Abstract

The All India Survey of Photovoltaic Module Reliability 2014 is an enhanced version of the survey conducted in the previous year, with detailed characterization of PV modules including current-voltage, infrared and electroluminescence imaging, visual inspection, insulation resistance test and interconnect breakage test. More than a thousand modules were inspected in the field and the main results of the survey are presented in this paper. The average Pmax degradation rate for the so-called ‘good’ modules (Group X) is 1.33%/year which is higher than that commonly projected by manufacturers, and widely employed in financial calculations. Modules falling in the ‘not-so-good’ category (Group Y) show even higher degradation rates, and it is at least partly due to higher number of micro-cracks in the modules, and increased degradation of the packaging materials like encapsulant, backsheet, etc. Modules in ‘Hot’ climates degrade faster than modules in the ‘Non-Hot’ climates. Degradation in fill factor is the primary cause for performance degradation in the young modules (ages <5 years), whereas short-circuit current degradation is the main contributor to power degradation in the older modules. Small installations (<100 kWp capacity) show higher degradation than large systems, which may be partly due to lack of proper due diligence by the owner at the time of procurement and installation.

Abstract

As machine learning potentials for molecular dynamics (MD) simulations, Spectral Neighbor Analysis Potential (SNAP) and quadratic SNAP (qSNAP) were constructed for silicon (Si) and silicon carbide (SiC). The reproducibility of the basic material properties about perfect crystal, free surface and dislocation cores in Si and 3C-SiC was investigated. The coefficients of SNAP and qSNAP were optimized using liner regression to present energy and force obtained by DFT. In addition, hyperparameters (cutoff length and weights for optimization, here) were determined using genetic algorithm to reproduce elastic moduli obtained by DFT. Lattice constant and elastic moduli of Si crystal by MD using our SNAP or qSNAP agree well with the values of DFT, and they have higher accuracy than those by any empirical potential. Additionally, melting point and specific heat at constant pressure were calculated by MD correctly. Especially in qSNAP of Si, the surface energy of {100} and {111} planes and the reconstructed {100} surface structure were almost reproduced. For 3C-SiC, SNAP reproduces lattice constant and elastic moduli of DFT. Furthermore, edge dislocation cores were generated successfully. However, the potentials we constructed have insufficient reproducibility in the plastic region, so it is necessary to continue development.