In this research, a new deep learning method called Dual-Axis Solar Tracking System (DA-STS) is presented to increase the hourly energy provided by four dual-axis solar trackers'' real-time forecast accuracy. A novel Artificial Neural Network (ANN) model and a recently developed Particle Swarm Optimisation (PSO) technique known as the
The work deals with the simulation and optimization of a tracking mechanism used to increase the efficiency of photovoltaic (PV) systems. The proposed solar tracker is one with two degrees of freedom (so called dual-axis, or bi-axial), of the equatorial/polar type. The actuation of the tracking system is carried out with two linear actuators, one for each of the two
This paper presents the design, construction and evaluation of a high-precision dual-axis solar tracking system with a technology readiness level of 7–8. The system is controlled by a low-cost Arduino board in a closed-loop control using a
Accuracy of non-algorithm based one axis and dual axis solar trackers is important to determining their performance because the accuracy, which is the degree to which the trackers point towards the sun, determines the amount of irradiance on the PV panel and the incident angle of the
Rotar et al. [38] demonstrated a self-sufficient dual-axis solar tracking system using a stepper motor to regulate PV panel height and azimuth angles. A new set of maintainability-oriented metrics was proposed to track device evaluation and improvement to create a maintainability index. This index enhanced the repairability and maintainability
Findings indicate that single-axis solar trackers employing astronomical calculations with navigation sensors outperform stationary installations by over 57.4%.
Development of a dual-axis solar tracking system is more complex than a single-axis solar tracking system, but a dual-axis system tracks much better as compared to a single-axis system. The aim here is to design and develop a real model for dual-axis solar tracking...
In this study, a novel high accurate sensorless dual-axis solar tracking system controlled by the internal MPPT unit is proposed. The MPPT controller continuously calculates the maximum output power of the PV module at any time, and then, it uses the deviations of the altitude and azimuth angles to find the correct direction of the
The present research proposes a novel concurrent design methodology for optimizing the overall performance of two-axis trackers, allowing to keep a balance between the tracking error and the energy consumption from the design stage, from an optimization approach.
In this study, a novel high accurate sensorless dual-axis solar tracking system controlled by the internal MPPT unit is proposed. The MPPT controller continuously calculates
Dual-axis solar photovoltaic tracking (DASPT) represents a fundamental technology in optimizing solar energy capture by dynamically adjusting the orientation of PV systems to follow the sun''s trajectory
Key Takeaways. Dual axis solar tracking systems can lead to up to 14% more power generation than single axis trackers. Despite their higher upfront cost, they represent a long-term investment with the potential to increase solar power efficiency by 5% to 10%.
the control algorithm to improve tracking accuracy and energy efficiency. Additionally, scalability and cost-effectiveness considerations could be addressed to facilitate the deployment of dual-axis solar tracking systems in commercial and residential settings. REFERENCES
In a comparison of the data obtained from the measurements, 24.6% more energy was seen to have been obtained in the dual-axis solar tracking system compared to the fixed system. This study possesses potential value in small- and medium-sized photovoltaic applications.
Monitoring the energy generated by a solar system based on various weather conditions requires an accurate forecast algorithm. In this research, a new deep learning method called Dual-Axis Solar Tracking System (DA-STS) is presented to increase the hourly energy provided by four dual-axis solar trackers'' real-time forecast accuracy. A novel Artificial Neural
And we have found that a tracking system with a minimum accuracy of 0.2º in the platform position was required. Fortunately, there are tracking systems that can achieve an accuracy of 0.2º, such
the control algorithm to improve tracking accuracy and energy efficiency. Additionally, scalability and cost-effectiveness considerations could be addressed to facilitate the deployment of dual
In this research, a new deep learning method called Dual-Axis Solar Tracking System (DA-STS) is presented to increase the hourly energy provided by four dual-axis solar
The power generation performance of the dual-axis solar tracking system was compared with the fixed-tilted Photovoltaic (PV) system. It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°. The embedded Proportional Integral Derivative (PID) positioning system improves the tracking of
This paper presents the design, construction and evaluation of a high-precision dual-axis solar tracking system with a technology readiness level of 7–8. The system is controlled by a low-cost Arduino board in a closed-loop
Findings indicate that single-axis solar trackers employing astronomical calculations with navigation sensors outperform stationary installations by over 57.4%. Additionally, dual-axis solar trackers utilizing trajectory calculations with navigation sensors yield 67.65% more energy.
Accuracy of non-algorithm based one axis and dual axis solar trackers is important to determining their performance because the accuracy, which is the degree to which the trackers point towards the sun, determines the amount of irradiance on the PV
The present research proposes a novel concurrent design methodology for optimizing the overall performance of two-axis trackers, allowing to keep a balance between the tracking error and
Then, a new design of dual axis solar tracking system was presented by Khalifa and Almutawalli to track the sun horizontally and vertically every 3 minutes and 4 minutes respectively [7]. In terms of passive tracking systems, Zomewords -an American company- developed the first system in 1969. Another passive tracking system with the use of shape memory alloy was developed in
It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°. The embedded Proportional Integral
Dual-axis solar photovoltaic tracking (DASPT) represents a fundamental technology in optimizing solar energy capture by dynamically adjusting the orientation of PV systems to follow the sun''s trajectory throughout the day. This paper provides an in-depth review of the development, implementation, and performance of DASPT.
In a comparison of the data obtained from the measurements, 24.6% more energy was seen to have been obtained in the dual-axis solar tracking system compared to the fixed system. This
It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°. The embedded Proportional Integral Derivative (PID) positioning system improves the tracking of elevation and azimuth angles with minimum energy consumption.
Control System for Dual-Axis Solar Tracking: To accurately track the sun''s movement and control the position of the solar panels in a dual-axis solar tracking system, various algorithms are used
PDF | This research presents a performance analysis of dual axis solar tracking system using Arduino. The use of solar energy is increasing rapidly in... | Find, read and cite all the research you
The power generation performance of the dual-axis solar tracking system was compared with the fixed-tilted Photovoltaic (PV) system. It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°.
In dual-axis solar trackers, the system is positioned along the azimuth and altitude of the Sun, rotating east–west and north–south, as well as using a parallel mechanism , , , , , , , , , , , , , .
It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°. The embedded Proportional Integral Derivative (PID) positioning system improves the tracking of elevation and azimuth angles with minimum energy consumption.
Monitoring the energy generated by a solar system based on various weather conditions requires an accurate forecast algorithm. In this research, a new deep learning method called Dual-Axis Solar Tracking System (DA-STS) is presented to increase the hourly energy provided by four dual-axis solar trackers' real-time forecast accuracy.
Dual-axis solar photovoltaic tracking (DASPT) represents a fundamental technology in optimizing solar energy capture by dynamically adjusting the orientation of PV systems to follow the sun’s trajectory throughout the day. This paper provides an in-depth review of the development, implementation, and performance of DASPT.
The solar tracking accuracy can be improved through active tracking system. The system tilts the solar panel according to the sun's movement through a motor or hydraulic actuator which is controlled by a set of controller unit. This system can be classified into open and closed loops.
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