BIPV (Building Integrated Photovoltaic) supplemented the minimum area problem required when installing existing solar modules. However, in order to apply it to buildings, research was needed to increase the aesthetics of solar modules and use them as a design. Accordingly, modules with color applied to the entire surface of the photovoltaic module were being developed, but there was a disadvantage of low power. Therefore, by dividing and bonding the cell strips, it was possible to improve the output power by applying a shingled technology in which other divided cells overlap in a busbar region where light couldn't be received. Shingled technology was advantageous for color modules because the front busbar part that degrades aesthetics was removed. In this research, four color shingled solar modules (Green, Yellow, Blue, Gray) were manufactured and power degradation was analyzed by measuring transmittance and reflectance. Gray color had 80.83% transmittance, which was 31.31% higher than Yellow, resulting in a power difference of 4.45 W.

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

c-Si solar cells currently account for more than 90% of the solar energy market. Research on tandem junction solar cells to overcome efficiency limitations is drawing attention at a time when new technologies are being developed to secure the price competitiveness of silicon solar cells. Among several candidate materials for silicon-based tandem solar cells, perovskite has recently been studied as it is suitable for the ease of process as well as for its properties as a tandem solar cell material. In this study, we want to review the research trends and technology limitations of 2-T Perovskite/SHJ tandem junction solar cells.

The screen-printing method is the most mature solar cell fabrication technology, which has the advantage of being faster and simpler process than other printing technology. A front metallization printed through screen printing influences the efficiency and manufacturing cost of solar cell. Recent technology development of crystalline silicon solar cell is proceeding to reduce the manufacturing cost while improving the efficiency. Therefore, screen printing requires process development to reduce a line width of an electrode and decrease shading area. In this paper, we will discuss the development trend and prospects of screen-printing metallization using metal paste, which is currently used in manufacturing commercial crystalline silicon solar cells.