Islam Syed Zahurul, Izzati Nur Syahirah, Abdullah Mohd Noor, Kamarudin Muhammad Saufi, Omar Rosli, Uddin Jasim
Faculty of Electrical & Electronic Engineering, Universiti Tun Hussein Onn Malaysia(UTHM), Parit Raja, 86400 Batu Pahat, Johor Malaysia.
Department of Applied Computing and Engineering, Cardiff School of Technologies, Cardiff Metropolitan University, Western Avenue, Cardiff, CF5 2YB UK.
SN Appl Sci. 2022;4(11):321. doi: 10.1007/s42452-022-05205-7. Epub 2022 Oct 31.
Wet dust on the Photovoltaic (PV) surface is a persistent problem that is merely considered for rooftop based PV cleaning under a high humid climate like Malaysia. This paper proposes an Automated Water Recycle (AWR) method encompassing a water recycling unit for rooftop PV cleaning with the aim to enhance the electrical performance. This study makes a major contribution by developing a new model to correlate output power ( ) and dust-fall factor. For model validation, we conducted an experiment of taking one set of Monocrystalline PV (mono) on a of medium luminance day. One mono module was cleaned by AWR - pressurized water sprayed through 11 small holes over its front surface, while the other module was left with no-cleaning. The dust-contaminated water was filtered and collected back to the tank for recycling process. The water loss per cleaning cycle was achieved 0.32%, which was normalized to net loss of 28.8% at a frequency of 1 cycle/day for 90 days of operation. We observed that of no-cleaning PV was decreased by 29.44% than that of AWR method. From this experimental data also, a unique and more accurate model is created for prediction, which is much simpler compared to multivariables equation. Our investigation offers important insights into the accuracy of this regression model demonstrated by or a strong negative quadratic relationship between and dust-fall. The cleaning of PV modules is expected to save significant energy to reduce the payback period.
An automated water recycle method for cleaning dust-fall in rooftop photovoltaic module is proposed.Both simulation and experimental models are developed to predict output power of the photovoltaic module.Proposed method can produce 24.40% more output power than a no-cleaning system with a mere water loss of 0.32%/cycle.
光伏（PV）表面的湿尘是一个长期存在的问题，在马来西亚等高湿度气候下，仅在基于屋顶的光伏清洁中才会考虑。本文提出了一种自动水循环（AWR）方法，该方法包括一个用于屋顶光伏清洁的水循环单元，旨在提高电气性能。本研究通过开发一个新模型来关联输出功率（ ）和降尘因子，做出了重大贡献。为了验证模型，我们在中等亮度的一天对一组单晶光伏（mono）进行了实验。一个单晶模块通过AWR进行清洁——通过11个小孔在其正面喷洒加压水，而另一个模块则不进行清洁。被灰尘污染的水经过过滤后收集回水箱进行循环利用。每个清洁周期的水损失率为0.32%，在90天的运行中，以每天1个周期的频率进行归一化处理后，净损失率为28.8%。我们观察到，未清洁的光伏的 比AWR方法降低了29.44%。从这些实验数据中，还创建了一个独特且更准确的模型用于 预测，该模型与多变量方程相比要简单得多。我们的研究为该回归模型的准确性提供了重要见解，该模型通过 或 与降尘之间的强负二次关系得到证明。光伏组件的清洁有望节省大量能源，以缩短投资回收期。
提出了一种用于清洁屋顶光伏组件降尘的自动水循环方法。开发了模拟和实验模型来预测光伏组件的输出功率。所提出的方法比不清洁系统可多产生24.40%的输出功率，每个周期的水损失仅为0.32%。
