photovoltaic panels. This is consistent with the results of Lu et al. 's study on the effect of dust deposition on ground-mounted solar PV arrays [22]. The trajectory distribution of snow particles is shown in Figure 5. Snow particles mainly accumulate on the surface of photovoltaic panels and the ground at the junction, which is caused by snow falling and accumulating on the ground under the influence of gravity. At the same time, snow accumulates on the ground below the photovoltaic panels due to turbulence on the back of the photovoltaic panels. Therefore, in practical engineering, we can increase the height of the panel from the ground to increase the sliding of snow.

photovoltaic panels. This is consistent with the results of Lu et al. 's study on the effect of dust deposition on ground-mounted solar PV arrays [22]. The trajectory distribution of snow particles is shown in Figure 5. Snow particles mainly accumulate on the surface of photovoltaic panels and the ground at the junction, which is caused by snow falling and accumulating on the ground under the influence of gravity. At the same time, snow accumulates on the ground below the photovoltaic panels due to turbulence on the back of the photovoltaic panels. Therefore, in practical engineering, we can increase the height of the panel from the ground to increase the sliding of snow.

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The snow falling on the surface of photovoltaic modules tends to reduce the output power. In order to understand the process of snow accumulating on solar photovoltaic modules and reveal the impact of snow accumulation on photovoltaic conversion efficiency, the snow-cover process was simulated on the surface of photovoltaic modules with different t...

Citations

... In snowy regions, non-uniform snow coverage and buildup on the panels can cause a considerable drop in performance. For instance, in simulations and field experiments, it was found that when snow thickness reaches 1 cm, the power generation efficiency of the PV panel drops to approximately 7.1% of its normal output [197]. A study analyzing snow-related energy losses in PV systems found that modules placed at elevated positions experience annual losses of 1% to 9%, while those closer to the ground suffer losses of up to 29% due to snow accumulation and ground interference. ...
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The rapid expansion of photovoltaic (PV) systems underscores the need to understand environmental factors affecting their performance, degradation, and economic viability. This study comprehensively reviews 175 articles, classifying environmental factors such as atmospheric deposits (dust, sea salt, pollen), meteorological conditions (wind, temperature, humidity, rainfall, snowfall, hailstorms), shading, and solar irradiation variability. A novel multilevel classification of degradation modes is introduced, identifying failure mechanisms and their impacts. Key findings reveal performance losses of up to 60%–70% due to combined factors, while mitigation strategies, such as wind-induced cooling, can improve power output by 14.25%, and snow accumulation results in up to 12% annual energy losses. Performance metrics like Performance Loss Rate (PLR) and Degradation Rate (DR) are evaluated to quantify long-term impacts, with economic implications including potential revenue losses and maintenance costs. For instance, addressing dust accumulation in arid regions could save 20%–30% in annual cleaning costs while reducing energy inefficiencies. Recent advancements in AI-driven predictive maintenance are highlighted as pivotal for optimizing system performance and minimizing costs. This integrated analysis provides actionable insights for researchers, engineers, and policymakers, emphasizing the need for tailored strategies to enhance PV resilience and economic sustainability. By addressing the interaction of environmental factors and introducing standardized metrics, this study fills critical research gaps, offering a roadmap for improving PV system reliability, reducing operational costs, and supporting the transition to sustainable energy under diverse environmental conditions.
... On the one hand, ice and snow covering power lines may lead to line icing [6,7], which can cause serious accidents, such as line breaks and tower collapses, affecting the power supply and resulting in economic losses; on the other hand, ice and snow disasters may also affect the normal operation of new energy equipment. For example, wind turbines in the power distribution network may experience ice accretion on blades and transmission system jamming under ice and snow coverage, leading to reduced power generation efficiency or even shutdown [8,9]; distributed photovoltaic panels in the power distribution network may also reduce the power generation capacity under snow cover conditions [10,11]. Therefore, under the conditions of extremely low temperatures and ice and snow coverage, the normal operation of power equipment is affected, and the power supply reliability of the power distribution system is reduced. ...
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As global climate change intensifies, extreme weather events are becoming more frequent, with ice disasters posing an increasingly significant threat to the stable operation of power distribution networks. Particularly during power outages for de-icing, multiple power islands may form within a distribution area, increasing the complexity of grid operations. Existing research has not fully considered the comprehensive coordination of stable operation of these power islands and de-icing maintenance schedules. Therefore, for the potential multi-island operation of distribution networks caused by freezing disasters, this paper first establishes a dynamic island partitioning model based on distribution network reconfiguration technology. Secondly, based on the characteristics of the de-icing phase, a de-icing maintenance schedule model is established. Finally, dispatch optimization of the distribution network is coordinated with the line de-icing maintenance schedule. By adjusting the de-icing strategies and network structure, the aim is to minimize the risk of load loss. The relevant case analysis indicates that the collaborative optimization model established in this paper helps power distribution networks to reduce their economic losses when facing adverse weather conditions.
... On the other hand, there are also many studies specializing on the snow covering and melting process on PV panels. Perovich [ [36] studied on the relationship between snow cover depth, PV tilt angle and PV system efficiency. Hosseini et al. [37] modelled variation of power and current with snow cover. ...
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PV technologies are regarded as one of the most promising renewable options for the transition towards Net Zero. Despite the rapid development of PV systems in recent years, achieving the necessary goals requires more than a threefold increase in annual capacity deployment by 2030. However, current PV systems often fall short of optimal performance due to improper installation angles. In high-latitude cold regions, the actual PV generation capacity is frequently overestimated due to the omission of snow conditions. This study introduces a novel model designed for high-latitude regions to predict local optimal PV installation angle that maximizes PV power generation, utilizing historical weather big data, including snowfall and melting effects. A case study is presented within a Swedish context to demonstrate the implementation of these methods. The results highlight the crucial role snow conditions play in determining PV performance, resulting in an average reduction of 14.7% in annual PV power generation. Optimal installation angle could yield approximately a 4.8% improvement compared to common installation angles. The study also explores the application of snow removal agents, which could potentially increase PV generation by 0.1–2.3%. Additionally, the new PV installation angle successfully captures the impact of the local weather changes on PV power generation, potentially serving as a bridge between climate change adaptation and future PV power generation endeavors.
... The literature [21] investigated the optimal scheduling of systems for the combined operation of combined heat and power (CHP), carbon capture systems and P2G. Among the studies on the clean energy body of IESs, the literature [22][23][24][25][26][27] investigated the performance of photovoltaic power generation and [28][29][30][31][32][33] investigated the efficiency of electrical equipment. However, the following three aspects of the above studies can be further explored: most of the above studies were based on a non-cooperative game model, which focused only on the independence of each energy subject and ignored the potential cooperative relationship between the subjects of the IES; most of the studies took system operation cost minimization and carbon emission requirements as the objective function, but relied only on cost compression, which leads to limited profit growth; few studies took hydrogen-energy-to-gas conversion subjects into the study of benefit distribution of IESs and there was a lack of comprehensive research on the behaviour of multiple subjects under cooperative mode. ...
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The integrated energy system is an important development direction for achieving energy transformation in the context of the low-carbon development era, and an integrated energy system that uses renewable energy can reduce carbon emissions and improve energy utilization efficiency. The electric power network and the natural gas network are important transmission carriers in the energy field, so the coupling relationship between them has been of wide concern. This paper establishes an integrated energy system considering electricity, gas, heat and hydrogen loads; takes each subject in the integrated energy system as the research object; analyses the economic returns of each subject under different operation modes; applies the Shapley value method for benefit allocation; and quantifies the contribution value of the subject to the alliance through different influencing factors to revise the benefit allocation value. Compared with the independent mode, the overall benefits of the integrated energy system increase in the cooperative mode and the benefits of all subjects increase. Due to the different characteristics of different subjects in terms of environmental benefits, collaborative innovation and risk sharing, the benefit allocation is reduced for new-energy subjects and increased for power-to-gas subjects and combined heat and power generation units after revising the benefit allocation, to improve the matching degree between the contribution level and the benefit allocation under the premise of increased profit for each subject. The cooperative mode effectively enhances the economic benefits of the system as a whole and individually, and provides a useful reference for the allocation of benefits of integrated energy systems. The analysis shows that the revised benefit distribution under the cooperative model increases by 3.86%, 4.08% and 3.13% for power-to-gas subjects, combined heat and power generation units, and new-energy units, respectively, compared with the independent function model.