18%
72.80%
August
CUF [%]
September
October
November December
22. Takeaways
• #1: Great components do not automatically lead to
high performing plants
• #2: Design has a huge impact (but not only
electrical design!)
• #3: CUF is a good tool but will not provide the
complete picture
• #4: PR is also a tool for quality management
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24. Component
Capacity
Nos Installed
Plant
Capacity Lost
Chance of
Detection
1 Panel
250Wp
4000
0.025%
“0”
1 String
5kWp
200
0.5%
Not very likely
1 SCB
50kWp
20
5%
Possible
1 Inverter
500kW
2
50%
Likely
1 Transformer
1000kW
1
100%
Most likely
*1MW plant – not a real application; simplified for illustration
Design for Reliability
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27. Min. Performance and Typical Performance of c-Si Panels vs. Time in Operation
(Aging Process)
100%
98%
96%
94%
92%
90%
88%
86%
84%
82%
80%
0
5
10
Min. Performance
15
20
Typical Performance
Performance of Panels
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25
28. Simplified Output Power vs. Ambient Temperature
120
Standardized Output Power
100
80
60
Temperature
De-Rating
40
20
0
0
10
20
30
40
50
Ambient Temperature
Performance of Inverter
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60
70
29. Is focusing on Panels
and Inverters enough?
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41. Conclusion
• Plant Efficiency
• EPCs and Owners Engineers – educate your clients about
plant efficiency (PR vs. CUF)
• Quality Control
• Install and use a SCADA system to monitor and document
the plant performance
• System Deployment
• Deploy a system – focus on all design aspects (not only
electrical, but also civil)
• Share
• Share your generation and performance data to set a
benchmark
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43. Contact Us
REACH Solar Consulting P Ltd.
S3 Team Business Center
98 V M Street, Mylapore
Chennai 600004
India
c/o CHROSIS UG
Hallerstrasse, 27
74549 Wolpertshausen
Germany
madhavan@reach-solar.com
sebastian@reach-solar.com
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