Progress and prospects on performance analysis of solar cleaning system – A comprehensive review

Md. Mashuk , Abu Yousouf Siddiky , Md. Thohid Rayhan , Md. Jahid Hasan , Moyeen Khan , Md Hosne Mobarak , Md Israfil Hossain Rimon
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Abstract

Solar energy is growing quickly around the world. By the end of 2023, the world's installed solar photovoltaic (PV) capacity will have grown from 1.2 TW in 2022 to 1.6 TW. In the same year, new installations will have grown by 87% to 447 GW. This growth has made it even more important to have good cleaning methods, since dust and other particles can cut PV performance by 20–50%, and even 80% in dry conditions. This evaluation looks at many ways to clean, including as robotic systems, electrostatic methods, ultrasonic techniques, and self-cleaning coatings. It looks at how well they clean, how much water and energy usage, how they affect panels over time, and how much they cost to run. The results show that robotic and electrostatic cleaning can bring back 95–98% of panel efficiency, although they use more energy (0.5–2% of PV output) and cost more money. Passive nanostructured coatings cut soiling losses by 50–70% and preserve water, but they break down when exposed to UV light for a long time. Combining robotics with coatings in hybrid approaches makes cleaning less frequent while keeping high efficiency. Case studies from different regions and sizes demonstrate that waterless robotic and electrostatic cleaning are most effective in dry areas, while rain-assisted coatings are best suited for humid areas. In contrast, manual or passive approaches remain the most cost-effective for small rooftop systems. For sustainable and scalable PV maintenance, AI-driven predictive cleaning and durable nanocoating, supported by targeted policies and incentives, are needed.
太阳能清洁系统性能分析的研究进展与展望
太阳能在世界范围内发展迅速。到2023年底,全球太阳能光伏(PV)装机容量将从2022年的1.2太瓦增长到1.6太瓦。同年,新增装机容量将增长87%,达到447吉瓦。这种增长使得良好的清洁方法变得更加重要,因为灰尘和其他颗粒会使PV性能降低20-50%,在干燥条件下甚至降低80%。该评估着眼于许多清洁方法,包括机器人系统、静电方法、超声波技术和自清洁涂层。它考察了它们的清洁效果,水和能源的使用量,它们随着时间的推移如何影响面板,以及它们的运行成本。结果表明,机器人和静电清洁可以恢复95-98%的面板效率,尽管它们使用更多的能源(光伏输出的0.5-2%)和成本更高。被动式纳米结构涂层可以减少50-70%的污染损失并保持水分,但当长时间暴露在紫外线下时,它们会分解。将机器人技术与涂料相结合,可以在保持高效率的同时减少清洁频率。来自不同地区和规模的案例研究表明,无水机器人和静电清洁在干燥地区最有效,而雨水辅助涂层最适合潮湿地区。相比之下,手动或被动方法仍然是小型屋顶系统最具成本效益的方法。为了实现可持续和可扩展的光伏维护,需要人工智能驱动的预测性清洁和耐用的纳米涂层,并得到有针对性的政策和激励措施的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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