On Field Infrared Thermography Sensing for PV System Efficiency Assessment: Results and Comparison with Electrical Models The evaluation of photovoltaic (PV) systemxe2x80x99s efficiency loss, due to the onset of faults that reduce the output power, is crucial. The challenge is to speed up the evaluation of electric efficiency by coupling the electric characterization of panels with information gathered from module diagnosis, amongst which the most commonly employed technique is thermographic inspection. The aim of this work is to correlate panelsxe2x80x99 thermal images with their efficiency: a xe2x80x9cthermal signaturexe2x80x9d of panels can be of help in identifying the fault typology and, moreover, for assessing efficiency loss. This allows to identify electrical power output losses without interrupting the PV system operation thanks to an advanced PV thermography characterization. In this paper, 12 faulted working panels were investigated. Their electrical models were implemented in MATLAB environment and developed to retrieve the ideal IV characteristic (from ratings), the actual (operative) IV characteristics and electric efficiency. Given the curves shape and relative difference, based on three reference points (namely, open circuit, short circuit, and maximum power points), faultsxe2x80x99 typology has been evidenced. Information gathered from infrared thermography imaging, simultaneously carried out on panels during operation, were matched with those from electrical characterization. Panelsxe2x80x99 xe2x80x9cthermal signaturexe2x80x9d has been coupled with the xe2x80x9celectrical signaturexe2x80x9d, to obtain an overall depiction of panelsxe2x80x99 health status.

A SemiEmpirical Model of PV Modules Including Manufacturing IV Mismatch This paper presents an analysis of the impact of manufacturing variability in PV modules when interconnected into a large PV panel. The key enabling technology is a compact semiempirical model, that is built solely from information derived from datasheets, without requiring extraction of electrical parameters or measurements. The model explicits the dependency of output power on those quantities that are heavily affected by variability, like short circuit current and open circuit voltage. In this way, variability can be included with Monte Carlo techniques and tuned to the desired distributions and tolerance. In the experimental results, we prove the effectiveness of the model in the analysis of the optimal interconnection of PV modules, with the goal of reducing the impact of variability.