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23 heliolytics aerial inspection pvpmc 2017-05-09

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8th PVPMC Workshop, May 9-10 2017

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23 heliolytics aerial inspection pvpmc 2017-05-09

  1. 1. Aerial inspections and DC O&M optimization Rob Andrews CEO, Heliolytics rob.andrews@heliolytics.com Megan Mattes Heliolytics 1
  2. 2. Company overview • Heliolytics specializes in aerial infrared audits of PV assets • Inspections of 3.5 GW+ of projects across North America • Operates on commercial rooftop to large scale utility assets • Use proprietary manned aircraft sensor systems and analysis software 2
  3. 3. 3 Hot Junction Boxes Sub-Module Faults String Outs 3 Aerial inspections • Can detect all module defect modes causing significant energy loss in a system • Can be a replacement for manual DC preventative maintenance scopes, including I-V tracing, manual IR, etc.
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  5. 5. Analysis tools • The critical part of aerial inspection is proper post- processing and analytics • It is important to be able to repeatibly detect What and Where faults are in a system • Heliolytics has developed software which produces a spatial database of the exact fault type and location in an array • This data can be integrated into SCADA systems, providing high granularity information on DC capacity losses
  6. 6. 6 Average measured DC capacity loss
  7. 7. Summary results • 1.6 GW subset of data representing systems from commercial to utility scale • Sites with faults >10% excluded • Average across all sites: 1.2% • This represents an energy weighted DC capacity loss • Does not include the effects of DC clipping • The majority of losses causing energy issues were related to string faults
  8. 8. Summary Data • Faults have a wide distribution: • Many sites have low fault rates • The tails are long- some sites have serious serial issues not visible to traditional tools • But, if a system is a high DC/AC ratio, does a 1-2% DC capacity loss affect yearly output?
  9. 9. 9 DC Clipping
  10. 10. DC clipping • Most systems have more DC capacity than AC capacity • Optimizes AC infrastructure, interconnect, development costs, etc. • A system in Phoenix, AZ will spend ~20% of daylight hours in a clipping mode So: If 20% of the time the system is clipping, why do we care if we loose 1% DC capacity? One year of time series modelled performance data, Phoenix, AZ ----- Potential System production ----- Actual System production
  11. 11. DC clipping • Looking at it another way: How much energy is lost on a yearly basis? • For a 1.3 DC Over-rate system, 2.6% of potential energy is lost due to clipping. • So: If we have a 1% DC capacity loss, how much will translate to yearly energy loss? ----- System production ----- Clipping loss
  12. 12. DC clipping factor • Define: DC Clipping Factor • Ratio of DC capacity loss that translates to yearly energy loss 𝐷𝐶 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑙𝑜𝑠𝑠 % 𝑌𝑒𝑎𝑟𝑙𝑦 𝑒𝑛𝑒𝑟𝑔𝑦 𝑙𝑜𝑠𝑠 %
  13. 13. Methodology • Modelled using SAM • Easy to configure • Good parametric analysis interface • <1hr resolution possible • High accuracy • Using up sampled (5min) TMY data • Important to properly model clipping transitions • High quality geographically distributed 5 minute data hard to obtain • DC capacity decreased while AC capacity maintained constant Location Module Name DC to AC Ratio Desired Array Size (kWhdc) Tracking Mode Capacity Loss % System Energy Gross AC (kWh) Energy loss Energy loss ratio Specific Production (kwh/kw) Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.3 13000Fixed 0% 24349200 1873 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.287 12870Fixed 1% 24155800 0.8% 79% 1877 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.274 12740Fixed 2% 23955400 1.6% 81% 1880 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.261 12610Fixed 3% 23750600 2.5% 82% 1883 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.248 12480Fixed 4% 23540000 3.3% 83% 1886 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.235 12350Fixed 5% 23322500 4.2% 84% 1888 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.222 12220Fixed 6% 23100700 5.1% 85% 1890 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.209 12090Fixed 7% 22872400 6.1% 87% 1892 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.196 11960Fixed 8% 22641100 7.0% 88% 1893 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.183 11830Fixed 9% 22405500 8.0% 89% 1894 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.17 11700Fixed 10% 22168400 9.0% 90% 1895 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.157 11570Fixed 11% 21929500 9.9% 90% 1895 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.144 11440Fixed 12% 21687600 10.9% 91% 1896 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.131 11310Fixed 13% 21445600 11.9% 92% 1896 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.118 11180Fixed 14% 21201200 12.9% 92% 1896 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.105 11050Fixed 15% 20957400 13.9% 93% 1897 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.092 10920Fixed 16% 20711800 14.9% 93% 1897 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.079 10790Fixed 17% 20467100 15.9% 94% 1897 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.066 10660Fixed 18% 20222300 16.9% 94% 1897 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.053 10530Fixed 19% 19975900 18.0% 95% 1897 Upsampled USA AZ Phoenix (TMY2) Trina Solar TSM-315PD14 1.04 10400Fixed 20% 19730700 19.0% 95% 1897
  14. 14. DC clipping factor North America • Data for Fixed and Tracking systems • 1% accumulated losses • Assorted cities in North America • Eg. A new 1.3 over-rate system with 1 axis tracking in Phoenix has a DC clipping factor of 0.67. So, the first 1% DC capacity loss would reduce yearly energy yield by 0.67% 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Fixed Tilt Upsampled Canada ON Toronto (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA CA San Diego (TMY2) Upsampled USA CA San Francisco (TMY2) Upsampled USA CO Denver Intl Ap (TMY3) Upsampled USA FL Orlando Intl Arpt (TMY3) Upsampled USA HI Honolulu (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2) Upsampled USA OR Portland (TMY2) Upsampled USA PR San Juan (TMY2) Upsampled USA TX Austin (TMY2) 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1 Axis Tracking Upsampled Canada ON Toronto (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA CA San Diego (TMY2) Upsampled USA CA San Francisco (TMY2) Upsampled USA CO Denver Intl Ap (TMY3) Upsampled USA FL Orlando Intl Arpt (TMY3) Upsampled USA HI Honolulu (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2) Upsampled USA OR Portland (TMY2) Upsampled USA PR San Juan (TMY2) Upsampled USA TX Austin (TMY2)
  15. 15. DC clipping factor Global • Data for Fixed and Tracking systems • 1% accumulated losses • Assorted global cities 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Fixed Tilt Upsampled Canada ON Toronto (INTL) Upsampled Chile CHL Santiago (INTL) Upsampled El Salvador SLV Ilopango S_Salvador (INTL) Upsampled India IND Madras (INTL) Upsampled India IND New_Delhi (INTL) Upsampled United Kingdom GBR London Gatwick (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2) 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1 Axis Tracking Upsampled Canada ON Toronto (INTL) Upsampled Chile CHL Santiago (INTL) Upsampled El Salvador SLV Ilopango S_Salvador (INTL) Upsampled India IND Madras (INTL) Upsampled India IND New_Delhi (INTL) Upsampled United Kingdom GBR London Gatwick (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2)
  16. 16. DC clipping factor Effect of accumulated losses • As losses accumulate, system becomes more exposed to DC losses and clipping factor increases 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1% Losses Upsampled Canada ON Toronto (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA CA San Diego (TMY2) Upsampled USA CA San Francisco (TMY2) Upsampled USA CO Denver Intl Ap (TMY3) Upsampled USA FL Orlando Intl Arpt (TMY3) Upsampled USA HI Honolulu (TMY2) Upsampled USA MA Worchester (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2) Upsampled USA OR Portland (TMY2) Upsampled USA PR San Juan (TMY2) Upsampled USA TX Austin (TMY2) 0.00% 20.00% 40.00% 60.00% 80.00% 100.00% 120.00% 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 10% losses Upsampled Canada ON Toronto (INTL) Upsampled USA AZ Phoenix (TMY2) Upsampled USA CA San Diego (TMY2) Upsampled USA CA San Francisco (TMY2) Upsampled USA CO Denver Intl Ap (TMY3) Upsampled USA FL Orlando Intl Arpt (TMY3) Upsampled USA HI Honolulu (TMY2) Upsampled USA MA Worchester (TMY2) Upsampled USA NC Raleigh (TMY2) Upsampled USA NJ Newark (TMY2) Upsampled USA OR Portland (TMY2) Upsampled USA PR San Juan (TMY2) Upsampled USA TX Austin (TMY2)
  17. 17. DC clipping and system aging • As the system collects faults, production will fall below the clipping threshold more often, magnifying the effects of losses • Eg. A 4 year old system will have accumulated degradation of ~2%-2.8%. Adding 1% of DC capacity loss means that the DC clipping factor is goes from 67% to 72% 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1 1.05 1.1 1.2 1.3 1.4 DCClippingfactor DC Over-rate Phoenix AZ- DC Clipping factor as a function of DC over-rate and accumulated losses 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% 11.00% 12.00% 13.00% 14.00% 15.00% 16.00% 17.00% 18.00% 19.00% 20.00% Siteaccumulatedlosses
  18. 18. Conclusions • Minor DC capacity losses translate to energy yield losses, even for systems with high DC/AC ratios • Maintenance of DC capacity is important for system yield optimization • The buffer created by a low DC clipping factor is a valuable resource, and is generally already accounted for in financial models • Therefore DC capacity losses can be quantified and remediation can be budgeted
  19. 19. 19 Questions? Rob Andrews Rob.Andrews@heliolytics.com

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