Dual Axis Solar Tracking System Research Articles

Design and Implementation of a Dual-Axis Solar Tracking System with IoT-Enhanced Monitoring Using Arduino

The position of the sun varies over the day and with the seasons, making it difficult for conventional fixed solar panel systems to achieve optimum energy production. By reorienting the panels to face the sun, solar tracking systems solve this problem. This study suggests a dual-axis solar tracker system that continuously adjusts the panels to stay perpendicular to sunlight in order to maximize energy capture. The system uses sensors to monitor the sun's elevation and azimuth angles. Light sensors, motor controllers, microcontrollers, control algorithms, and an Internet of Things (IoT) monitoring system are some of the system's essential parts. The microprocessor determines the ideal angles for panel alignment based on the location of the sun as detected by the light sensors. The motor driver then adjusts the panels appropriately. The sun's position is accurately and smoothly tracked using dual-axis tracking systems, which employ sensors to detect solar position and actuators controlled by sophisticated algorithms to adjust the panels accordingly. Real-time parameter monitoring of the solar panel is done using an IoT-enabled webpage. The study's findings show that the dual-axis solar tracker system performs noticeably better in terms of energy capture efficiency than fixed installations, especially in areas with high solar incidence angles and fluctuating sunshine.

A Novel Tracking Strategy Based on Real-Time Monitoring to Increase the Lifetime of Dual-Axis Solar Tracking Systems

Solar tracking systems allow an increase in the use of solar energy for its conversion with photovoltaic technology due to the alignment with the sun. However, there is a compromise between tracking accuracy and the energy required to perform the movement action. Consequently, the wear of the tracker components increases, reducing its useful lifetime and affecting the profitability of these systems. The present research develops a novel tracking strategy based on real-time measurements to increase the lifetime without reducing the energy productivity of the tracking systems. The proposed approach is verified experimentally by implementing the real-time decision-making algorithm and a conventional tracking algorithm in identical tracking systems under the same weather conditions. The proposed strategy reduces energy consumption by 14.18% due to the tracking action, maintaining a practically identical energy generation between both systems. The findings highlight a 53.33% reduction in the movements required for tracking and a 60.77% reduction in operation time, which translates into a 6.8-fold increase in the lifetime of the solar tracking system under the experimental conditions applied. The results are promising, so this research initiates and motivates the development of more complex models to increase the useful life of the tracking systems and their profitability and environmental impact concurrently.

Dual-axis solar tracker system utilizing Fresnel lens for web-based monitoring

Dual-axis solar tracker system utilizing Fresnel lens for web-based monitoring

Dependability Assessment of a Dual-Axis Solar Tracking Prototype Using a Maintenance-Oriented Metric System

This study presents a numerical method for evaluating the maintainability of a dual-axis solar tracking system that can be deployed in residential areas for improved energy production. The purpose of this research manuscript is threefold. It targets the following objectives: (i) First, we present the construction of a self-sufficient dual-axis solar tracking system based on a low-power electronic schematic that requires only one motor driver to control the azimuth and elevation angles of the photovoltaic (PV) panel. The automated system’s main electronic equipment comprises 1 × Arduino Mega2560 microcontroller unit (MCU), 1 × TB6560 stepper driver module, 2 × stepper motors, 2 × relay modules, 1 × solar charge controller, 1 × accumulator, and 1 × voltage convertor. Additional hardware components such as photoresistors, mechanical limit switches, rotary encoders, voltage, and current sensors are also included to complete the automation cycle of the solar tracking system. (ii) Second, the Arduino Mega 2560 prototyping board is replaced by a custom-made and low-cost application-specific printed circuit board (ASPCB) based on the AVR controller. The MCU’s possible fault domain is then further defined by examining the risks of the poor manufacturing process, which can lead to stuck-at-0 (Sa0) and stuck-at-1 (Sa1) defects. Besides these issues, other challenges such as component modularity, installation accessibility, and hardware failures can affect the automated system’s serviceability. (iii) Third, we propose a novel set of maintenance-oriented metrics that combine the previously identified variables to provide a maintainability index (MI), which serves as a valuable tool for evaluating, optimizing, and maintaining complex systems such as solar tracking devices. The experimental data show that the computed MI improves the system’s maintainability and enhances repair operations, increasing uptime.

Comparative performance evaluation of dual-axis solar trackers: Enhancing solar harvesting efficiency

Nowadays, renewable energy is a much discussable topic because of its important specifications such as pollution and un end sources. This paper emphasizes the importance and capabilities of the dual axis solar tracking system (DASTS) of solar cell technologies. The study carried out a practical process of a dual-axis system design, which practically demonstrates the influence of dual-axis solar trackers, including their operational principles, advantages, and associated challenges. Furthermore, it has been shown that dual-axis solar trackers can significantly increase solar energy yield by capturing maximum sunlight, making them an important advancement in improving the efficiency and effectiveness of solar energy generation. The paper also presents a performance evaluation of a solar tracker system that improved energy output by 45 % compared to the fixed solar panel (FSP) while also reducing the numerical calculation (NC) efficiency of DASTS by 3.16 %. Based on these findings, solar tracker systems can provide sustainable and environmentally friendly energy solutions that are both feasible and substantial.

Advancing sustainable cooling: Performance analysis of a solar-driven thermoelectric refrigeration system for eco-friendly solutions

The solar-powered thermoelectric refrigerator (SPTR) is an innovative approach that uses solar energy to cool spaces. Its effectiveness relies on solar insolation rates and an intelligent dual-axis solar tracking system (STS) that maximizes solar energy capture. Performance analysis of SPTR with the fixed panel solar system (WST) and dual-axis STS by keeping the SPTR at a standard ambient temperature of 25 °C was carried out under local climate conditions. The experimental test setup includes a thermoelectric refrigerator (TER), thermoelectric module (TEM), solar panels, and STS. The experimental findings showed that the coefficient of performance (COP) of SPTR depends on the solar irradiance, the system's input power, the surface temperature of the solar panels, and the cooling rate. The maximum and minimum values of COPs were 1.19 and 0.27 for directly coupled SPTR with a WST and 2.07 and 0.39 for STS, respectively. Compared with the stand-still solar system, a COP enhancement of 44–75 % is achieved. The results also show that the cooling load is a function of the refrigerated space, and the products are to be cooled, which is affected by the thermoelectric properties of the TEM. The cooling rate is recorded at its maximum when the system is operated using an STS on a clear sunny day with a maximum solar insolation rate. The SPTR has proven to be environmentally friendly, the best alternative to conventional cooling systems, and sustainable due to the independence of traditional energy resources.

Design and Implementation of A Dual-Axis Solar Tracking System using Arduino Uno Microcontroller

This paper presents a dual-axis solar tracking system developed and evaluated using LDR sensors and stepper motors, controlled by an Arduino Uno microcontroller. The aim was to enhance photovoltaic energy efficiency by designing a system capable of automatically adjusting the position of solar panels to follow the sun's movement throughout the day. Comparative testing between static solar panels and those equipped with solar trackers demonstrated that the latter produced 35% more power on average. Additionally, the dual tracking system showed a 14% improvement in efficiency over previous averages noted in existing references. Analysis of azimuth and elevation angles confirmed that the solar tracker accurately adjusted the panels' position, significantly boosting solar energy capture. This finding is consistent with prior research, which also supports the efficacy of solar trackers in enhancing photovoltaic efficiency. Future research should expand testing to include various weather and environmental conditions and focus on developing more advanced control algorithms to enhance system responsiveness. Continuous advancements in solar tracking technology are vital for maximizing solar energy potential and facilitating a transition to a more sustainable society.

Design of Model Predictive Control and IoT for Experimental Dual Axis Solar Tracker System based on FPGA

Design of Model Predictive Control and IoT for Experimental Dual Axis Solar Tracker System based on FPGA

Comparative Study on Efficiency Analysis of Fixed and Dual-Axis Solar Tracking System

Solar energy is a crucial renewable energy source, offering sustainable solutions to address energy demands and combat climate change. Maximizing the efficiency of solar energy harvesting is essential for widespread adoption and integration into the energy landscape. Solar tracking systems play an important role in increasing the efficiency of solar panels by optimizing their orientation towards the sun throughout the day. This research presents a comparative analysis of the efficiency of dual-axis solar tracking systems using Light-Dependent Resistors (LDRs) as input devices. A closed-loop tracking technique is implemented to adjust the position of the solar panels based on real-time sensor feedback. A comparative study between LDRs demonstrates their effectiveness in detecting the sun's position, despite limitations such as susceptibility to ambient light conditions and saturation to light intensity. Through experimental evaluation and data analysis, this study provides valuable insights into the power output and assessment of efficiency variation of dual-axis solar tracking systems offering applications for optimizing solar energy harvesting in practical scenarios.

Suntrack Weather: Real Time Solar Power Weather Update

The need for efficient solar energy utilization has become increasingly evident in the face of climate change and growing energy demands. This led to the recognition of the problem of suboptimal energy capture in fixed solar panels. Through extensive research and observations, it was identified that conventional fixed solar panels do not fully harness the available solar energy due to the sun's changing position throughout the day. This realization prompted the exploration of advanced tracking systems to improve energy capture. How the Problem was identified: In addressing the challenge of maximizing solar energy capture, various solar tracking technologies have been developed. Single-axis trackers are among the initial solutions, adjusting panels on a horizontal axis to follow the sun's east-west movement. However, these systems fail to account for the sun's changing altitude throughout the day. Dual-axis solar tracking systems emerged as a more advanced solution, capable of continuously aligning solar panels in both the horizontal and vertical planes. These systems employ an array of sensors, microcontrollers, and actuators to precisely track the sun's position, thereby significantly enhancing energy output. KEYWORDS: Sun-track weather, Real-time, Solar power, Weather update, Sun tracking technology.

Solar PV tracking system using arithmetic optimization with dual axis and sensor

Presently, PV system is considered the best renewable energy source for electricity production. In order to maximize energy output in photovoltaic systems, a system for tracking the sun's position and adjusting panel positions was created. Despite the fact that several models for tracking solar radiation have been suggested to improve energy production, it faces challenges in continuous tracking and power consumption. This paper proposes a novel sensor-based solar tracking system with numerical optimization to increase photovoltaic systems' energy output. The initial model was for a two-axis tracking system based on sensors. Solar panel and sun positions are detected by this system using ultraviolet and microelectromechanical sun sensors. To improve tracking movements and photovoltaic energy production, we recommend using solar sensors to construct a novel two-axis solar tracking device. This technology benefits from increased solar radiation and solar energy harvesting capabilities. The main disadvantage of dual-axis active solar tracking systems is that the drive mechanism frequently uses up the output power of the solar panels. As a result, the net power gain of the solar panel is less than its maximum. Further, a control system was developed with proportional integral derivative (PID) controller and arithmetic optimization (AO) to adjust the panel position relative to suns movement. The AO technique tunes the PID controller gains until it reaches its desired level to enhance the production of power. With the use of sensors, the tracking system can use mathematical optimization algorithms and the sun's position to minimize power consumption while still maintaining optimal solar panel positioning. The developed model was designed in the MATLAB software and the outcomes are analyzed. The paper also presents an energy analysis of the system, which evaluates the energy input, output and overall system efficiency. We recommend using solar sensors to create a unique dual-axis solar tracking system. This technology benefits from increased solar radiation and solar energy harvesting capabilities.

Fabrication, Design, and Analysis of Dual Axis Solar Tracking System

Energy crisis is one of the prime issues in the third world developing country like Bangladesh. There is an enormous gap between generation and demand of electrical energy. Nearly 50% of the population of the country is extremely isolated from this blessing. Renewable energy is the only answer to solve this issue. Solar energy is one of the most effective resources of renewable energy which could play a significant role in solving this crisis. This research presents a performance analysis of the dual axis solar tracking system using Arduino. The main objective of this research is whether a static solar panel is better than a solar tracker or not. This work is divided into two parts, hardware, and software system. In the hardware part, four light dependent resistors (LDR) is used to detect the utmost light source from the sun. Two servo motors conjointly used to move the solar panel to maximum light source location perceived by the LDRs. In the software part, the code is written by using C programming language and has targeted to the Arduino UNO controller. The outcome of the solar tracker system has analyzed and compared with the fixed or static solar panel found better performance in terms of voltage, current and power. Therefore, the solar tracker has proved more practical for capturing the maximum sunlight supply for star harvesting applications. The result showed dual- axis solar tracking system produced extra 10.53-watt power compared with fixed and single axis solar tracking system. Key Words: Solar Pannel, Servo Motor, LDR

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

Dual axis solar tracking system for agriculture applications using machine learning

The three most basic amenities required for human survival are food, shelter and clothing. In today's tech-savvy generation, these have experienced a great deal of scientific advancement. Unfortunately, agriculture is still more man power-oriented. So they have to rely on the hit and trial method to learn from experience which leads to waste of time. In proposed work includes an automated system using dual axis solar tracking system and gives crop recommendation for different types of soil to yield maximum. The suggested system is a dual-axis solar tracker based on machine learning that is intended to considerably increase the effectiveness of energy harvesting. The approach makes use of the logistic regression algorithm (LR) to do this. This novel strategy tries to maximize the solar panel's ability to produce energy, leading to increased energy yields. The quality of soil is predicted by using suitable sensors for crop recommendation. The data’s are temperature, humidity, pH of soil, nitrogen, phosphorous & potassium in soil and rainfall in soil are considered. For crop recommendation six algorithms- SVM, KNN, Native Bays, Logistic Regression, Decision Tree classifier, Random Forest Classifier are applied and tested. It is found that random forest classifier gave us excellent results.

Machine learning assisted prediction of solar to liquid fuel production: a case study

In this era of heightened environmental awareness, the global community faces the critical challenge of climate change. Renewable energy (RE) emerges as a vital contender to mitigate global warming and meet increasing energy needs. Nonetheless, the fluctuating nature of renewable energy sources underscores the necessity for efficient conversion and storage strategies. This pioneering research focuses on the transformation of solar energy (SE) into liquid fuels, with a specific emphasis on formic acid (FA) as a case study, done in Binh Thuan, Vietnam. The paper unveils a technology designed to convert solar energy into formic acid, ensuring its stability and storage at ambient conditions. It involves detailed simulations to quantify the daily and monthly electricity output from photovoltaic (PV) systems and the corresponding mass of formic acid producible through solar energy. The simulation of a dual-axis solar tracking system for the PV panels, intended to maximize solar energy capture, is one of the project's illustrations. The elevation and azimuth angles, which are two essential tracking system parameters, are extensively studied in the present research. The project makes use of machine learning algorithms in the field of predictive modeling, specifically Artificial Neural Networks (ANN) and Support Vector Machines (SVM). These tools play a crucial role in modeling PV power output and formic acid production while accounting for a variety of influencing factors. A comparative study shows that SVM outperforms ANN in accurately predicting the production of FA and PV power generation, both of which are the major goals. This model is a predictive tool that can be used to forecast these goals based on certain causal variables. Overall, it is observed that the maximum power produced with 2-axis solar tracker was achieved in February as 2355 kW resulting in the highest formic acid production of 2.25 ×106 grams. The study's broad ramifications demonstrate solar liquid fuel technology's potential as a long-term fix in the field of renewable energy. In addition to advancing the field of renewable energy storage, the study represents a major step toward tackling the global challenge of climate change.

Azimuth Angle and Magnetic Declination to Maximize Solar Panel Efficiency (Solar Tracking System)

This study presents the idea of power production through the solar which depends on the light intensity that falls on the solar panel. This project utilizes dual axis solar tracking system based on intensity of light using Arduino UNO. The hardware implementation includes an Arduino UNO and four LDR sensor for sensing the maximum intensity of light. Two DC motors are used, one motor is used for horizontal rotation and the second motor is used for the vertical rotation. This system includes the implementation of MPPT. It controls the charge and stores it in a battery. Battery provides 12V to inverter where DC voltages convert into AC voltages. SPWM inverter is designed over push pull topology. In conclusion, the proposed system operates on low input power and delivers high efficiency in output.

Design of a dual axis solar tracking system with strong wind protection system

The article discusses a model of a two-axis solar tracker with a control algorithm that provides a system of protection from strong winds, increasing the performance and reliability of a two-axis solar tracker, paying special attention to optimizing the controller board and software. The article also discusses formulas for determining the location of the sun, which can be used in the control algorithm of a solar two-axis tracker, which takes into account both daily and seasonal movements. As well as auxiliary trigonometric functions in the standard library of the programming language. Experimental studies have been conducted to confirm the need to equip a photovoltaic module with a solar tracker to obtain maximum energy efficiency.

Dual Axis Solar Tracking System with Weather Monitoring System

This paper presents the design and implementation of a solar tracking system integrated with weather monitoring capabilities. The system is designed to maximize the efficiency of solar panels by continuously adjusting their orientation to track the sun's position throughout the day. In addition to solar tracking, the system incorporates weather monitoring sensors to collect real-time data on environmental conditions such as cloud cover, wind speed, temperature and light intensity. This data is utilized to dynamically adjust the solar panel's position to optimize energy production and system performance in varying weather conditions. The integration of dual-axis tracking with weather monitoring enhances the overall efficiency and reliability of solar energy systems, making them more adaptable to changing environmental factors and increasing their potential for renewable energy generation.

Fuzzy Logic Control System for Optimizing Dual-Axis Solar Panel Tracking

The utilization of solar energy through solar panels has gained considerable attention in renewable energy applications. However, the effectiveness of energy conversion is hindered by the misalignment of solar panels with the incident sunlight. To address this issue, a dual-axis solar tracker system is proposed to automatically adjust the orientation of solar panels, enhancing energy generation efficiency. This research introduces a novel approach using a fuzzy logic control system to regulate the movement of stepper motors responsible for adjusting the solar panel positions. The system relies on input data from Light-Dependent Resistor (LDR) sensors to detect the sunlight’s position. Additionally, voltage, current, and angle sensors are integrated to accurately determine the solar panels angular position. The fuzzy logic control system employs the Mamdani method with Mean of Maximum (MOM) defuzzification. A comprehensive analysis of the systems performance was conducted, demonstrating that the manual calculations yielded 0.87 and 0.59 micro steps, while the Fuzzy Inference System (FIS) produced 0.35 and 0.26 micro steps. These results were verified through the serial monitor in the Arduino Integrated Development Environment (IDE). This research focuses on the development of a microcontroller-based two-axis solar panel control system using fuzzy logic. The system’s primary objective is to maximize solar energy utilization by ensuring that solar panels consistently align with the direction of sunlight, both vertically and horizontally. The proposed system offers an effective means of enhancing the efficiency of solar panel energy generation by continuously optimizing their alignment with the incident sunlight.

Model Prototype of a Solar Tracking System Supplying Electrical Power for Sensors Used in a Natural Disaster Monitoring System

Sun is the universe main source of energy. This energy can be converted to useful electrical energy by the utilization of solar panels or photovoltaic (PV) during the daytime with the presence of suitable sun irradiation level. It is important that during the energy conversion process, suitable methods are employed to extract as much energy as possible from the PV panels. Some issues affecting PV performance are the accuracy of the panel’s orientation and tilt angle with respect to the sun position. This causes PV to operate with lower efficiency, thus generating low output power compared to its rated capacity. One of the approaches to this issue is to constantly maintain a perpendicular profile of PV panels towards the sun direction as to capture the sun energy as much as possible, thus increases the PV efficiency. To do so, the conversion system needs a tracking mechanism to help the solar panel to constantly follow the sun’s direction, enhancing the achievement of higher PV efficiency. For this reason, a model prototype has been designed and developed which consists of a dual-axis solar tracking system, with two axis movement direction from east to west and north to south by utilizing the Light Dependent Resistors (LDRs) sensors. This tracking system is developed using Arduino UNO as the microcontroller that allows the PV panel to move optimally towards the high intensity of sunlight via four LDRs and two servo motors. To analyze the PV tracker’s performance, a monitoring system is implemented using ThingSpeak platform as the Internet of Things (IoT) platform interfacing with the controller Node MCU ESP8266. This monitoring system records the data of the PV energy parameters from the sensors’ output employed in this prototype. To assess the system efficacy, the dual-axis tracking system is compared with the single-axis tracking system. The result showed that the dual-axis tracker has efficiencies of 68.46% which is higher compared to that’s of the single-axis tracker. Implementation of the real-time monitoring system has shown a practical and handy way to analyze and monitor the solar tracking system’s performance.