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The purpose of this paper is to establish the dynamics model of spacecraft during deployment of oblique solar panel using Auto Dynamic Analysis of Mechanical System (ADAMS) and to study the attitude motion of the spacecraft system during the oblique solar panel deployment.

For the case of an oblique solar panel on spacecraft, the dynamics virtual prototype model of deployment of oblique solar panels on spacecraft is established and the dynamics simulation is carried out using ADAMS. The effects of solar panel deployment on the attitude motion of spacecraft with different oblique angles are studied and the attitude motion regularities of spacecraft system are discussed. First, the effects on attitude motion of spacecraft are compared between the normal solar panel deployment and oblique solar panel deployment on a spacecraft. Then the attitude motion of spacecraft during the deployment of solar panel with different oblique angles on spacecraft is studied.

The effects of oblique angle of solar panel deployment on the attitude motion of spacecraft are significant in yaw axis. The bigger the oblique angle, the bigger the changes of yaw angle of spacecraft. However, the bigger the oblique angle, the smaller the changes of roll angle of spacecraft. The effects of oblique angle on pitch angle of spacecraft are slight.

Providing a practical method to study the attitude motion of spacecraft system during deployment of solar panel and improving the engineering application of spacecraft system, which put forward up spacecraft system to the practical engineering.

The paper is a useful reference for engineering design of a spacecraft attitude control system and ground text.

The use of renewable energy has become necessary because of the harmful effects of current energy sources on the environment, limited availability and financial crisis. Transparent solar panels have emerged as a promising technology for integrating renewable energy generation into building structures. Therefore, this paper aims to explore the feasibility of transparent solar panels for high-rise building façades in Sri Lanka.

The research apprehended a qualitative approach, including two expert interview rounds adhering to the Delphi technique with 17 and 15 experts each per round. Manual content analysis was incorporated to analyse the collected data.

Regarding operation and maintenance, the study emphasizes the importance of regular inspection, cleaning and repair of transparent solar panels to ensure optimal performance and longevity. These activities contribute to maximizing energy generation and maintaining the aesthetic appeal of the building. The benefits of implementing transparent solar panels on building façades are manifold. They include renewable energy generation, reduced greenhouse gas emissions, improved energy efficiency and enhanced architectural aesthetics. Furthermore, the research findings underscore the potential of transparent solar panels to contribute to Sri Lanka’s sustainable development goals and address the country’s increasing energy demand. However, the study also identifies challenges that need to be addressed for successful implementation.

This study contributes to understanding the feasibility of transparent solar panels for high-rise building façades in Sri Lanka. The research findings offer valuable insights into the operation and maintenance aspects, benefits, challenges and strategies for implementing transparent solar panels effectively. This knowledge can guide policymakers, architects and developers in making informed decisions regarding the integration of transparent solar panels, thereby promoting sustainable and energy-efficient building practices in Sri Lanka.

This paper aims to design an AI-based drone that can facilitate the complicated and time-intensive control process for detecting healthy and defective solar panels. Today, the use of solar panels is becoming widespread, and control problems are increasing. Physical control of the solar panels is critical in obtaining electrical power. Controlling solar panel power plants and rooftop panel applications installed in large areas can be difficult and time-consuming. Therefore, this paper designs a system that aims to panel detection.

This paper designed a low-cost AI-based unmanned aerial vehicle to reduce the difficulty of the control process. Convolutional neural network based AI models were developed to classify solar panels as damaged, dusty and normal. Two approaches to the solar panel detection model were adopted: Approach 1 and Approach 2.

The training was conducted with YOLOv5, YOLOv6 and YOLOv8 models in Approach 1. The best F1 score was 81% at 150 epochs with YOLOv5m. In total, 87% and 89% of the best F1 score and mAP values were obtained with the YOLOv5s model at 100 epochs in Approach 2 as a proposed method. The best models at Approaches 1 and 2 were used with a developed AI-based drone in the real-time test application.

The AI-based low-cost solar panel detection drone was developed with an original data set of 1,100 images. A detailed comparative analysis of YOLOv5, YOLOv6 and YOLOv8 models regarding performance metrics was realized. Gaussian, salt-pepper noise addition and wavelet transform noise removal preprocessing techniques were applied to the created data set under the proposed method. The proposed method demonstrated expressive and remarkable performance in panel detection applications.

The purpose of this paper is to propose a conceptual framework for handling end of life (henceforth EoL) scenarios of solar photovoltaic (solar PV) panels, which includes different options available to businesses and end-users, as well as promoting the collaboration between government and all relevant stakeholders.

This paper adopts purposeful sampling, secondary data and content analysis to develop an appropriate conceptual framework that helps to create awareness of the appropriate options for dealing with the EoL cases of solar PV panels.

From the data analysis, it is revealed that reuse, repair and recycling of solar PV panels can ensure value creation, public-private partnership and a solution for education in sustainability, and thus, prolonging the useful life cycle of the products.

This paper limits the analysis on developing economies and the use of selected literature based on the recycling of solar PV panels.

This paper is an initial attempt to create an awareness by identifying, analyzing and educating the stakeholders to handle appropriately any EoL scenario of solar PV panels.

To analyze the operating performance of a fuzzy logic control (FLC) based solar energy conversion modular system controlled by a digital signal processor (DSP) microcontroller.

A range of published works relevant to the solar energy conversion modular systems are evaluated and their limitations are indicated in the first section of the paper. The circuit diagram of the panel‐boost converter system is described in the second section. In the third section, a neural network model is suggested for the photovoltaic panel and the model is created in the MATLAB/SIMULINK and then combined with other blocks existing in the system. The design of the FLC method is described in section 4. The simulation and experimental results corresponding to the control of the duty‐cycle of the converter to set the operating point of the solar panel at the maximum power point (MPP) are given in sections 5 and 6, respectively. Section 7, summarizes the results and conclusions of the study.

The paper suggests a simple dc‐dc boost converter controlled by FLC method. The proposed converter model can be used to obtain maximum power from a photovoltaic panel.

In preparing this paper, the resources books existing in the library of our university and the resources relative to the solar energy conversion and FLC published in English language and reachable through the internet were researched.

The paper suggests a neural network model for a solar panel, which can be used in the simulation of the solar energy panel‐boost converter system. The solar energy panel‐boost converter system proposed in this study can be used by the researchers who are working in the solar energy conversion area.

The suggestion of a neural network model for a solar panel and creation of this model in the MATLAB/SIMULINK environment provides researchers to simulate and to analyze the performance of the solar energy panel‐boost converter system using the MATLAB/SIMULINK simulation program. In addition, since the control approach proposed in this paper does not require the information on temperature and solar irradiance that affect the maximum output power, can effectively find the MPP of the solar panel.

Autonomous mobile cleaning robots are widely used to clean solar panels because of their flexibility and high efficiency. However, gravity is a challenge for cleaning robots on inclined solar panels, and robots have problems such as high working power and short battery life. This paper aims to develop a following robot to improve the working time and efficiency of the cleaning robot.

The mechanical structure of the robot is designed so that it can carry a large-capacity battery and continuously power the cleaning robot. The robot determines its position and orientation relative to the edge of solar panel by using optoelectronic sensors. Based on the following distance, the robot changes its state between moving and waiting to ensure that supply cable will not drag.

Prototype following robot test results show that the following robot can stably follow the cleaning robot and supply continuous power to cleaning robot. The linear error of the following robot moving along the solar panel is less than 0.3 m, and the following distance between the robot and the cleaning robot is in 0.5–1.5 m.

The working time of cleaning robots and working efficiency is improved by using following robot, thereby reducing the labor intensity of workers and saving the labor costs of cleaning.

The design of the following robot is innovative. Following robot works with the existing cleaning robots to make up for shortcomings of the existing cleaning system. It provides a more feasible and practical solution for using robots to clean solar panels.

This study aims to predict the types of thermally induced dynamics (TID) that can occur on deployable solar panels of a small form factor satellite, CubeSat which flies in low Earth orbit (LEO). The TID effect on the CubeSat body is examined.

A 3U CubeSat with four short-edge deployable solar panels is considered. Time historic temperature of the solar panels throughout the orbit is obtained using a thermal analysis software. The results are used in numerical simulation to find the structural response of the solar panel. Subsequently, the effect of solar panel motion on pointing the direction of the satellite is examined using inertia relief method.

The thermal snap motion could occur during eclipse transitions due to rapid temperature changes in solar panels’ cross-sections. In the case of asymmetric solar panel configuration, noticeable displacement in the pointing direction can be observed during the eclipse transitions.

This work only examines an LEO mission where the solar cells of the solar panels point to the Sun throughout the daylight period and point to the Earth while in shadow. Simplification is made to the CubeSat structure and some parameters in the space environment.

The results from this work reveal several practical applications worthy of simplifying the study of TID on satellite appendages.

This work presents a computational method that fully uses finite element software to analyze TID phenomenon that can occur in LEO on a CubeSat which has commonly used deployable solar panels structure.

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

The purpose of this paper is to design and develop an IR and sprinkler based embedded controller operated robotic arm for automatic dust removal system to mitigate the dust effect on the solar panel surface, since dust accumulation normally affected by real weather conditions is one of the serious concern for the deterioration of photovoltaic (PV) system output.

The system is a wet cleaning device which provides a cheap silicon rubber-based wiping operation controlled by the pulse width modulation-operated motors of robotic arm. The IEEE 1149.1-compliant mixed signal-embedded platform of C8051F226DK is involved to command the complete system.

A prototype of 30 W_P system is capable of producing an inspiring average value of 11.26 per cent in energy increase, 13.63 per cent in PV module efficiency and 85.20 per cent in performance ratio of the system after 73 days of cleaning in summer season. In addition, a total of 1,617.93 W power; 1,0516.55 Wh energy; and 350.55 KWh/KW_P final yield was found during the entire cleaning period.

A novel technique of the implementation of IR sensor and sprinkler in dust mitigation is proposed in this paper. The IR sensor is used as a versatile object which can manage the robotic arm setting and control the automatic switching between cleaning and charging, as well as identify the thermal condition of solar panel for overheating.

The roofs of houses located at middle latitudes receive significant solar radiation useful to supply their own energy demands and to feed back into the urban electricity network. However, solar panels should be properly integrated into roofs. This study analyzed roof geometry and integrated solar performance of Photovoltaic, thermal-photovoltaic, and hybrid solar collection technologies on dwelling cases selected from a sample of recent housing developments in Concepción, Chile. Hour-by-hour energy generation estimates and comparisons with demand levels were calculated for representative days during seasons of maximum, minimum as well as mid-season. These estimates took into account the roof tilt and orientation effects also. Trnsys@ software was used to determine electricity supply and F-Chart tool for thermal energy supply. The results show five times more panels can be placed on the largest and most regular shaped roof sections than on those with the smallest and most irregular shapes. The house model with the largest roof section can provide up to six times more energy than the model with the smallest second roof section in different seasons and systems. This paper thus provides new findings on the performance of solar technologies when related to home energy demands and roof geometry.