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• Improving PV-TEG efficiency by tackling metal surface and air gap thermal challenges. • Proposing mathematical modeling for predictive performance evaluation of PV-TEG systems. • Investigating the effectiveness of PGS as a TIM in PV-TEG systems. • Assessment of three cooling approaches: natural air, forced air, and forced water. • Bent PGS configuration proves most effective in reducing PV panel temperature to enhance power generation. PV-TEG systems utilize waste heat by using TEGs under PV panels. TEGs improve the efficiency of PV and generates more energy. However, rough metal surfaces at contact points reduce the system's thermal efficiency and create air gaps. This paper employs a mathematical model based on principles of thermal resistances and energy conservation. The proposed model is built using MATLAB R2020a. The paper assessed the effectiveness of a Pyrolytic Graphite Sheet (PGS) as a Thermal Interface Material (TIM) in PV-TEG systems and three cooling approaches. The investigation explores two configurations (parallel and bent) of PGS and five TIM materials. The results indicate that bent PGS is the most effective. It lowers the temperature of the PV panels to 18.99 ℃, 19.95 ℃, and 20.74 ℃. As a result, the power increased to 0.606 W, 0.639 W, and 0.667 W. Additionally, the efficiency improves to 1.66 %, 1.75 %, and 1.82 % with natural air, forced air, and forced water cooling, respectively. The results show that PGS can improve PV-TEG system performance and solve thermal issues with metal surfaces and air gaps. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) power generation has become one of the key technologies to reach energy-saving and carbon reduction targets. However, dust accumulation will significantly affect the electrical, optical, and thermal performance of PV panels and cause some energy loss. For this reason, appropriate cleaning measures are needed to restore their performance and power output. Many researchers have reviewed the effects of dust on the performance of PV panels and cleaning methods, but their coverage is narrow and lacks more in-depth summarization, comparison, and critique of key quantitative results. Using the Web of Science database as the main search source, this paper provides a comprehensive overview of research results on the mechanisms and influencing factors of dust deposition on photovoltaic panels, photovoltaic performance loss and prediction models, cleaning methods, and dirt monitoring systems. The results found that the module power output degradation due to dust deposition is more serious in different regions, ranging from 7% to 98.13%. The automatic cleaning robot, as an emerging intelligent technology, has a better cleaning effect and can increase PV efficiency by up to 49.53%. This paper also proposes a comprehensive strategy for dust prevention on PV panels that integrates "real-time monitoring of dust accumulation - model prediction of losses - and optimization of cleaning solutions", emphasises the development of new intelligent cleaning methods represented by robots and drone cleaning, and suggests promoting the application of AI in the monitoring and cleaning of PV modules to accelerate the process of achieving carbon neutrality. [ABSTRACT FROM AUTHOR]