Spectral analysis of photovoltaic panels

How spectral response and quantum efficiency are used in solar cell analysis?

The spectral response and the quantum efficiency are both used in solar cell analysis and the choice depends on the application. The spectral response uses the power of the light at each wavelength whereas the quantum efficiency uses the photon flux. Converting QE to SR is done with the following formula:

What is the contribution of solar spectrum to photovoltaic performance?

The contribution of the solar spectrum is lower, about 3%. Similarly, Huld and Amillo [ 8] studied the effect of several variables on the performance of photovoltaic panels. They concluded that variations in the solar spectrum received by crystalline silicon cells leads to a performance variation between −5% and +2%.

Do solar panels respond to spectral distribution?

In general, solar panels do not respond to the full AM1.5 spectrum [ 5, 16, 17, 18 ]. The impact of the spectral distribution on energy production varies for each month of the year and decreases as the latitude of the installation site of the photovoltaic modules decreases [ 19 ].

What are spectral features of PV modules?

As the market share of silicon solar cells currently exceeds 90% (Silvestre et al., 2018), this feature can be treated as another main spectral feature of PV modules. The index of average reflectance in the VNIR (aVNIR) (see Fig. 5) targets strong spectral absorption features in the VNIR region of PV materials.

What spectral range does a PV module have?

Common and traditional PV modules have a low average reflectance between 500 nm and 1000 nm (Czirjak, 2017), which is used to absorb more solar energy in this spectral range. For example, monocrystalline PV cells are blackish, and polycrystalline PV cells are dark bluish.

What is physics based solar PV?

This physics-based approach is robust, transferable and operational. Over the past decades, solar panels have been widely used to harvest solar energy owing to the decreased cost of silicon-based photovoltaic (PV) modules, and therefore it is essential to remotely map and monitor the presence of solar PV modules.