Dual-axis Tracking Research Articles

Photovoltaic tracking technologies for sustainable electrification: A techno-economic analysis on Western Pelee Island, Canada

This article investigates the economic and technical feasibility of employing various photovoltaic (PV) tracking systems to electrify Western Pelee Island. The systems under consideration include horizontal-axis monthly adjustment (HMA), horizontal-axis continuous adjustment (HCA), vertical-axis continuous adjustment (VCA), and dual-axis tracker (DAT). The analysis includes a techno-economic assessment of these trackers, considering solar, bio, and diesel operation and two dispatch strategies: cycle charging (CC) and load following (LF). The results indicate that the optimal solution is a CC-controlled system equipped with a VCA tracker. The LF-controlled system with this tracker has a higher net present cost (NPC), cost of energy (COE), and renewable fraction by ∼$0.02 M, ∼$0.002/kWh, and 7.6%, respectively. NPC of HMA and COE of HVA-based systems with CC strategies are the most sensitive cases to SOCmin. In load variation, the largest and lowest decrease in COE, respectively, is observed in HVA and DA trackers controlled by CC dispatch strategy. In order for DA trackers to match the performance of VCA trackers, their costs must decrease by approximately 41% and 43% in CC and LF systems, respectively. The financial sensitivity of DA-based systems is higher due to albedo effects. This study provides valuable insights into optimizing PV tracking for the electrification of Western Pelee Island and enhances our understanding of the economic implications associated with dispatch strategies and tracking technologies in sustainable energy planning.

Enhancing solar energy collection with the implementation of a dual-axis tracking system

Abstract This paper describes the design and control of a two-axis solar tracking system that is unique in integration and uncomplicated in structure. Concerning the accumulation of solar energy, the system adopts a Solar Photovoltaic (SPV) power plant model. Theoretical analysis of the output of the system including the impact of the solar radiation was also done and a comparison was made with a fixed axis SPV station provided with fixed stand tilt at 30° south. As shown in the outcomes, the efficiency of the proposed dual-axis tracking system is much higher than that of the keeper-stationary positioning scheme. These results proved the hypothesis of the effectiveness of the proposed SPV system from both experimental and theoretical positions. A comparison of data indicated that the tracking system tapped much more solar energy than the fixed system. Consequently, this research aims at transforming and investigating the feasibility of small and medium scale SPV power uses employing dual-axis solar tracking systems.

Free-form surface-based polar-axis rotational direct solar radiation spectrum measurements

Accurate measurements of direct solar radiation spectra are crucial for atmospheric science, climatology, agriculture, and solar energy. Existing systems depend on costly dual-axis tracking devices, leading to high maintenance and error rates. This study presents a free-form surface-based polar-axis rotating solar direct radiation spectrometer, enabling year-round measurements across all latitudes without mobile tracking. The system operates in the 380–780 nm range with a spectral resolution better than 2 nm. Simulation results demonstrate spectral curve area errors between 0.68% and 1.22%, and outdoor experiments in Changchun, China, confirm the accuracy of measurements against the AM1.5 G standard.

New geographic information system based sustainability metric for isolated photovoltaic systems

The integration of photovoltaic (PV) technologies is vital for achieving sustainable energy solutions in isolated systems. However, A critical challenge that remains is maintaining the sustainability of these systems under the fluctuating conditions of solar irradiance, which is key for isolated energy systems. This study hypothesizes that the sustainability of PV systems can be accurately assessed through a new metric that incorporates performance consistency, variability, and resilience, using real-time energy production data alongside GIS-based solar radiation models. By analyzing fixed PV, concentrated PV (CPV), and dual axis tracking PV (DATPV) systems over a three-year period (2017–2019), The analysis indicates that DATPV systems achieved the highest energy output, with energy ratios exceeding 300% in 2019, though this was accompanied by substantial variability in performance. Fixed PV systems demonstrated the most stable performance, with a consistency term reaching 0.93 and a sustainability score of 0.87 in 2019. CPV systems performed moderately, with a sustainability score of 0.66 in 2017. These results highlight the trade-off between energy capture and operational stability, which is critical for sustainable energy management in isolated systems.

Machine learning and physics-based model hybridization to assess the impact of climate change on single- and dual-axis tracking solar-concentrated photovoltaic systems

Machine learning and physics-based model hybridization to assess the impact of climate change on single- and dual-axis tracking solar-concentrated photovoltaic systems

Automatic solar tracking system: a review pertaining to advancements and challenges in the current scenario

Abstract An automatic solar tracking system is an approach for optimizing the generation of solar power and modifying the angles and direction of a solar panel by considering changes in the position and path of the sun. The performance status of an automatic solar tracking system depends on various factors, including its design, location, and maintenance or repairs. The solar energy from the sun that the Earth intercepts is approximately 1.8 × 1011 MW, which is thousands of times greater than the intensity at which the Earth now uses all other commercially available energy sources combined. Currently, research into automatic solar trackers is on the rise, as solar energy is abundant in nature, but its use in a highly efficient way is still lacking. This paper provides a detailed literature review and highlights some key advancements and challenges associated with state-of-the-art automatic solar tracking systems. The performance of the dual-axis photovoltaic tracking system outperforms that of the stationary systems by more than 27% based on the overall system efficiency. Under diverse weather conditions, the efficiency of the scheduled-based solar tracking systems was enhanced by 4.2% compared with that of the light-dependent resistor-based solar trackers.

Advancing Solar Power Efficiency: Innovations in Material Science and System Optimization for Enhanced Solar Energy Conversion

This study aims to advance solar power efficiency through innovations in material science, surface engineering, and system optimization. The research integrates experimental testing and computational modeling to assess improvements in energy conversion efficiency. The methodology includes testing photovoltaic materials such as perovskite and multi-junction cells, anti-reflective coatings, self-cleaning surfaces, and optimizing panel orientation, cooling systems, and Maximum Power Point Tracking (MPPT) algorithms. Perovskite cells demonstrated a 22% increase in efficiency, while multi-junction cells achieved up to 35% efficiency. Anti-reflective coatings and self-cleaning surfaces improved energy capture by 4% and 7%, respectively. System optimization, including dual-axis trackers and AI-enhanced MPPT algorithms, provided additional efficiency gains of up to 25% and 10%, respectively. These findings demonstrate significant advancements in solar panel performance, providing a clear path for enhancing scalability and commercial viability in diverse environmental conditions. The integration of innovative materials and system optimizations presents a promising solution for making solar energy more sustainable and cost-effective. Future research should focus on improving the durability and reducing the costs of these technologies for widespread adoption.

Adaptive control systems for dual axis tracker using clear sky index and output power forecasting based on ML in overcast weather conditions

The use of artificial intelligence in renewable energy systems increases energy generation and improves energy system management. The control system of many solar trackers is designed for maximum radiation power conditions and shows decent performance indicators, but during rapidly changing weather conditions or cloudy days, the performance of the solar trackers is reduced due to moving parts and low irradiance. Some studies show that the horizontal configuration produces more energy with scattered solar radiation than solar tracking systems. This work shows the possibility of using solar tracking systems under different weather conditions and cloudy days. To achieve the goals, a new adaptive control system for dual-axis solar trackers with astronomical tracking was developed, which differs from traditional controls in the use of horizontal configurations under certain weather conditions. The assessment of spatio-temporal weather conditions was carried out using the Clear Sky Index (CSI) and was complemented by forecasting the panel's power output. The study found that at 0.4 CSI values, the horizontal configuration exhibits higher power output than solar tracking systems, providing the potential to use the threshold for adaptive control. The developed system is more efficient by 18.3 %, 14.9 %, and 10.01 % than the horizontal configuration, single-axis, and dual-axis solar trackers.

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.

Notes on Measuring Concentration Ratio Distribution for a Solar Tower Using Moonlight

The authors' original concept of indirect solar flux mapping of a heliostat field measures CRD using a compact stationary array of moonlight illuminometers on the receiver aperture and a reference moonlight illuminometer on the dual-axis moon tracker. Two sets of moonlight concentration experiments (CCD camera + white target; concentrated lunar beam passing across the linear array of illuminators) were carried out on 63 heliostats at Badaling Solar Tower Power Plant in Beijing on a full moon night in 2018. How the sun and moon shapes differ for CRD as light sources on a solar dish is investigated. Solar/lunar CRDs are similar. Another lunar flux mapping model is also presented, allowing different moon shapes to estimate the solar CRD and contribute improvements in extrapolating measured lunar CRDs to a solar tower working with the real Sun by repeated smooth-filtering. In this paper, some unknown factors, effects, and improvements are carefully considered to enhance the CRD measurement accuracy of a solar tower power plant by using moonlight concentration.

Photovoltaic penetration potential in the Greek island of Ikaria

The operation of Distribution Networks (DNs) has been affected by the ongoing energy transition, gradually incorporating more Distributed Energy Resources (DERs), mainly Renewable Energy Sources (RES), as well as Energy Storage Systems (ESS) sustainably enhancing DN’s flexibility. In the case of the non-interconnected island of Ikaria, Greece, with high solar and wind potential, the DN includes conventional generators, Photovoltaic systems (PVs), wind farms and a hydro-pumped ESS. Scope of this study is to assess the possible impact of the PVs expansion considering either: i) fixed, ii) single-axis or iii) dual-axis tracking panels. For this purpose, CERTH’s in-house INTEMA.grid platform is used. Tracking mechanism’s effectiveness is studied considering that the expansion doubles or triples the rated power of the existing, fixed 0.4 MW PVs, following the directions of the Distribution System Operator (DSO). Additionally, a monthly analysis is presented, because Ikaria is an island with extremely higher load during summer months due to tourism. According to the results, if the current PV capacity is doubled or tripled, a dual-axis expansion yields 16.0% or 21.3% yearly production increase compared to fixed panels, respectively, with the single-axis effect though being much higher (14% or 18.7%, respectively) than the incremental effect of the second axis (further comparative 1.8% or 2.3%, respectively). The effectiveness of tracking mechanisms is highlighted during summer months and particularly early in the morning or late in the afternoon. Finally, environmental and economic indicators for the proposed installations are assessed.

Design and implementation of a dual-axis sun tracker for an Arduino-based micro-controller photovoltaic system

This research investigates the optimization of solar panel performance by designing and implementing a low-cost Dual-Axis Sun Tracker (DAST) for an Arduino-based Microcontroller Photovoltaic System. The primary aim is to enhance solar energy extraction by precisely aligning the panel perpendicular to the sun's position, maximizing output voltage and current efficiency compared to fixed systems. The DAST employs two micro servo motors, SG90, controlled by a specialized chronological algorithm in offline mode, ensuring strategic alignment and scheduled adjustments. A comprehensive evaluation of the DAST's performance is conducted, contrasting it with a Fixed System to underscore the advantages of solar tracking. As a result, a DAST produces higher output than a fixed system by 0.896W during sunny days and 0.206W during cloudy days. Besides, the efficiency of PV panels in the DAST is 71.65%, and fixed is 49.66% during sunny days, while DAST is 22.96% and fixed is 17.91% during cloudy days.

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.

Solar Energy Received on Flat-Plate Collectors Fixed on 2-Axis Trackers: Effect of Ground Albedo and Clouds

This study investigates the performance of isotropic and anisotropic diffuse models to estimate the total solar energy received on flat-plate collectors fixed on dual-axis trackers. These estimations are applied at twelve sites selected in both hemispheres with different terrain and environmental conditions. The diffuse (or transposition) models used in this study are the isotropic Liu-Jordan (L&J), Koronakis (KOR), Badescu (BAD), and Tian (TIA), and the anisotropic Hay (HAY), Reindl (REI), Klucher (KLU), Skartveit and Olseth (S&O), and Steven and Unsworth (S&U). These models were chosen because of their simplicity in the calculations and minimum number of input values. The results show that a single transposition model is not efficient for all sites; therefore, the most appropriate models are selected for each site under all, clear, intermediate, and overcast conditions in skies. On the other hand, an increase in the ground albedo in the vicinity of the solar installation can increase the annual inclined solar availability on a two-axis tracker by at least 9% on average. Further, a linear dependence of the annual inclined solar energy on the variation of the ground albedo was found. Also, a linear relationship exists between the annual diffuse-fraction and cloud-modification factor values at the 12 sites.

Hybrid Photovoltaic Output Forecasting Model with Temporal Convolutional Network Using Maximal Information Coefficient and White Shark Optimizer

Accurate forecasting of PV power not only enhances the utilization of solar energy but also assists power system operators in planning and executing efficient power management. The Temporal Convolutional Network (TCN) is utilized for feature extraction from the data, while the White Shark Optimization (WSO) algorithm optimizes the TCN parameters. Given the extensive dataset and the complex variables influencing PV output in this study, the maximal information coefficient (MIC) method is employed. Initially, mutual information values are computed for the base data, and less significant variables are eliminated. Subsequently, the refined data are fed into the TCN, which is fine-tuned using WSO. Finally, the model outputs the prediction results. For testing, one year of data from a dual-axis tracking PV system is used, and the robustness of the model is further confirmed using data from single-axis and stationary PV systems. The findings demonstrate that the MIC-WSO-TCN model outperforms several benchmark models in terms of accuracy and reliability for predicting PV power.

Estimation of the solar radiation intensity on photovoltaic surfaces using anisotropic Models, investigation of influence of tilt angles and solar trackers: A case study for the southeastern of Türkiye

The estimation of total solar radiation (TSR) intensity is crucial for the performance, design, and economic assessment of photovoltaic (PV) energy systems operating in different geolocations and climates. Various transposition Models can be utilized in performance calculations for PV systems in the estimation of TSR on tilted and tracked PV surfaces. Solar tracking equipment can be applied to optimize the TSR gathered by solar PV surfaces. In addition, energy gain can be considerably increased with the use of optimally tilted PV surfaces. This study aims to perform a reliable estimation of TSR for fixed and tracked PV surfaces by applying Hay-Davies, Klucher, Reindl, HDKR, and Perez anisotropic transposition Models over a specific period in Şanlıurfa Turkey. This study does not identify the best anisotropic Model, but with a relative cross-comparison, it points out the values of high variability in outputs and disagreements between different Models. The study highlights the potential of using multiple transposition Models to provide more robust estimates for the annual, seasonal, and monthly solar energy gain in desired geolocations. The annual optimal tilt angle (OPTA) for Şanlıurfa province is estimated to be 30°-31°, which is close to the latitude but below the latitude (6°-7°) of the respective geolocation. The monthly OPTA throughout the year is between 3° in July and 64° in December. It is revealed that the loss in annual TSR does not surpass 0.5% due to the 5° offset of the tilt angle from the OPTA of fixed PV surfaces. The gain in annual TSR for a fixed surface compared to a horizontal surface is estimated to be between 6.05% and 8.24%. The gain in annual TSR for a north-south oriented single-axis tracker (the axis of rotation is on the east-west plane) is estimated between 22.03% and 25.68%, whereas for a dual-axis tracker, it is estimated between 31.49% and 36.66%. It is inferred that, compared to a single-axis tracking, a dual-axis tracking can yield approximately 8.84% more energy. In light of this research, it is recommended that the solar energy potential of the Şanlıurfa can be significantly enhanced by installing tracking systems for maximal generation of solar energy. In the absence of a tracking system, the annual OPTA setting of a PV surface can be a typical strategy. On the other hand, this study reveals that some solar parameters involved in anisotropic Models significantly contribute to the quality of the estimation results. The Models presented in this study can be used to accurately estimate TSR on PV surfaces in various implementations in any place of Türkiye and around the world.

Experimental and numerical study of a linear Fresnel solar collector attached with dual axis tracking system

The demand for an alternative to fossil fuel energy is increasing as environmental and economic challenges rise. The linear Fresnel solar collector is considered a promising option for obtaining thermal energy at medium and high temperatures. A linear Fresnel solar collector consists of a number of mirror strips that are used to focus solar beam radiation toward a line receiver. This study aims to obtain a clear evaluation of the thermal performance of a linear Fresnel solar collector through design, manufacture, and experimental testing under different outdoor conditions in Baghdad over various periods. There have been tests on April 1 and 22, as well as May 8 and 27, using water as the working fluid. The solar collector used is an aluminum base measuring 200 cm in length and 150 cm in width on which 14 mirror strips from each side are fixed. The receiver (absorber copper tube) has a length of 200 cm and a height of 60 cm from the base. The solar collector is provided with a dual-axis tracking system (North-South and East-West) for ensuring that the solar concentrator faces the sun at normal incidence during all daytime hours. The best thermal performance of the solar collector was observed on May 27, where the average useful energy, thermal and exergy efficiency reached 1042.61 W, 39.15 %, and 1.31 %, respectively. The present study also included a numerical analysis done using computational fluid dynamics (CFD) to verify the experimental results. The numerical results confirmed the validity of the experimental results.

Study on the carbon migration from fossil fuel to liquid methanol by integrating solar energy into the advanced power system

Coupling advanced systems with carbon dioxide (CO2) capture and CO2-to-methanol technologies is a possible solution for both greenhouse gas emissions and low-carbon use of fossil energy. In view of this, this study further develops an advanced molten carbonate fuel cell (MCFC)/steam turbine (ST) hybrid system. The existing single pressurized liquefaction for storing CO2 is expanded to co-exist with liquid methanol synthesis for storing CO2. In detail, the valid thermodynamic models are presented, and the evaluation criteria for energy conversion are described. The case study shows that the energy efficiency of the referenced MCFC/ST system reaches about 62.60 %, without cutting down this performance, the photovoltaic methanol efficiency is in the range of about 54 %–63 %, which is at a current leading level. This study also investigates the effect of oxygen purity in cryogenic air separation unit (ASU), hydrogen production pressure of proton membrane electrolytic cells (PEMEC), and incident irradiation on CO2-to-methanol conversion. The results indicate that O2 purity of 0.97 in ASU, H2 production pressure of 13.6 bar in PEMEC and a dual-axis tracking method is recommended. These findings provide theoretical guidance for improving the CO2-to-methanol performance and providing a possible solution to the storage of intermittent renewable electricity.

Understanding the impact of sky diffuse irradiance on curved photovoltaic modules

Modules utilized in vehicle-integrated photovoltaics (VIPV) have particularities that make them differ from standard PV modules. These particularities are related to their curvature and operating conditions (changing locations, orientations, etc.) and they need to be addressed in the characterization. A vital characterization test is the angular response test, which allows obtaining the electrical response of the module under different angles of incidence and orientations. Results from these tests on real commercial modules presented some dispersion, which is related to diffuse irradiance. Two outdoors experiments involving a programmable dual-axis tracker were conducted to verify its impact: the first one was made with a 1D highly curved module under cloudy sky conditions to identify the effect of diffuse irradiance on such modules and the second experiment assessed the angular response of a 2D commercial curved module under clear sky conditions. Based on the findings, recommendations are given to minimize dispersion in outdoors angular response measurements.

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.