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Problem Statement: Mismatch

Module Mismatch

Module mismatch significantly lowers the energy production of even the most perfect PV arrays.  Research shows that mismatch typically represents 4-7% energy loss in a new, unshaded commercial array, with increasing losses over time. 

Mismatch occurs due to many variables including manufacturing variance, thermal gradients within an array, uneven surface soiling, cloud shading and edge effects, failed bypass diodes, voltage drop in conductors, variable cell degradation, and accumulated module wear and tear.  Tigo’s optimization solution provides innovative technology to identify and rectify issues of mismatch, thus increasing the performance of any solar array.

Three Major Types of Mismatch

Cloud Cover and Refraction

Clouds create shade patterns that reduce the productivity of modules.  Additionally, as clouds move away from an array, they produce a phenomenon known as “cloud edge effect,” which actually creates a spike in energy production. In the case of edge effects, the array not only gets direct sunlight from the clear sky above it, it receives additional sunlight reflected through the white patch directly next to the patch of clear sky.  Mismatch from clouds can result in as much as 5-8% energy loss in places like Hawaii.

  

Here we see the difference in irradiance a site can experience just from clouds passing overhead.  This data, collected by NREL, shows that the annual standard deviation at this particular Oahu site was 15.4% just from cloud coverage.  This corresponds to a 5-8% loss of energy due to mismatch

Variable Degradation 

As silicon modules degrade over time, they do so at different rates.  In the first year of operation, a significant number of modules show degradation patterns between 0% and 1%.  In five years this will lead to a 5% difference in power production between modules throughout the entire array.  A smaller (but not trivial) portion of modules show degradation rates between 1% and 4% per year; within five to ten years, these modules will be significantly underperforming their peers (by as much as 20-40%), and will negatively impact system power production.

This figure illustrates the results of more than 200 PV modules recently subjected to reliability testing at PV Evolution labs

 

Manufacturing Mismatch

Crystalline structures have inherent differences, meaning that no two solar cells are ever identical.  In order to manage this problem, manufacturers “bin” modules based on range of power, which is typically ±3%.  While binning helps reduce the problems associated with manufacturing inconsistencies, they still represent a significant and measurable source of module mismatch.

 

Conclusion

The collective impact of the sources of mismatch typically represents a 4-7% loss in a new array.  However, these losses can be reduced by using module-level power electronics, such as the Tigo Optimizer System. By keeping each module working at its individual peak power point, a module-level power maximization system can increase the energy output of any solar array.  In addition, module-level data helps system owners spot anomalies or system failures as soon as they happen—and often diagnose the type of failure before even going onsite. 

 

To learn more, see our Quantifying Mismatch whitepaper below.

 

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