The large-size chemical vapor infiltration (CVI) of the carbon/carbon (C/C) composite thermal insulation tube is a key component for drawing large diameter monocrystalline silicon rods. However, the CVI densification process is complex, and the cost of experiment optimization is extremely high. In this article, a multi-physics coupling simulation model was established and validated based on COMSOL Multiphysics v.5.6 software to simulate the fabrication process of an isothermal CVI process for a Φ1185 mm C/C composite thermal insulation tube. The influence of process parameters on densification was explored, and a method of optimization was proposed. Our modeling results revealed that the deposition status in areas of low densification was effectively and significantly enhanced after process optimization. At the monitoring site, the carbon density was no less than 1.08 × 10³ kg·m⁻³, the average density of the composite-material thermal insulation tube improved by 5.7%, and the densification rate increased by 26.5%. This article effectively simulates the CVI process of large-sized C/C composite thermal insulation tubes, providing an important technical reference scheme for the preparation of large-sized C/C composite thermal insulation tubes.

The output power of photovoltaic modules is significantly reduced by solar irradiance shading. To address this issue, innovative strategies for mitigating shading effects have been continuously explored. In this study, detailed research on the edge dust accumulation effect of modules has been conducted. It is found that under vertical installation, when the shading ratio reaches 50%, the output power of full-cell modules decreases by 42%, while that of half-cell modules drops by only 27%. Moreover, when the shading ratio reaches 100%, the output power of full-cell modules declines by nearly 99%. In contrast, half-cell modules are still able to maintain nearly 50% of their output power. These results demonstrate that half-cell modules exhibit significantly better resistance to shading compared to full-cell modules. On the other hand, under a horizontal layout, power degradation for both full-cell and half-cell modules is observed to be approximately 16% when the shading ratio is 25%, and around 36% when the coverage reaches 50%. Experimental results further revealed that shading under horizontal orientation leads to a multi-peak power output profile, which poses a risk of the PV inverter being trapped in local maxima. Overall, half-cell modules demonstrated better resistance to dust-induced shading under both layouts. Based on these findings, novel module design schemes are proposed to enhance resistance to dust accumulation effects. The proposed method can effectively reduce power losses caused by edge dust-induced shading and improve the annual power generation of PV modules, thereby offering technical support for effectively enhancing the operational stability of PV power generation systems.

To reveal the degradation mechanism and the formation mechanism of multiple power peaks in photovoltaic modules under irregular shading conditions, this study investigated the performance of full-cell photovoltaic modules through a combination of experimental and simulation approaches. First, the I–V and P–V characteristics of photovoltaic modules under partial and complete shading of photovoltaic cells at different locations were analyzed. The results show that, under local partial shading conditions, the photovoltaic module characteristics are mainly determined by the shaded area, whereas under complete cell shading conditions, the performance degradation primarily depends on the number of bypassed cell strings. A single-diode photovoltaic module simulation model was developed, and the coupling effects of representative partial shading ratios and the number of participating cell strings were analyzed on the MATLAB/Simulink platform. The results indicate that the characteristics of photovoltaic modules under partial shading conditions are jointly governed by the coupling effects of shading ratio and cell-string participation. As the shaded area increases, the degree of electrical mismatch among cells becomes more pronounced, causing the P–V characteristics to evolve from a single-peak profile to a multi-peak profile, accompanied by reduced peak differences and increasingly blurred characteristic boundaries. Through a comprehensive analysis of the simulation and experimental results, it is found that complex shading conditions enhance the multi-peak characteristics of power while causing the peak values to converge. These accompanying features increase the likelihood of multi-peak power points, thereby posing greater challenges to inverter operation and maximum power point tracking techniques in photovoltaic arrays. It is of great significance for optimizing the configuration of photovoltaic arrays and designing high-precision maximum power point tracking strategies.

Under partial-shading conditions, landscape-oriented photovoltaic (PV) modules can exhibit dual- or multi-peak power–voltage (P–V) characteristics, which may trap conventional maximum power point tracking (MPPT) algorithms at local optima. A 60-cell full-cell PV module model incorporating bypass diodes was established, and global maximum power point tracking (GMPPT) simulations were conducted under partial-shading conditions. The model agreed well with previously obtained experimental data, with a mean absolute percentage error of 3.48% between the simulated and measured powers. An improved particle swarm optimization–incremental conductance strategy (PSO-INC) was developed by incorporating a transition stage, an irradiance-change-triggered global-search restart mechanism, and a search-direction-dependent adaptive step size. This strategy combines the global exploration capability of particle swarm optimization (PSO) with the local refinement capability of incremental conductance (INC). Thirty independent simulations with prescribed random seeds were performed for each scenario. Relative to the experimentally measured global maximum power point (GMPP), PSO-INC achieved a mean tracking efficiency of 99.20% and a mean relative error of 0.80% across the six static-shading configurations. Its mean settling time was 44.81% shorter than that of PSO. Under 25% shading, the mean tracked power was 256.23 W, exceeding the reported outputs of INC and jump-exploration incremental conductance (JEINC) by 41.95 W (19.58%) and 40.10 W (18.55%), respectively. Following irradiance transitions from 1000 to 500 W/m² and from 1000 to 0 W/m², the mean settling time was reduced by 53.03% and 53.05%, respectively, relative to PSO. These results demonstrate that PSO-INC improves GMPPT accuracy, settling performance, and steady-state behavior under partial-shading conditions and rapidly changing irradiance.

The acetic acid corrosion resistance of silver electrodes is critical for ensuring photovoltaic (PV) module reliability. Ethylene-vinyl acetate (EVA) is the most widely used encapsulant material in photovoltaic modules. Under exposure to light, heat, and moisture, EVA decomposes to generate acetic acid, which corrodes the silver electrodes, leading to energy conversion efficiency degradation of the module. To address this problem, the lead-free paste was formulated and evaluated in this paper to improve the anti-acetic acid performance. The contact resistivity of the front and the rear side of the solar cells have been measured before and after acetic acid exposure, and greater degradation is shown in the front electrode than in the rear side. Furthermore, the lead-free paste demonstrates lower efficiency degradation compared to the lead-containing paste after acetic acid exposure. In addition, top-view and cross-sectional scanning electron microscopy was performed to analyze the mechanism of the acetic acid corrosion resistance, in which the silver acetate particles were observed. Our experimental results demonstrate that the lead-free paste exhibits superior acetic acid corrosion resistance, which is due to its higher glass acidity and the absence of lead oxide that causes enhanced chemical reactivity with acetic acid. Based on these findings, the acetic acid corrosion model is proposed to attribute the conversion efficiency degradation of reactions between acetic acid and silver, as well as the glass of the silver electrodes.

Existing parameter extraction methods for photovoltaic modules are mostly developed for specific module types or structural configurations, making it difficult to achieve unified modeling across different materials, structures, and operating conditions. To address this issue, this study proposes a unified five-parameter identification method based on the single-diode model of photovoltaic cells and combines it with a genetic algorithm. The photocurrent, reverse saturation current, series resistance, shunt resistance, and diode ideality factor are selected as the identification parameters, and the parameter extraction problem is formulated as a global optimization problem. On this basis, a cell-unit-based parameter correction model considering the effects of irradiance and temperature is established, and unified modeling of photovoltaic modules with different architectures is achieved according to their internal electrical connections, enabling the prediction of their electrical characteristics. The proposed method is validated using experimental data from a half-cell mono-crystalline silicon module under different shading conditions, as well as mono-crystalline silicon, multi-crystalline silicon, and thin-film modules under varying irradiance and temperature conditions. In addition, the RTC France solar cell and Photowatt-PWP201 module benchmark datasets are employed to further assess the reliability of the parameter identification procedure. The results demonstrate that the proposed method can effectively reproduce the electrical characteristics of the investigated photovoltaic modules, with maximum relative errors of 2.48%, 2.17%, and 4.32% for open-circuit voltage, short-circuit current, and maximum power, respectively. The benchmark validation further demonstrates that the proposed method achieves fitting accuracy comparable to that of other representative optimization algorithms while exhibiting good repeatability and convergence performance. These results collectively demonstrate the feasibility of the proposed cell-unit-based five-parameter modeling framework for photovoltaic modules with different materials and structures under the investigated operating conditions, providing a simple and feasible approach for unified parameter identification, performance characterization, and engineering modeling.