Abstract

With the increasing demand for renewable energy, solar photovoltaic technology is being a topic of concern. However, due to the accumulation of dust and dirt over the panel surface, performance of photovoltaic system degrades to a noticeable amount. In order to address this issue: a fully automated, cost worthy and efficient system needs to be invented. This paper presents the design and fabrication process of a prototype along with its testing on a demonstration photovoltaic module; furthermore, depicting the implementation of the developed model on large-scale solar farms. The prototype of this system comprises of a cleaning robot and a cloud interface: the cleaning robot is mobile, and able to clean the entire solar array back and forth, with its separately driven cleaning rotatory brush; whereas, the cloud interface is a human-machine interface featuring the distant monitoring and control of the robot. Additionally, to notify the performance of distantly placed solar farm, a sensing unit consisting of sensors was added to this system, which updates the input and output parameters of the farm to the cloud interface. Furthermore, in this study, a month-long data of totally clean and dusty panel, were processed with regression analysis, and the regression model was developed to predict the suitable time for cleaning action. An Internet of Things based model is suggested for a large-scale solar farm having: a sensing unit, which senses the conditions of the farm; robotic unit: robots placed on each array of solar farm, which perform cleaning action if and only if, the command is sent from the operator or the sensing unit; and the cloud interface: interfacing each and every unit of the smart solar photovoltaic panel cleaning system.

Keywords: Renewable energy; Performance; Prototype; Solar farms; Robot; Cloud; Regression analysis; Internet of things