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Welcome to the PVMismatch wiki!
Please use these pages to engage in discussion about PVMismatch.
Here are some presentations that use PVMismatch.
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A Fast Parameterized Model for Predicting PV System Performance under Partial Shade Conditions by Bennet Meyers at 2016 IEEE 43rd PVSC in Portland, Oregon
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PVMismatch Python Package at 8th PV Performance Modeling Workshop in 2017
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Accurate Modeling of Partially Shaded PV Arrays by Bennet Meyers at 2017 IEEE44th PVSC in Washington, DC
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Quantification of System-Level Mismatch Losses using PVMismatch by Chetan Chaudari in 2018 at WCPEC-7
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A Simplified Method to Approximation Bifacial System Mismatch Losses by Ronda Bailey at NREL 2018 bifiPV 2018 workshop in Denver
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The subtle art of bifacial perfromance modeling for fixed and tracking systems at 2019 PV Systems Symposium (PVPMC 12th)- by Silvana Ayala (NREL)
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Performance modeling of MLPEs at 2019 PV systems symposium (PVPMC 12th) - by Chetan Chaudhari (SunPower)
The most pressing items on the PVMismatch roadmap are as follows:
- Integration with PVLIB-Python. The key to this will be creating an abstract
PVcellso that backend can be set by the user. This would allow the PVLIB-Python 5-parameter model to be used instead of the current 2-cell model already in PVMismatch. - Fixing bugs and adding features. There are a few bugs and many feature requests in PVMismatch that aren't blockers, just a PITA.
- Even more speed improvements. There were massive speed improvements in v0.3.1 thanks to @bmeyers. But we can do even more, see #86 and #60.
The following tips may help you avoid any known issues and eek out some more performance.
- Create a new
pvsys = pvsystem.PVsystem()to set all cells to a new ambient irradiance instead ofpvsys.setSuns(). As system size grows,setSuns()is slower and slower, but creating a new system is always about 0.5[s] thanks to cheap copies.