Photovoltaic Tracking System Research Articles

Techno-economic and GHG mitigation assessment of concentrated solar thermal and PV systems for different climate zones

In this study, energy production by two solar energy technologies, namely concentrated solar power (CSP) and photovoltaic (PV) power, is compared from a technical, economic and environmental perspective. Initially, a 50 MW CSP plant is modeled and simulated at four selected sites in Pakistan. Then, the most feasible location of the CSP plant is compared with the solar PV plant of the same capacity. The effect of the solar thermal storage size and cooling system of the CSP system is investigated, while the photovoltaic tracking system is investigated to evaluate the technical and economic performance of the power plants. Technical performance is evaluated based on energy generation and capacity factors metrics, while economic performance is evaluated with respect to levelized cost, payback period and net present value. In addition, environmental criteria such as reducing greenhouse gas emissions (GHG), saving fossil fuels, and life-cycle water consumption are evaluated. From the results, it was concluded that the CSP plant located in Quetta is technically and economically viable. The capacity factor of the CSP plant is 36.6% compared to 19.8% for the PV plant, while the solar-to-electrical efficiency of the CSP plant is 14.2% compared to 20.8% for the PV plant. The required land area is 2.77 acres/GWh for the CSP plant and 2.33 acres/GWh for the PV plant, while the net capital cost of the CSP plant is five times higher than that of the PV plant. Various design parameters are optimized to obtain the minimum levelized cost of energy (LCOE) for both CSP and PV plants. The results of CSP and PV plants indicate that the LCOE can be reduced to 11.57 cents/kWh and 4.69 cents/kWh, respectively. Thus, the CSP plant performs better from the technical point of view while the PV plant performs better from the economic perspective.

A Review of Time-Based Solar Photovoltaic Tracking Systems

Solar energy is the cleanest and most abundant form of energy that can be obtained from the Sun. Solar panels convert this energy to generate solar power, which can be used for various electrical purposes, particularly in rural areas. Maximum solar power can be generated only when the Sun is perpendicular to the panel, which can be achieved only for a few hours when using a fixed solar panel system, hence the development of an automatic solar tracking system. Over the years, different solar tracking systems have been proposed and developed, and a few have been reviewed in the literature. However, the existing review works have not adequately provided a comprehensive survey and taxonomies of these solar tracking systems to show the trends and possible further research direction. This paper aims to bridge these gaps by extensively reviewing these time-based solar tracking systems based on axis rotation and drive types. Lessons learned from the comprehensive review have been highlighted and discussed. Finally, critical open research issues are identified and elaborated.

Techno-Economic Analysis of Photovoltaic Hydrogen Production Considering Technological Progress Uncertainty

The application of photovoltaic (PV) power to split water and produce hydrogen not only reduces carbon emissions in the process of hydrogen production but also helps decarbonize the transportation, chemical, and metallurgical industries through P2X technology. A techno-economic model must be established to predict the economics of integrated PV–hydrogen technology at key time points in the future based on the characteristics, variability, and uncertainties of this technology. In this study, we extracted the comprehensive technical factors (including PV tracking system coefficient, PV conversion efficiency, electrolyzer efficiency, and electrolyzer degradation coefficient) of an integrated PV–hydrogen system. Then, we constructed a PV hydrogen production techno-economic (PVH2) model. We used the levelized cost of hydrogen production (LCOH) method to estimate the cost of each major equipment item during the project lifetime. We combined the PVH2 and learning curve models to determine the cost trend of integrated PV–hydrogen technology. We developed a two-dimensional Monte Carlo approach to predict the variation interval of LCOH for PV–hydrogen projects in 2030 and 2050, which described the current technology variability with variable parameters and the uncertainty in the technology advancement with uncertain parameters. The results showed that the most critical factors influencing LCOH are PV conversion efficiency and the capital cost of the electrolyzer. The LCOH of PV to hydrogen in China will drop to CNY 18–32/kg by 2030 and CNY 8–18/kg by 2050. The combination of a learning curve model and a Monte Carlo method is an effective tool to describe the current variability in hydrogen production technologies and the uncertainty in technological progress.

Techno-economic comparative study of grid-connected PV/reformer/FC hybrid systems with distinct solar tracking systems

The purpose of this study is to analyze and compare the techno-economic performance of grid-connected Hybrid Energy Systems (HES) consisting of Photovoltaic (PV) and Reformer Fuel-Cell (RF-FC) using different types of solar PV tracking techniques to supply electricity to a small location in the City of Chlef, Algeria. The PV tracking systems considered in this study include fixed facing south at four different angles (32°, 34°, 36°, 38°), horizontal-axis with continuous adjustment, vertical-axis with continuous adjustment and a two-axis tracking system. The software tool HOMER Pro (Hybrid Optimization of Multiple Energy Resources) is used to simulate and analyze the technical feasibility and life-cycle cost of these different configurations. The meteorological data, consisting of global solar radiation and air temperature, used in this study was collected from the geographical area of the City of Chlef during the year 2020. This study has shown that the optimal design of a grid-connected hybrid PV/RF-FC energy system with Vertical Single Axis Tracker (VSAT) leads to the best economic performance with low values of Net Present Cost (NPC), Cost of Energy (COE) with a Positive Return on Investment (ROI) and the shortest Simple Payback (SP) period. In addition, from the simulation results obtained, it can be concluded that the Horizontal and Vertical Single-Axis Trackers (HSAT and VSAT) as well as the Dual-Axis Tracker (DAT) are not always cost effective compared to the Fixed Tilt System (FTS). Therefore, it is necessary to carefully analyze the use of each tracker to assess whether the energy gain achieved outweighs the overall shortcomings of the tracker.

Review of recent water photovoltaics development

Abstract Photovoltaic (PV) power generation plays an important role in the clean energy. Placing PV on water has therefore become an interesting alternative siting solution. In this paper, the floating photovoltaic system is divided into four categories: fixed pile photovoltaic system, floating photovoltaic system, floating platform system and floating photovoltaic tracking system and the principles, technologies and future challenges of PV systems on water will be reviewed. Other challenges encountered with water PV are discussed and future research directions are presented.

Optimalisasi Daya Output Pada Photovoltaic Penggunakan Sistem Tracking dan Fuzzy Logic Controller

Photovoltaic is one of the environmentally friendly power plants. One of the problems using photovoltaic is the low efficiency level. Therefore, a method is needed to optimize photovoltaic performance. The use of fuzzy logic control for dual axis tracking system is used in this study to optimize photovoltaic performance. The dual axis tracking system functions to keep the photovoltaic always perpendicular to the direction of the sun's arrival so that it has more optimal output power. The input of the tracking system comes from the LDR sensor which is installed on each side of the Photovoltaic. This sensor is combined with RTC to anticipate weather changes (cloudy). LDR and RTC sensor data as input for fuzzy logic controller. Based on the results of the research, the output power of the Photovoltaic tracking system is 9.363 Watts or 46.82% of the Photovoltaic specifications. Meanwhile, static photovoltaic with conventional installation has a power of 7.247 Watt or 36.23% of the specification. So that Photovoltaic with fuzzy logic control for dual axis tracking system is 29.20% more optimal.

Quality Improvement of Operation of The Tracking Photovoltaic Systems

Achievements in the field of Renewable Energy Sources (RES) have revolutionized the traditional and centralized energy model into a modern and decentralized one, utilizing existing energy infrastructure. Photovoltaic modules have become a popular source of emission-free and renewable energy. The prospects for the future of the energy market are promising, thanks to technological advancements in the Renewable Energy Sources industry. The optimal conditions for the operation of a photovoltaic module are a temperature of 25°C, air mass of 1.5, and sunlight intensity of 1000 W/m². Furthermore, industry literature confirms that the most optimal angle of solar radiation incidence, guaranteeing the highest energy yield, is 90 degrees concerning the surface of the photovoltaic module. Such conditions are challenging to achieve in the daily operation of micro photovoltaic installations. Scientific research on RES focuses on creating new photovoltaic cells, optimizing existing installations, and facilitating economic improvements in generator procurement. In this paper, the authors investigate the impact of environmental conditions on the efficiency of photovoltaic cells, paying attention to temperature and the angle of solar radiation incidence.

Quality Improvement of Operation of The Tracking Photovoltaic Systems

Achievements in the field of Renewable Energy Sources (RES) have revolutionized the traditional and centralized energy model into a modern and decentralized one, utilizing existing energy infrastructure. Photovoltaic modules have become a popular source of emission-free and renewable energy. The prospects for the future of the energy market are promising, thanks to technological advancements in the Renewable Energy Sources industry.

Comparison, evaluation and prioritization of solar photovoltaic tracking systems using multi criteria decision making methods

The purpose of the present study is to evaluate and compare solar tracking systems connected to the grid. The solar systems considered were Fixed Tilt (FT), Vertical Continuous Adjustment (VCA), Horizontal adjustment (Monthly Adjustment (HMA), Continuous Adjustment (HCA)) and Two-Axis (TA) tracking system. Technical, economic and environmental assessment for an industrial consumer in southern Iran was performed by HOMER software. Unlike previous studies, multi-criteria approaches have been used to evaluate solar tracking systems. Due to the economic or technical superiority of each tracking system, solar tracking systems were prioritized using multi-criteria decision-making approaches. SWARA was used to weight criteria and WASPAS, EDAS and ARAS methods were used for prioritization of solar tracking systems. Technical evaluation showed that most of the electricity was generated by the TA and it was 31.8 % more than the FT system. Economic evaluation showed that the minimum LCOE was related to FT and the maximum LCOE was related to horizontal tracking systems (8.8 % more than FT system). Environmental assessment also showed that the reduction of CO2 emissions in the TA system is more than the FT system. This evaluation, taking into account all technical, economic and environmental aspects, showed that the priority of systems in the case study was HMA < HCA < FT < VCA < TA.

Benefits of MPP tracking PV system using perturb and observe technique with boost converter

In recent decades, researchers have become interested in the photovoltaic (PV) system as one of the renewable energies. There are nonlinear I-V and P-V features in the PV generators. The greatest power generated varies with temperature and irradiation. To increase PV power, it is necessary to watch MPP carefully. In order to avoid some of shortcomings of conventional perturb &amp;amp; observe (P&amp;amp;O) MPP tracking approach and increase the transient responsiveness and decrease oscillations of steady-state terminal voltage, this study introduces a modified (P&amp;amp;O) MPPT algorithm employing fuzzy logic-based variable step size. An indoor simulated PV source built from a typical solar panel, DC power supplying, a DC-DC converter, in addition to P&amp;amp;O-based MPPT controlling unit was used to create and test the suggested MPPT algorithm. To demonstrate the P&amp;amp;O strategy's performance benefits under both constant and fluctuating irradiations and temperatures, their simulation under unsteady state circumstances is already performed with MATLAB/Simulink. Results of the simulations demonstrate that the photovoltaic simulation system can precisely monitor the highest power point. According to the simulation findings, efficiency is attained at 95% under typical test settings and at 96% when the weather is unpredictable and there are changes in temperature and irradiance.

Integration of Solar Energy Supply on Smart Distribution Board Based on IoT System

Today’s residential electricity management depends heavily on the Internet of Things (IoT). It is still challenging to create practical, affordable smart condition monitoring, protection, and control systems for residential distribution networks. The performance of the developed system is evaluated for a variety of residential electric loads with different energy consumption patterns. In this paper, a photovoltaic tracking system and also a cleaning system will be connected to a smart board. All input data will be gathered and sent over Bluetooth using a working prototype built on an Arduino board. The mobile application is also used to let individual users monitor the system in real-time, alert users about electrical system issues, display their energy use in real time, and provide other essential alerts and warnings.

Technical, Economic and Environmental Comparison of Three Different Grid-Connected PV Tracking Systems Power Plant Under Kurdistan Region/Iraq Climate Condition

In this paper, a 1 MW grid-connected PV system was performed and simulated numerically in Zakho city, using hourly meteorological data for three systems; fixed, single-axis, and dual-axis tracking systems for solar module. The analysis of this study is based on technical, economic, and environmental feasibility. The analysis based on the actual 3 PV solar panels using different tracking systems which installed on the roof of the Engineering college of Zakho University. The evaluation findings suggest that PV technology is quite promising in this location, with annual yield factors of (1416 kWh/kW), (1694 kWh/kW), and (1902 kWh/kW) for the three systems, respectively. Furthermore, the proposed system's capacity factors are 16.2 percent, 19.3 percent, and 21.70 percent. The economic growth of a 1MW grid-connected photovoltaic (PV) system adjusted for meeting the daily peak load in Zakho is analyzed and compared based on the cost of electricity (COE), net present value (NPV), payback period (PBP), and the energy payback time (EPBT) for three systems in the present work. The COE for the three proposed systems, fixed, 1st axis, and dual axes solar tracking systems, was 0.0826 USD/kWh, 0.0489 USD/kWh, and 0.0441 USD/kWh, respectively, which indicated the tracking system is economically feasible. The findings indicate a favorable trend, implying that large-scale photovoltaics of dual-axis systems might be a feasible option for addressing future power needs.

Experimental Investigation and Comparison of the Net Energy Yield Using Control-Based Solar Tracking Systems

As the world trend is going towards renewable energy, solar photovoltaic (PV) energy shines the most due to the low generation cost especially by using the latest PV cell technologies and materials, although the conventional silicon cell has an efficiency in the range of 15-16%. A PV tracking system (PVTS) could be a considerable method to increase electrical PV efficiency. In this study, the performance enhancement of the daily output power and energy has been experimentally investigated using single- and dual-axis tracking mechanisms for flat-plate conventional PV panels under the insolation conditions of the Eastern province of Saudi Arabia (SA). In the current study, the active PVTS has been designed and implemented with PID controllers and controlled in real-time with an embedded system. The fixed-tilt (FTPV), single-axis solar tracking system (SAST), and dual-axis solar tracking system (DAST) were tested simultaneously under clear-sky conditions. The PV electrical energy balance has revealed that the energy consumed by the electrical controllers of the SAST and DAST is 3.4% and 3.9%, respectively. In addition, the energy losses due to the actuators of the SAST and DAST are 7.8% and 13.0%, respectively, where they contributed mainly to the energy losses. However, the PV energy production by the DAST was high enough to compensate for the higher actuating mechanism losing rate compared to the SAST and performed incremental net energy output of around 8.64%. On other hand, the DAST and SAST were more efficient than the FTPV recording higher net energy increase by 28.98% and 18.73%, respectively.

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

Solar photovoltaic (PV) energy systems are one of the most widely deployed renewable technologies in the world. The efficiency of solar panels has been studied during the last few decades, and, to date, it has not been possible to displace the production of energy using crystalline silicon wafer-based technology whose efficiency has reached values around 26.1%. Moreover, using solar tracking PV systems has become a feasible alternative to increase the electric output of PV silicon technologies instead of using the conventional fixed PV installation on a flat or sloping surface. The following study has compared fixed and dual-axis sun-tracking PV panels in order to quantify the enhancement associated with the amount of energy harvested when using dual-axis tracking PV systems in the city of Manta, located in a coastal region of Ecuador. In order to carry out this study, an IoT monitoring system based on Raspberry Pi3 and Arduino platforms was used. Measurements of solar radiation (W/m2), light intensity (Lux), temperature (°C), short-circuit current (A), and open-circuit voltage (V) were taken every minute for both systems. The results prove that the dual-axis tracking PV system produces, on average, 19.62% more energy than the static PV system. These results present an 8.62% energy increase with respect to a previous study carried out in an equatorial region with similar characteristics to those of the city of Manta, where a one-axis tracking PV system was used.

Integration of solar energy supply on a smart distribution board based on IoT system

Modern electricity management of solar power supply at the smart distribution board is heavily dependent on the Internet of Things (IoT). It is still difficult to create practical, affordable intelligent systems for condition monitoring, protection and control at the smart distribution board of distribution networks. Smart grids use the capabilities of information and communication technologies, especially the Internet of Things, to improve the sustainability, quality and productivity of energy production and demand forecasting, as well as to reduce resource consumption and increase the integration of renewable energy sources. The performance of the developed system is evaluated for a variety of residential electrical loads with different energy consumption patterns on a smart distribution board. In this project, the photovoltaic tracking system as well as the cleaning system will be connected to the smart board. All the input data will be collected and sent via Bluetooth/WI-FI by a working prototype built on an Arduino board, which can independently collect and monitor the real-time energy and environmental conditions of solar plants. The mobile application is also used to allow individual users to monitor the system in real time, notify users of electrical system problems, display real-time energy consumption, and provide other important notifications and alerts to the remote user when there is a deviation of solar power production quality parameters from a predefined set of standard values. A number of improvements are also proposed for further integration with Internet of Things (IoT) and smart home technologies.

Solar Transposition Modeling via Deep Neural Networks With Sky Images

This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{\circ }$</tex-math></inline-formula> arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -dimensional vector, where <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. These profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

The comparison of dual axis photovoltaic tracking system using artificial intelligence techniques

&lt;span&gt;In this paper, the efficiency of photovoltaic panels is improved by adding a sun tracking system. The solar tracking system is used for tracking the sun so that photovoltaic always faces the sun. This system uses a dual axis consisting of horizontal rotation axis and a vertical rotation axis. The horizontal rotational axis motion is to follow the azimuth angle of the sun from north to south. Then, to follow the sun's azimuth angle from east to west is the vertical axis motion. Both types of movements are controlled using a PID controller that is optimized with an artificial intelligence approach, namely particle swarm optimization (PID-PSO), firefly algorithm (PID-FA), imperialist competitive algorithm (PID-ICA), bat algorithm (PID-BA), and ant colony optimization (PID-ACO). Experiments of various approaches were carried out and the corresponding performance compared. The experimental results show that PID-BA performs best in terms of settling time and overshoot. The results also allow the comparison of different PID controller and the calculation of the fastest completion time.&lt;/span&gt;

A Techno-Economic Comparative Study of a Grid-Connected Residential Rooftop PV Panel: The Case Study of Nahr El-Bared, Lebanon

Lebanon suffers from daily electricity shortages. The country has paid much attention to renewable energy sources, particularly solar, to gradually replace conventional energy. Installing a photovoltaic (PV) system becomes increasingly attractive for residential consumers due to the rising electricity tariff rates while it reduces the dependency on domestic power generators. No known study has dealt with the investigation of potential grid-connected rooftop PV systems with various sun-tracking modes and PV technologies in Nahr El-Bared, Lebanon. Consequently, the main objective of the current paper is to investigate the feasibility of a 5kW grid-connected PV system of various technologies (mono-crystalline silicon and poly-crystalline silicon) and sun-tracking modes including fixed tilt and 2-axis systems for rooftop households in Lebanon. The Nahr El-Bared camp was the case study was of the paper. RETScreen Expert software was used to evaluate the techno-economic performance of the proposed systems. The results show that the annual electrical energy from a fixed 5kW PV panel tilted at an optimal angle ranged from 8564.47kWh to 8776.81kWh, while the annual electrical energy from the PV tracking system was within the range of 11511.67-12100.92kWh. This amount of energy output would contribute significantly to reduce the energy shortage in the country. A typical household was selected to establish a load profile and load supply during both grid availability and outage periods. The highest energy consumption that can be covered by the PV systems was recorded during the spring and summer seasons. Also, the average energy production cost ranged from 0.0239 to 0.0243$/kWh for all the proposed systems. It was concluded that a 5kW grid-connected rooftop PV system could be economically justifiable. Finally, this study tried to increase the awareness about utilizing PV sun-tracking systems and the feasibility of small-scale grid-connected rooftop PV systems in the selected regions. The results of this research can help investors in the energy and building sectors.

The Optimum PV Panels Slope Angle for Standalone System: Case Study in Duhok, Iraq

Due to the high operation and maintenance charges of the photovoltaic (PV) tracking systems, it is better to install the PV panels at a stationary angle which is considered as an optimum slope angle. Usually the optimum annually slop angle equals to latitude. However, Duhok site (latitude 36°50’40.6” N, longitude 43°01’05.3” E) has a special case because it’s located in valley between two mountains where the eastern sides of these mountains block the sunlight at the early morning. This paper aims at finding the optimum annually slop angle that makes the solar panels in this site generate the highest possible amount of electrical energy by capturing largest amount of solar radiation at this period when the sun appears from behind the mountain. HOMER software is used to simulate the suggested standalone PV system at the study site. The optimization outcomes present that the optimum annually slope angle for the PV panels should be equal to 25 °.

Model Development and Validation of a Dual-Axis PV Tracking System: A Case of South Africa

Dual axis photovoltaic (PV) tracking system is considered in general to be a poor investment. This is mainly due to the substantial initial investment costs that these systems carry. However, in recent years, solar panels and accompanying component costs have decreased significantly. Additionally, electricity price hikes in South Africa have compelled most of the country’s citizens to reconsider their sources of electrical energy. A popular alternative to grid energy in South Africa is the use of photovoltaic systems. Careful consideration is required when choosing from the various systems available on the market. The main method for maximizing the output power of these systems is to introduce solar tracking systems. Therefore, in this paper, a model of a dual axis tracking system is developed and validated against a real-world plant in the Bloemfontein region in South Africa. The presented model was observed to be accurate to within an error rate of 6.39%. Additionally, the performance of the inverters of the PV tracking systems were evaluated and discussed. The validated model may prove to be an excellent tool for energy managers to determine the feasibility of such systems, compared to conventional photovoltaic setups.