Modeling and design of low-cost automatic self cleaning mechanism for standalone micro PV systems

Khan, Muhammad Umar; Abbas, Majed; Kousar, Anila; Alam, Mehboob; Massoud, Yehia; Jafri, Syed Hassan Mujtaba

doi:10.1016/j.seta.2020.100922

Cited by 9 publications

(6 citation statements)

References 31 publications

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“…Dust particles are removed from the surface without using water; however, spraying water on the photovoltaic cells during cleaning increases their efficiency. The economic viability of automatic self-cleaning mechanisms of solar panels is evaluated in [59] to determine their contribution to the total system cost. When comparing the power generation of PV modules with and without automated selfcleaning mechanisms, the findings reveal a difference of 35%.…”

Section: Evaluation Of the Performance And Cost Of Solar Panel Cleani...mentioning

confidence: 99%

Solar Panels Dirt Monitoring and Cleaning for Performance Improvement: A Systematic Review on Smart Systems

2022

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The advancement in technology to manage energy generation using solar panels has proved vital for increased reliability and reduced cost. Solar panels emit no pollution while producing electricity as a renewable energy source. However, the solar panel is adversely affected by dirt, a major environmental factor affecting energy production. The intensity of light falling on the solar panel is reduced when dirt accumulates on the surface. This, in turn, lowers the output of electrical energy generated by the solar panel. Since cleansing the solar panel is essential, constant monitoring and evaluation of these processes are necessary to optimize them. This emphasizes the importance of using smart systems to monitor dirt and clean solar panels to improve their performance. The paper tries to verify the existence and the degree of research interest in this topic and seeks to evaluate the impact of smart systems to detect dirt conditions and clean solar panels compared to autonomous and manual technology. Research on smart systems for addressing dirt accumulation on solar panels was conducted taking into account efficiency, accuracy, complexity, and reliability, initial and running cost. Overall, real-time monitoring and cleaning of the solar panel improved its output power with integrated smart systems. It helps users get real-time updates of the solar panel’s condition and control actions from distant locations. A critical limitation of this research is the insufficient empirical analysis of existing smart systems, which should be thoroughly examined to allow further generalization of theoretical findings.

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Section: Evaluation Of the Performance And Cost Of Solar Panel Cleani...mentioning

confidence: 99%

Solar Panels Dirt Monitoring and Cleaning for Performance Improvement: A Systematic Review on Smart Systems

2022

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“…Cai et al [16] explored the structure of the dust removal port of the photovoltaic panel cleaning robot, theoretically analyzed the gas-solid two-phase flow equation, the correlation between the pressure distribution and the velocity of the dust particles during the dust removal, simulated and analyzed the flow field, and optimized the structural parameters of the dust removal port based on the orthogonal experimental method. Khan et al [17] proposed an automatic self-cleaning photovoltaic panel device comprising installation structure, cleaning wipes and relevant mechanical components. The pulley mechanism was developed to drive the cleaning wipes to dust the photovoltaic panel and improve the power generation efficiency of the photovoltaic panel.…”

Section: Structural Designmentioning

confidence: 99%

Research on Mechanism Design and Kinematic Characteristics of Self-Propelled Photovoltaic Cleaning Robot

et al. 2023

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A hydraulic drive-based self-propelled photovoltaic panel cleaning robot was developed to tackle the challenges of harsh environmental conditions, difficult roads, and incomplete cleaning of dust particles on the photovoltaic panel surface in photovoltaic power plants. The robot has the characteristics of the crawler wheel drive, rear-wheel-independent turning and three-point-independent suspension design, which makes it adhere to the walking requirements of complex environmental terrains, more flexible in turning and automatically levelling so that the stability of the boom mechanism during walking can be ensured. The kinematics model of the upper arm structure equipped with the end cleaning device was built, and the optimized Circle chaotic map and nonlinear weight factor were introduced to enhance the search ability and convergence speed of the sparrow algorithm. Furthermore, the boom running track was optimized in combination with the seven-order non-uniform B-spline curve. Through optimization, the running time of the boom was reduced by 18.7%, and the cleaning efficiency of photovoltaic panel surface was increased. The effectiveness of self-propelled photovoltaic panel cleaning robot cleaning and the reliability of time-optimal trajectory planning were confirmed through simulation and experiment.

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“…A PV cleaning system can clean dust, bird droppings, and other foreign particles from the PV surface automatically and is expected to boost energy production by 10%, on ❒ ISSN: 2302-9285 average [18]. Cleaning of the PV surface on rooftops or in large solar farms is a hard task (e.g., staff accidents, panel damage, movement difficulties, and poor maintenance) for human beings using a ladder and also proved to be pricey for large-scale PV generation [19], [20]. With evolving technology, many studies have been conducted by developing a mechanism using an automatic cleaning system [21].…”

Section: Introductionmentioning

confidence: 99%

Adaptive position control of DC motor for brush-based Adaptive position control of DC motor for brush-based

Sorfina¹,

Islam

Ching

et al. 2023

Bulletin EEI

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In this paper, we have developed an automatic brush-based PV cleaning system to control and synchronize the 3 motors together with a smooth periodic of cleaning while moving it horizontally over the PV surface. The mechanical design involved installing linear guides at the top and bottom of the rail to support the aluminium plate that holds the carrier motors and rotating brush. Two different movements of translational and rotational motion of the motors are managed by an algorithm programmed in Arduino Mega. In investigating the performance of motor parameters and dust removal rate, we conducted an experiment by spreading dry sand over the PV surface. Results showed that the torque of the cleaning brush motor increases with the increase in load. The obtained torque of the carrier motor was found to be 9.167 Nm ( stall torque, 9.8 Nm) with a full load of 18 brushes. The torque is inversely proportional to the speed but directly proportional to power. The required power to move the 2.93 kg of cleaning system was 19.20 W with 3.015 Nm of torque. The system achieved 86.8% of the dust removal rate from the four cycles of cleaning operations.

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Modeling and design of low-cost automatic self cleaning mechanism for standalone micro PV systems

Cited by 9 publications

References 31 publications

Solar Panels Dirt Monitoring and Cleaning for Performance Improvement: A Systematic Review on Smart Systems

Solar Panels Dirt Monitoring and Cleaning for Performance Improvement: A Systematic Review on Smart Systems

Research on Mechanism Design and Kinematic Characteristics of Self-Propelled Photovoltaic Cleaning Robot

Adaptive position control of DC motor for brush-based Adaptive position control of DC motor for brush-based

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