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.

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.