Assessing the impact of PV panel climate-based degradation rates on inverter reliability in grid-connected solar energy systems.

This paper provides an evaluation of a 4-kW grid-connected full-bridge PV inverter under three different scenarios to assess its reliability with a fixed PV degradation rate, with a climate-based degradation rate, and without considering PV degradation. The climate-based degradation rates are estimated using a physics-based model that considers the different parameters influencing the PV reliability. Three different locations representing three different climate zones (hot and dry, hot and humid, and moderate climates) have been chosen in this study. The estimated lifetime of the IGBT, the switching device in the PV inverter, varies depending on the location, with the inclusion of fixed and climate-based degradation rates extending the lifespan of the PV inverter in the examined locations. The results demonstrate the significant impact of PV climate-based degradation rates on power electronics' reliability assessment and the importance of considering various factors in predicting device failures. To ensure the PV inverter's lifespan over the desired period in areas with high solar irradiation rates and extremely hot climates, the design parameters should be slightly elevated above the standard value.

Electrical data of 10W, 40W, 80W, and 250W photovoltaic modules under the aging condition: Tested by a Solar Manufacturer Company in Bangladesh.

The health monitoring system of photovoltaic modules throughout their lifespan is an important research topic. The dataset of aged PV modules is required to investigate the performance of the aged PV array for simulation work. Different aging factors are responsible for decreasing the output power of aged PV modules and increasing the degradation rate. In addition, mismatch power losses are increases with the nonuniformity of aged PV modules due to different aging factors. In this work, four datasets of 10W, 40W, 80W, and 250W PV modules are collected under nonuniform aging conditions. Each dataset contains forty modules with a four-year aged average. The average deviation of each electrical parameter of the PV modules can be calculated from this data. Moreover, a correlation can be developed between the average deviation of electrical parameters and mismatch power loss in PV array modules under early aging conditions.