Panel Orientation Research Articles

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.

Long-term performance analysis of a large-scale photoVoltaic plant in extreme desert conditions

This study comprehensively evaluates the performance and operational challenges of a 9 MW grid-connected photovoltaic (PV) system in Timmimoun, southern Algeria, after eight years of operation. We identified a significant linear correlation (R2 = 0.73) between increased ambient temperatures and decreased PV module efficiency, underscoring the need for effective thermal management strategies. The investigation also examines potential solutions, such as cooling mechanisms, optimization of panel orientation and tilt angles, and development of temperature-resistant materials. Adhering to the International Energy Agency IEC 61724 standard, our analysis reveals a yield factor of 5.04 h/day, a yield ratio of 7.04 h/day, a performance ratio of 73 %, and a capacity factor of 21 % in 2023. Over its operational lifespan, the system has generated 133.43 GW h of energy, mitigating 1.01 105 tons of CO2 emissions. This long-term study provides critical insights into the performance and reliability of PV systems in hot desert climates, offering valuable guidance for future large-scale solar installations and contributing to the transition towards a sustainable energy future.

Rapid assessment of solar PV micro-system energy generation in Poland based on freely pvlib-python library

Abstract Poland has experienced a remarkable growth in renewable energy adoption, notably in photovoltaic (PV) solar systems. The majority of installations are prosumer PV micro-installations, exceeding predicted capacity targets outlined in the Energy Policy of Poland until 2040. Despite the significant growth in installed PV capacity, there is still a lack of comprehensive research focusing on fast assessment of energy generation capacity for solar PV micro-systems. This study aims to address this gap by providing a comprehensive analysis of energy production potential across different configurations and locations in Poland. Using geocoding techniques, solar irradiation data from PVGIS database and pvlib-python library, a methodology was developed to rapidly estimate energy generation from 1 kWp solar PV systems . Results reveal spatial disparities in energy yield from solar PV micro installations in Poland, influenced by factors such as geographical location and panel orientation and inclination. Recognizing that the presented energy indicators provide valuable initial parameters for determining solar PV system power output, this data can serve as a critical reference point for stakeholders, assisting them in estimating potential energy generation capacities in different regions of Poland.

Design and Analysis of the Effect of the Number of Membership Functions on the Accuracy of the Fuzzy Controller in a Sun Tracking System

Purpose: To investigate how the number of rules in the fuzzy controller affects the single-axis solar tracking system's orientation accuracy. Methodology: Design and compare FLC49 and FLC25 controllers, each with different organic rules and functions. To improve the system efficiency by accurately measuring the maximum power point, the controller receives comparison results from the light sensors installed on the solar panels. We study and analyze the controllers, selecting the best one based on the accuracy of the solar panel orientation. Using the FLC output to operate a two-phase SM. Findings: This study developed a sun tracking system using Matlab/Simulink and compared FLC49 and FLC25 controllers. FLC49 performed better in simulations, with lower settling time and overshoot. The number of rules significantly influenced accuracy, and it also showed lower transient ripple magnitudes, accelerating time response. Unique Contribution to Theory, Practice and Policy: The research investigates the effectiveness of rules in a fuzzy controller and recommends the optimal number of windings to achieve precision in controlling a stepper motor. The study explores the use of 49-rule and 25-rule fuzzy logic controllers to control a stepper motor based on LDR sensor inputs. The researchers found that while both controllers had similar steady time error and overshoot, they differed in orientation accuracy, with the 49-roll fuzzy controller being more accurate in orientation. This single-axis solar tracking system optimizes solar energy conversion into electricity.

Evaluating water ingress in glass fiber plastic/Nomex honeycomb panels under varying panel orientation

The paper presents the results of experimental and numerical investigations on water ingress trapped in aircraft honeycomb panels. The ingress of atmospheric water during aircraft service may cause minor or major damages of airplane crucial components. The percentage of water/ice filling honeycomb cells is an important factor related to possible cell damage. This study is focused on the analysis of the following inspection parameters: 1) influence of panel orientation (horizontal, vertical and Inclined at 30, 45 and 60°) on the efficiency of water detection, 2) efficiency and optimization of a heating technique in evaluating water ingress, 3) influence of water/ice phase transformation on detectability of water ingress. The numerical analysis was conducted by using the ThermoCalc-3D software in order to evaluate the detectability of water ingress in the cases where a test panel is placed in different spatial orientations. The samples with water and ice were tested and analysed by using several data processing algorithms available in the ThermoFit software to enhance water detection performance. The signal-to-noise ratio concept was used to compare efficiency of image processing algorithms in the inspection of water ingress in honeycomb panels with varying water content, spatial orientation and water/ice phase transformation.

A Model Validatory Approach in Determining Solar Panel Tilting Angles and Orientations at the Brikama Environment of The Gambia

Solar energy demand in The Gambia has got a boost in recent times owning to it cleaner nature and affordability compared to other renewables and by this many people are shifting towards solar PV installation. To optimize the design of any PV system for maximum performance, adequate knowledge of the orientation and tilt angles of the solar panel against the sun radiation received by the solar panel is vital. This paper determines the solar optimal tilt angle and orientation of solar panels in the Brikama environment of The Gambia. This was achieved by comparing a mathematical model results with experimental data collected using a PV module (Model AP-120) manufactured by AstroPower, Inc., Deleware, USA, and single axis tracker technology at the same location and months of the year 2022. The experimental tilt angles obtained range from 29.85-30.14 with an average angle of 29.99 while the mathematical model approach obtained the tilt angle to be 30. By comparing all the values recorded during the experiment, the peak value of power generated by the solar panel was recorded at an angle of 30due South and this proves our techniques in determining the tilted angles with our applied model. The monthly tilt angles of the solar panel, which were averaged from the total months of the year and the average tilt angle in the Brikama environment is 15.5and the solar module should face south during installation for optimization. These results are vital in maximizing solar energy collection from photovoltaic systems.

Effect of solar panel orientation and EV charging profile on grid design

The implementation of solar coupled with daytime electric vehicle (EV) charging, aligns seamlessly with the broader goal of transitioning to a decarbonized grid and clean energy future. This paper explores how fixed-tilt solar arrays coupled with daytime EV charging would affect a future renewable-energy-driven grid in California. We use capacity-expansion modeling to identify the lowest-cost grid design for 40 scenarios that compare two solar panel mounting configurations (east–west versus south-facing), two EV charging profiles, five tilt angles ranging from 15°to 35°, and two assumptions about a long-duration energy storage (LDES) candidate resource. We then evaluate and discuss the mix of generators selected by the model for the various scenarios, the associated curtailment, and the implications about the best approaches for adding fixed-tilt solar arrays as part of transitioning to a new energy system. Although the east–west-facing solar orientation is expected to reduce the need for diurnal storage by being able to charge EVs early and late in the day, it appears that the better matching between seasonal supply and demand for the south-facing orientation is more important.

Evaluating Water Ingress in Glass Fiber Plastic/Nomex Honeycomb Panels under Varying Panel Orientation

Evaluating Water Ingress in Glass Fiber Plastic/Nomex Honeycomb Panels under Varying Panel Orientation

IoT Based Solar Tracking System with Automatic Dust Monitoring System

The most plentiful energy source available to all living things on Earth is solar energy. One way to generate power from sunshine is via the Solar Tracking System. This form of electricity generating uses renewable natural resources. It just needs the most sunshine possible to produce energy. This system tracks light levels to their maximum. By tracking the sun's movement and modifying the panel's angle and orientation accordingly, the technology maximises the effectiveness of solar panels. Using a dust sensor and a nozzle to spray water on the panel when there is a greater accumulation of dust, the cleaning system is used to remove the accumulated dust from its panel surface. Furthermore, the dust sensor continuously tracks the amount of dust accumulating on the panels and, if needed, initiates an automated cleaning procedure. Wi-Fi is used to transfer the system's data through Node MCU, allowing for real-time monitoring and analysis. The suggested system improves the efficiency of solar energy collection.

Estimating the efficacy of solar photovoltaic panels in Lebanon using a digital surface model: A geospatial approach

With the escalating need for alternative energy sources due to economic crises and fossil fuel shortages in Lebanon, solar photovoltaic (PV) panels have emerged as an attractive solution. This study examines the capacity and efficacy of rooftop-installed PV solar panels. Using geospatial technologies, including Digital Surface Models drone-based photogrammetry, the study assesses geometric and solar characteristics, seasonal solar radiation, solar duration, and power for 40 PV units installed in the study area. This research presents specific quantitative values for optimal orientations that result in high solar radiation across various seasons and identifies varying slopes influencing the performance of PV solar panels. Employing the Agglomerative Hierarchical Clustering (AHC) technique, PV units are systematically classified into clusters labeled as Moderate, High, Low, and Very Low solar power, offering quantitative metrics regarding the effectiveness of distinct panels. The high-efficiency Cluster exhibits an average solar power of 1868.114 kWh/m² during the summer season, whereas the Very Low Cluster, comprising panels with minimal solar power output, averages 150.578 kWh/m² in the same season. In conclusion, the most effective PV solar panels within the study area are those oriented between 195 and 225 degrees, with shallow inclination angles and larger surface areas contributing to enhanced performance in capturing solar radiation and generating power. These precise quantitative insights contribute to informed decision-making for optimizing the placement of PV panels to enhance energy generation. The study's recommendations are substantiated by specific numerical data, guiding future solar installations to maximize solar energy generation.

The Feasibility Study of a Solar Power Plant at Building B, Universitas Multimedia Nusantara

The use of environmentally friendly energy resources is becoming increasingly important in reducing the carbon footprint of buildings. One approach is to integrate solar power generation into the building's energy system. This research aims to reduce the carbon footprint by replacing conventional electricity sources with environmentally friendly renewable energy sources and integrating energy sources without disrupting the productivity of activities in Building B of Universitas Multimedia Nusantara (UMN). This study encompasses several key parameters, including the limited use of solar panels in Building B of UMN and simulations conducted using PVsyst software with shadow-free assumptions and solar panel orientation facing north. Additionally, the research considers the potential production of clean energy from available utilization areas, including the roof and fifth-floor balcony of Building B. This feasibility study also includes an analysis of electricity usage over three months, with electricity consumption sourced from PLN. The analysis results show that the use of solar panels can yield long-term economic benefits, with capital costs recoverable within 20 years. However, further review is needed regarding potential system losses, costs, and the addition of energy storage options. Cost calculations need to be adjusted to consider building owner profitability for more accurate results. This study only considers profits without accounting for repair and maintenance costs over the 20-year system operation period.

A Model Validatory Approach in Determining Solar Panel Tilting Angles and Orientations at the Brikama Environment of The Gambia

This paper determines the solar panel optimal tilt angle and orientations at the Brikama environment of The Gambia. This was achieved by comparing mathematical model results with experimental data collected using a PV module (Model AP-120) manufactured by AstroPower, USA, and a single-axis tracker technology at the same location and months of the year. The experimental tilt angles obtained range from 5.1°-28.2° with an average angle of 14.8° while the mathematical model approach obtained the tilt angle to be within the range of 9.1°-22.3° with a mean value of 15.5°. The generated power analysis revealed that the peak power produced by the solar panel was recorded at an angle of 30° due South and the mean power gain from the orientation of the PV panel ranged from 3.6-48.1W. The mean power result suggests that, in comparison to a horizontal position, solar collecting efficiency is higher at the optimal tilt angle.

Optimizing solar panel orientation for enhanced power output in cloudy conditions: a case study on solar energy supply in a water treatment plant

This paper presents a study on optimizing the performance of a photovoltaic solar generator used to power a water treatment plant in a remote area. The research aims to evaluate the system's efficiency and focuses on determining the optimal orientation of the solar panel during periods of cloudy weather, which significantly impact sunlight availability and ozone production. To achieve this, two optimization algorithms, namely the Grey Wolf Algorithm (GWO) and the Crayfish Optimization Algorithm (COA), are employed to optimize the power output. The study is conducted in Algeria, where prevalent autumn cloud cover poses challenges for solar panel operation. By addressing these challenges and designing a high-performance photovoltaic-powered water treatment plant, the research contributes to sustainable water treatment technologies and offers promising solutions for underserved communities in need of water pumping and treatment systems. The findings highlight the importance of optimizing solar panel orientation in cloudy conditions and showcase the effectiveness of the GWO and COA algorithms in maximizing power output. By leveraging these optimization techniques, the proposed approach enhances the performance of the solar generator, ensuring efficient power production even during periods of reduced sunlight. This research not only addresses the specific case of a water treatment plant in a remote area but also has broader implications for the renewable energy sector. The study demonstrates the potential of utilizing solar energy in powering critical infrastructure, such as water treatment facilities, in areas where access to reliable electricity is limited. By fostering the adoption of sustainable energy solutions, this research contributes to the goal of achieving long-term environmental and social sustainability.

Energy Production Optimization by Positioning of Solar Panels and Surveillance System with Cleaning of Panels

The pursuit of efficient and sustainable energy generation has led to the widespread adoption of solar panels. However, the optimal performance of these panels can be hindered by factors such as dirt accumulation, suboptimal orientation, and security concerns. To address these challenges, we propose an integrated Solar Panel Tracking, Cleaning, and Surveillance System (SPTCSS). Our system employs advanced tracking technology to optimize solar panel orientation, ensuring maximum exposure to sunlight throughout the day. Additionally, it incorporates automated cleaning mechanisms, utilizing water and brushes to remove dust, debris, and other contaminants, thereby maintaining peak efficiency. Furthermore, the surveillance aspect of the system provides real-time monitoring and security features, safeguarding against theft, vandalism, and unauthorized access. Through a network of sensors and cameras, any anomalies or suspicious activities can be promptly detected and addressed. By integrating tracking, cleaning, and surveillance functionalities into a single system, our solution offers a comprehensive approach to enhancing the performance, longevity, and security of solar panel installations. This not only maximizes energy generation but also minimizes maintenance requirements and mitigates risks, ultimately contributing to a more sustainable and reliable renewable energy infrastructure

Evaluating Text Reading Speed in VR Scenes and 3D Particle Visualizations.

This work reports how text size and other rendering conditions affect reading speeds in a virtual reality environment and a scientific data analysis application. Displaying text legibly yet space-efficiently is a challenging problem in immersive displays. Effective text displays that enable users to read at their maximum speed must consider the variety of virtual reality (VR) display hardware and possible visual exploration tasks. We investigate how text size and display parameters affect reading speed and legibility in three state-of-the-art VR displays: two head-mounted displays and one CAVE. In our perception experiments, we establish limits where reading speed declines as the text size approaches the so-called critical print sizes (CPS) of individual displays, which can inform the design of uniform reading experiences across different VR systems. We observe an inverse correlation between display resolution and CPS. Yet, even in high-fidelity VR systems, the measured CPS was larger than in comparable physical text displays, highlighting the value of increased VR display resolutions in certain visualization scenarios. Our findings indicate that CPS can be an effective metric for evaluating VR display usability. Additionally, we evaluate the effects of text panel placement, orientation, and occlusion-reducing rendering methods on reading speeds in generic volumetric particle visualizations. Our study provides insights into the trade-off between text representation and legibility in cluttered immersive environments with specific suggestions for visualization designers and highlight areas for further research.

Solar Tracking Methods: A Comprehensive Survey

Abstract: In the pursuit of maximizing solar energy utilization, solar tracking systems have emerged as indispensable tools for enhancing the efficiency of photovoltaic (PV) systems. This comprehensive survey delves into the multifaceted landscape of solar tracking methods, elucidating the diverse techniques and strategies employed in optimizing solar panel orientation relative to the sun's position Solar tracking systems are classified into two primary categories: single-axis and dual-axis tracking. Single-axis tracking systems adjust solar panels along one axis, typically the azimuth axis, while dual-axis tracking systems dynamically alter both azimuth and elevation angles to accurately follow the sun's apparent motion across the sky.Within the realm of solar tracking, passive and active tracking methods are explored. Passive tracking mechanisms rely on natural phenomena such as gravity or thermal expansion to adjust panel orientation, whereas active tracking systems employ mechanical, electrical, or hydraulic actuators driven by motors or other means to actively adjust panel angles based on real-time tracking algorithms.A pivotal aspect of solar tracking systems is the selection and implementation of tracking algorithms. Various algorithms, including sun position algorithms, maximum power point tracking (MPPT) algorithms, and predictive algorithms, are analyzed for their effectiveness in accurately predicting and optimizing solar panel orientation.Furthermore, this survey scrutinizes the role of sensor technologies in solar tracking, encompassing GPS-based tracking, light-intensity-based tracking, weather-based tracking utilizing meteorological sensors, and horizon tracking techniques. These sensor-based methodologies offer different advantages and trade-offs in terms of accuracy, cost, and reliability. To provide a comprehensive understanding, comparative analyses are conducted, evaluating the efficiency, cost-effectiveness, and energy yield of different tracking methods. These comparative assessments offer valuable insights into the performance characteristics and suitability of various tracking methodologies across diverse applications and environmental conditions.In conclusion, this survey serves as an invaluable resource for researchers, engineers, and policymakers involved in the design, development, and optimization of solar tracking systems for renewable energy applications. By synthesizing the latest advancements and comparative analyses, this survey facilitates informed decision-making and fosters the advancement of sustainable solar energy technologies.

Solar Powered Street Light with Sensor and Auto Intensity Control

The goal of this work is to predict solar panel power output by utilizing machine learning techniques, such as neural networks and regression, and by examining variables such as panel orientation, temperature, and sun irradiation. Models with high forecast accuracy help with grid integration and solar energy management. The article also outlines an innovative LED street light system that runs on solar power and uses Internet of Things (IoT) technology for intelligent control. By adjusting brightness in response to motion detection and current conditions, the device improves both urban safety and energy economy. For continuous operation, it runs on a backup battery, encouraging intelligent and sustainable street lighting

Raspberry Pico Based Dual Axis Smart Solar Tracking System

One of the most critical global concerns is the energy crisis, which has led to a growing emphasis on renewable energy solutions. Solar panels have become increasingly popular in recent years as they efficiently convert solar energy into electrical energy. Their affordability and minimal environmental impact make them a preferred choice. Solar panels release electromagnetic radiation during electricity production. The primary objective is to develop an effective autonomous solar tracking system that constantly adjusts the solar panel's position to remain perpendicular to the sun's rays. In this system, a photoresistor serves as the sensor, detecting sunlight to facilitate automatic adjustments. Both horizontal and vertical axes on the dual-axis solar panel are rotated to enhance device efficiency. This dual-axis mechanism provides precise control over the panel's elevation relative to the sun, ensuring optimal energy capture. Solar tracking systems are specifically designed to maximize solar panel efficiency by aligning them with the sun's position throughout the day. These systems utilize sensors and motors to continuously adjust the panel's orientation, resulting in increased energy production and a better return on investment compared to fixed solar panels.

Minimizing annual reflection loss in fixed-tilt photovoltaic modules using graded refractive index (GRIN) anti-reflective glass

This study evaluates the performance of graded refractive index (GRIN) anti-reflective (AR) structures on photovoltaic (PV) modules across twenty global locations and compares them with conventional thin film AR coatings and bare glass. Optimized glass nanocones were chosen to represent the GRIN structures. Electrodynamic simulations were conducted to assess reflection properties at multiple angles of incidence. GRIN AR structures dramatically reduce total solar-integrated reflection to 0.2% at normal incidence, compared to 3.8% for bare glass and 0.8% for optimized thin film AR coatings, and maintained low reflection across a range of incident angles, demonstrating only 0.7% reflection at 60 degrees compared to significantly higher values for other surfaces. Detailed hourly simulations for twenty global locations revealed that GRIN AR coatings substantially reduce annual reflection loss to just 0.86±0.19% and increase expected annual energy output by up to 11.15±1.00% compared to bare glass at optimal tilt angles. The benefits of GRIN AR coatings are more substantial at sub-optimal panel orientations such as horizontal or vertical due to its broad angle AR properties. These findings highlight the potential of GRIN AR technology to approach the theoretical limit where front surface reflection loss is completely eliminated and enhance solar power conversion efficiencies. Additionally, a generalized model to approximate annual reflection loss for various materials is presented. This research encourages further exploration into GRIN AR coatings to optimize power conversion efficiencies and reduce reflection in PV modules.

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