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  "Title": "Data Driven I-v Feature Extraction",
  "Description": "The Data Driven I-V Feature Extraction is used to extract\nCurrent-Voltage (I-V) features from I-V curves. I-V curves\nindicate the relationship between current and voltage for a\nsolar cell or Photovoltaic (PV) modules. The I-V features such\nas maximum power point (Pmp), shunt resistance (Rsh), series\nresistance (Rs),short circuit current (Isc), open circuit\nvoltage (Voc), fill factor (FF), current at maximum power (Imp)\nand voltage at maximum power(Vmp) contain important information\nof the performance for PV modules. The traditional method uses\nthe single diode model to model I-V curves and extract I-V\nfeatures. This package does not use the diode model, but uses\ndata-driven a method which select different linear parts of the\nI-V curves to extract I-V features. This method also uses a\nsampling method to calculate uncertainties when extracting I-V\nfeatures. Also, because of the partially shaded array, \"steps\"\noccurs in I-V curves. The \"Segmented Regression\" method is used\nto identify steps in I-V curves. This material is based upon\nwork supported by the U.S. Department of Energy’s Office of\nEnergy Efficiency and Renewable Energy (EERE) under Solar\nEnergy Technologies Office (SETO) Agreement Number\nDE-EE0007140. Further information can be found in the following\npaper. [1] Ma, X. et al, 2019.\n<doi:10.1109/JPHOTOV.2019.2928477>.",
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      "title": "Damp Heat Plus Dynamic Mechanical Load Indoor Accelerated Test I-V Curve.",
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        "This information is based off the following paper.X. Ma, W. Huang, E. Schnabel, M. Köhl, J. Brynjarsdóttir, J. L. Braid, and R. H. French. “Data-Driven I–V Feature Extraction for Photovoltaic Modules.” IEEE Journal of Photovoltaics 9, no. 5 (September 2019): 1405–12. https://doi.org/10.1109/JPHOTOV.2019.2928477.",
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