Panel Cleaning Research Articles

Online application of the periodic linear regression method for daily monitoring of photovoltaic systems performance

This paper presents an analysis of the performance of photovoltaic (PV) systems using daily applications of the periodic linear regression method to the performance indicators Final Yield (YF) and Reference Yield (YR). The research was conducted on PV systems installed on rooftops and ground at the Federal Institute of Education, Science, and Technology of Goiás (IFG), Itumbiara Campus, from July 2022 to August 2023. The Energy Monitoring and Management Software (SMGE) was developed to calculate the performance indicators and perform linear regression to analyze the performance of the systems. The results demonstrate that the efficiency of the systems can be monitored by analyzing variations in the slopes of the linear regression lines. An increase in energy conversion efficiency was observed following the cleaning of the PV panels, as reflected in significant changes in the regression slopes. Additionally, natural events, such as rainfall, positively impacted system efficiency. These findings highlight the importance of proper maintenance of PV panels, whether through scheduled cleaning or natural events like rain.

Automated cleaning of solar panels using a three-rotor drone

Automated cleaning of solar panels using a three-rotor drone

Optimal Scheduling of PV Panel Cleaning and Policy Implications Considering Uncertain Dusty Weather Conditions in the Middle East

Airborne dust easily accumulates on the top of solar panel surfaces and reduces the output power in arid regions. A commonly used mitigation solution for dust deposition issues is cleaning PV panels periodically. However, cleaning frequency affects the economic viability of solar PV systems, resulting in a trade-off between cleaning costs and energy loss costs. To address this issue, this study relates several metrics and develops a generic framework based on simulation and optimization to determine the optimal cleaning interval. Based on the computational tests, the optimal cleaning interval in Abu Dhabi is determined to be 34 days, which is longer than the currently recommended cleaning interval of 28 days. This study also identifies that energy recovery is responsive to decreases in unit cleaning costs in the presence of high electricity tariffs, whereas total cost savings show sensitivity when electricity tariffs are low. Finally, this study discusses energy policy implications by presenting an innovative concept involving the introduction of a cleaning subsidy which could reshape energy system cost dynamics, making PV systems economically competitive beyond the conventional levelized cost of electricity.

Universal droplet propulsion by dynamic surface-charge wetting

Controllable droplet propulsion on solid surfaces plays a crucial role in various technologies. Many actuating methods have been developed; however, there are still some limitations in terms of the introduction of additives, the versatilities of solid surfaces, and the speed of transportation. Herein, we have demonstrated a universal droplet propulsion method based on dynamic surface-charge wetting by depositing oscillating and opposite surface charges on dielectric films with unmodified surfaces. Dynamic surface-charge wetting propels droplets by continuously inducing smaller front contact angles than rear contact angles. This innovative imbalance is built by alternately storing and spreading opposite charges on dielectric films, which results in remarkable electrostatic forces under large gradients and electric fields. The method exhibits excellent droplet manipulation performance characteristics, including high speed (~130 mm/s), high adaptability of droplet volume (1 μL–1 mL), strong handling ability on non-slippery surfaces with large contact angle hysteresis (CAH) (maximum angle of 35°), significant programmability and reconfigurability, and low mass loss. The great application potential of this method has been effectively demonstrated in programmable microreactions, defogging without gravity assistance, and surface cleaning of photovoltaic panels using condensed droplets.

Solar Panel Cleaning System

Solar Panel Cleaning System

IoT based Solar Panel Cleaning Rover

The primary objective of this proposed study is to design a system for effectively maintaining the cleanliness of solar panels, thereby enhancing their performance and longevity through an Internet of Things-based solar panel cleaning rover equipped with a sensors, and manual automation capabilities. A suite of sensors, including dust sensors, enables the rover to gather relevant data about the cleanliness status and ambient conditions surrounding the solar panels. Manual automation features empower users to intervene and control the rover's movements and cleaning actions as needed, providing flexibility and customization in operation. Furthermore, the rover is designed to connect directly with water tanks, facilitating an autonomous water supply for the cleaning process. A sponge brush mechanism is integrated into the rover's design to effectively remove dust from the solar panel surfaces. The proposed work has developed a prototype of the IoT-based solar panel cleaning rover, which has been tested to demonstrate its effectiveness in improving solar panel efficiency and reducing maintenance efforts.

Smart solar maintenance: IoT-enabled automated cleaning for enhanced photovoltaic efficiency

This innovative project aims to increase the effectiveness and user experience of solar panel systems by introducing a state-of-the-art dust and speck removal system. Leveraging cutting-edge technology, the system demonstrates a remarkable 32% increase in power output compared to dirty solar panels. The approach is characterized by its reliance on the universe as the system controller, reducing the need for manual intervention and minimizing the workforce required for panel cleaning. The proposed timed system utilizes water and wipers, facilitated by internet of things (IoT) technology, microcontrollers, and sensor modules for efficient and automated operation. An Android application provides user control and notifications about ongoing processes. The system’s adaptability for various settings is emphasized, offering a portable solution. The smart IoT based automatic solar panel cleaning ensures reliable performance, underscoring the project’s commitment to improve scalability, cost-efficiency, performance, integrity, and consistency.

Design & Fabrication of Water Optimized - Solar Panel Cleaning Robot

Abstract: Maintaining a power capacity of solar cell is the main thing for exercising solar power system. Most common problems in solar power system are dust, beach, creature’s pollen and crops burning. These challenges have a huge impact on the power generation capacity of solar panel. The thing of the robot's conception design is to make a machine that's easy to install, adaptable in terms of configuration, and requires lower labourers and functional charges. The robot is equipped with helical comber skirmishes which are driven by dc motor so that the robot is enforced with a water sprinkle in order to clean the panels far and wide it moves through. In this design, a system contains a length dimension unit and bedded control schemes in order to drive a movement directly and to localize the positions of the robot.

IoT Based Solar Panel Cleaning System

IoT Based Solar Panel Cleaning System

Digital twin technology for enhanced smart grid performance: integrating sustainability, security, and efficiency

This research paper presents the development and analysis of a multifaceted smart grid prototype. It combines various technologies for the smart grid operation. The first technology is environmental analysis of smart grid and solar panel cleaning. Secondly, radio-frequency identification (RFID)-based security and access control system has been integrated for smart grid. The third component is internet of things (IoT)-based energy monitoring and load management. For environmental analysis sensors such as temperature, humidity, light-dependent resistor, and flame sensors are connected to a NodeMCU controller for real time monitoring. Moreover, IoT based solar cleaning system is developed in the form of prototype with the help of Blynk and servo motor. The second component of prototype is smart security system which is developed with the help of Arduino and RFID module to facilitate secure access control. The third part of prototype employs voltage and current sensors with an ESP32 microcontroller and the Blynk application for real-time energy consumption analysis. This setup enables remote monitoring of voltage, power dynamics, and consumption patterns in a smart grid. It also offers an IoT based solution for load management and load shedding within the smart grid. The complete prototype overall demonstrates a comprehensive approach to 1) smart grid management, 2) environmental analysis, 3) security, and 4) energy monitoring.

ECONOMIC AND SOCIAL BENEFITS OF ROBOTICS IN SOLAR AND BIOMASS ENERGY: A REVIEW WITH IMPLICATIONS FOR BIHAR

Robotics integration in the renewable energy sectors of solar and biomass energy can change energy production, improve efficiency, and introduce sustainability practices. This review paper will address some of the economic and social benefits of robotics in such energy domains, specifically for the state of Bihar in India, where substantial challenges in the production of energy are present. To initiate, the paper will discuss the situation of solar and biomass energy in Bihar: where this state is still poor concerning the provision of electricity, which indicates the amount of dependency that the state has with the conventional energy, and thus how urgent the need is for alternative sustainable sources. We then analyze the appraisal of how robotics can maximize energy production through automation, precision agriculture, and predictive maintenance-cutting operational costs and therefore maximizing energy output. The paper discusses various robotic applications such as automated solar panel cleaning systems and biomass processing robots, about which emphasis was placed for improving productivity and operational efficiency. We also take into account the socio-economic impacts of introducing robotics into these energy sectors. Improved access to energy, through more efficient modes of production, holds the promise of lifting local economic performance and providing employment opportunities and reducing energy poverty. However, the paper also addresses some of the possible challenges, such as some displacement of jobs and hence the need for upgradation in skills in response to new technologies. To put this into perspective, the literature synthesis and case studies are reviewed below to give an overview of successful implementations of robotics in renewable energy globally. We further discuss policy recommendations and strategies that must be integrated into Bihar's energy framework to support sustainable development goals and address regional energy demands. Hence, in conclusion, the strategic deployment of robotics in solar and biomass energy does not merely serve to provide significant economic advantage but also contributes to social development of Bihar to ensure a viable and sustainable future of the energy world.

Solar Panel Cleaning Robot

In this project, various studies revolving around how dirt and dust affect the performance of solar panels depending upon different regions, as different areas have different soil compositions and how they are different from one another. A new way of approach to the domestic solar panel cleaning system, researchers have proposed many ways to improve and classify the object and present it in an image in the past. However, there have few projects related to domestic cleaning of solar panels. Due to the inconsistencies in cleaning especially in region where rain is not the most convenient option for cleaning. On continuous using of solar panels, a layer of accumulated dust particles is settled on the surface of solar panels or PV panels which affect the result of decreasing in efficiency by 50 %. By cleaning on regular intervals it decreases this soil loss. Various data have been collected which shows the importance of domestic solar panel cleaning for future generation.

Challenges in the Planning, Construction and Farming Practices in Agrivoltaic Systems With Vertically Mounted Panels

Several challenges in planning, construction, and farming practices hinder the optimization of agrivoltaic systems (AS) and the achievement of optimal crop production. This paper identifies and addresses these issues while presenting initial solutions. One specific type of AS involves vertically mounted panels on arable or grassland sites. The installation of panel rows divides large fields into narrow units, restricting the use of farming implements with different working widths. Implement widths must align with the spacing between panel rows, which often results in residual strips or overlapping issues when field operations are carried out. Furthermore, boundary effects in AS are more pronounced, impacting yield along field borders. The presence of panel rows also complicates driving operations, requiring reduced speeds and posing collision risks between implements and panels. Soil compaction during AS construction, microclimate variations, and panel contamination by dust, or spray drift deposits further affect plant growth and solar system performance. Initial solutions are proposed to address these challenges. These include careful planning of row spacing based on the working widths of critical implements such as combines, adoption of field sprayers with foldable booms, consideration of pneumatic fertilizer spreaders, and integration of precision farming techniques to manage variability within AS. Additionally, the use of construction machinery with low soil pressure, employment of steering technologies based on global navigation satellite systems, and research on panel cleaning devices are suggested. Overall, this paper highlights the need for further research and development to overcome farming challenges in agrivoltaic systems with vertically mounted panels.

Machine Learning-Based Control of Autonomous Vehicles for Solar Panel Cleaning Systems in Agricultural Solar Farms

This paper presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in dedicated lands for solar energy production (e.g., agricultural solar farms), are susceptible to dust and debris accumulation, leading to diminished energy absorption. Instead of labor-intensive manual cleaning, robotic cleaners offer a viable solution. AVs equipped to transport and precisely position these cleaning robots are indispensable for the efficient navigation among solar panel arrays. However, environmental obstacles (e.g., rough terrain), variations in solar panel installation (e.g., height disparities, different angles), and uncertainties (e.g., AV and environmental modeling) may degrade the performance of traditional controllers. In this study, a biologically inspired method based on Brain Emotional Learning (BEL) is developed to tackle the aforementioned challenges. The developed controller is implemented numerically using MATLAB-SIMULINK. The paper concludes with a comparative analysis of the AVs’ performance using both PID and developed controllers across various scenarios, highlighting the efficacy and advantages of the intelligent control approach for AVs deployed in solar panel cleaning systems within agricultural solar farms. Simulation results demonstrate the superior performance of the ML-based controller, showcasing significant improvements over the PID controller.

Review on Design and Fabrication of Solar Panel Cleaning Mechanism

Today energy demands are increasing sharply therefore as a Renewable source of power, solar energy has an important role in producing the electricity direct from sunlight. The surface of solar panel in solar power plants becomes dirty due to natural factors such as dust and bird droppings. This project aims at increasing the efficiency of solar power plants by solving the problem of accumulation of dust on the surface of solar panel which leads to reduction in plant output and overall plant efficiency. It proposes to develop a Solar Panel Cleaning System which could remove the accumulated dust on its surface on a regular basis and maintain the solar power plant output.[8]

Fabrication of Solar Panel Cleaning Machine

Fabrication of Solar Panel Cleaning Machine

Energy Production Optimization by Positioning of Solar Panels and Surveillance System with Cleaning of Panels

The pursuit of efficient and sustainable energy generation has led to the widespread adoption of solar panels. However, the optimal performance of these panels can be hindered by factors such as dirt accumulation, suboptimal orientation, and security concerns. To address these challenges, we propose an integrated Solar Panel Tracking, Cleaning, and Surveillance System (SPTCSS). Our system employs advanced tracking technology to optimize solar panel orientation, ensuring maximum exposure to sunlight throughout the day. Additionally, it incorporates automated cleaning mechanisms, utilizing water and brushes to remove dust, debris, and other contaminants, thereby maintaining peak efficiency. Furthermore, the surveillance aspect of the system provides real-time monitoring and security features, safeguarding against theft, vandalism, and unauthorized access. Through a network of sensors and cameras, any anomalies or suspicious activities can be promptly detected and addressed. By integrating tracking, cleaning, and surveillance functionalities into a single system, our solution offers a comprehensive approach to enhancing the performance, longevity, and security of solar panel installations. This not only maximizes energy generation but also minimizes maintenance requirements and mitigates risks, ultimately contributing to a more sustainable and reliable renewable energy infrastructure

Solar Panel Cleaning System with Voltage Drop Detection

bstract: This research suggests a unique voltage drop sensor and LDR (light-dependent resistor) based solar panel dust removal detecting system. Whereas the voltage drop sensor gauges the voltage differential between the solar panel's input and output, the LDR sensor counts the amount of light reflected from the panel's surface. The system is able to precisely identify the existence of dust and assess its level of intensity by evaluating the aggregated data from these sensors. Afterwards, an automatic dust removal device, like a water spray system or robotic brush, can be started using this information. The suggested method improves the overall performance and lifespan of solar photovoltaic systems by providing an automated, economical, and efficient alternative for the removal of dust from solar panel

Influence of a Dual Axis IoT- Based Off-Grid Solar Tracking System and Wheatstone Bridge on Efficient Energy Harvesting and Management

Influence of a Dual Axis IoT- Based Off-Grid Solar Tracking System and Wheatstone Bridge on Efficient Energy Harvesting and Management

Solar Panel Cleaning System

Abstract: The goal of Project SPACE is to create an automated solar panel cleaner that will address the adverse impact of soiling on commercial photovoltaic cells. Specifically, we hoped to create a device that increases the maximum power output of a soiled panel by 10% (recovering the amount of power lost) while still costing under $500 and operating for up to 7.0 years. A successful design should operate without the use of water.