Investigation on Different Bypass Diodes for Shade Resistant PV-Modules

The SegmentPV project focuses on developing photovoltaic modules for residential buildings, addressing challenges such as partial and dynamic shading through a collaboration between AESOLAR and the Fraunhofer Center for Silicon Photovoltaics (CSP). The design process encompasses various aspects, including the selection of the bill of materials (BOM), lamination processes, types of photovoltaic (PV) cells, interconnections, and bypass diodes. To understand the electrical, thermal, and structural requirements and challenges, this study investigates a selection of state-of-the-art and alternative bypass diodes. A primary goal is to determine the diode parameters essential for creating a digital twin, specifically a SPICE model, to simulate partial shading effects. Partial shading of a single PV cell can lead to substantial power losses in the entire substring connected in series. For example, older designs with 60 cells and three substrings may suffer a 33% power loss if one cell is shaded, whereas modern butterfly designs reduce this to one-sixth of the module's power. This research explores various string designs to further minimize losses, requiring a detailed examination of bypass diode requirements, including I-V characteristics, power losses, reverse breakdown voltage, thermal behavior, and form factors for in-laminate designs. Alternatives to conventional Schottky diodes, such as silicon diodes, field-effect diodes, and active bypass diodes, are also evaluated. Ten different diodes suitable for bypass applications were selected. Four-point measurements using a programmable source meter were conducted to determine I-V characteristics, with temperature-dependent I-V curve tracing performed on a subset. Diode parameters, including saturation current (Is), ideality factor (n), and series resistance (Rs), were extracted, and their temperature dependencies in the Shockley equation were characterized. The results provide insights for robust diode characterization and highlight temperature dependencies critical for accurate simulations.