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.

Half-cell photovoltaic modules have been widely applied in distributed photovoltaic systems and building-integrated photovoltaic systems. Linear edge shading caused by buildings, guardrails, and adjacent modules is a key factor affecting their power generation performance. To address this problem, this paper establishes an equivalent prediction model for edge-shading of half-cell modules by combining the series–parallel topology of the module and the conduction behavior of bypass diodes. The genetic algorithm is employed to extract the model parameters, and the bisection method is used to solve the output current and obtain the corresponding I–V and P–V characteristics of the module under shading conditions. Simulation analysis is conducted by considering the edge-shading ratio and module installation orientation as variables, and the output characteristics and variation trends of PV modules under two configurations, namely long-edge shading with horizontal installation and short-edge shading with vertical installation, are investigated and compared. The results show that long-edge shading can cause current mismatch in cell strings and conduction of bypass diodes, leading to step features in the I–V curve, a multi-peak structure in the P–V curve, and rapid power attenuation. Short-edge shading only results in a linear decrease in photogenerated current, with smooth output curves and an approximately linear reduction in power along with the shading ratio, resulting in relatively smooth output characteristics. This study reveals the coupled effects of edge-shading and module installation orientation and provides a reference for evaluating shading-induced performance degradation and selecting suitable installation orientations for half-cell PV modules under the investigated shading conditions.

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.

In order to improve the dexterity of robots in complex environments and meet the people's requirements for robot work efficiency, the harmony search algorithm has been improved and integrated into the initial population generation process of genetic algorithm to optimize the parameters of traditional PID controllers. The simulation results show that the optimized harmony search genetic algorithm has better ability to handle nonlinear problems, improves the steady-state accuracy, response speed, and robustness of the controller, and can better complete complex environmental tasks.

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.