Panel Placement Research Articles

Urban Microclimate Impact on Vertical Building-Integrated Photovoltaic Panels

The ongoing climate crisis and turbulence on the world stage has highlighted the need for sustainability and resilience in the development and maintenance of urban areas regarding climate comfort and energy access. Local production of green energy increases both the sustainability and resilience of an area. Traditionally, photovoltaic (PV) panels are deployed wherever the amount of sunlight is highest but lowering costs for PV panels makes them cost-effective even in colder climates. Within the broader umbrella of positive energy districts, façade mounted building-integrated PV panels in urban areas additionally present unique opportunities and challenges, as factors such as wind, solar irradiance, or nearby obstructions can have either a positive or negative effect on the performance of the PV panels. In this article, we aimed to answer the question: What factors inform the optimization of vertical PV panels? To answer this, we developed a method for the optimization of placement of PV panels. By building upon readily available weather data, local panel conditions were examined, and field-driven aggregation algorithm used to guide panel placement. Performance of the resulting panel configurations were then compared to a baseline case. Results indicate that our developed method helped mitigate negative impacts of the aforementioned factors, and often improved performance over baseline.

Comparative Analysis of Tilt And Illumination of Solar Panels in the Design of Solar Test Simulator

In order for the designed tool to simulate solar panel measurements based on real-world conditions, the solar panel placement holder was arranged in a specific way during the design process. A monitor display that is mounted on the design will show the effectiveness of the solar panels and provide general solar panel information. Limitations in the positioning of solar panels will not provide a reference to conditions for measurement depending on the angle of incidence of the sun so further design needs to be done regarding the position of solar panels when measurements are taken. The development carried out in the design of this tool is in the form of adjusting the solar panel holder in the form of a solar panel holder tilt of 0°, 90°, 180°, and a distance of 30 cm halogen lamp as an energy source that is measured. Measurement results based on design, temperature 46°C, and 100% light.

Maximizing solar energy generation: guidelines for optimizing photovoltaic panel placement on building facades

PurposeThis purpose of this paper is to address the research problem of optimizing photovoltaic (PV) panel placement on building facades to maximize solar energy generation.Design/methodology/approachThe study examines the significance of various design configurations and their implications for PV system performance. The research involves analysis of relevant literature and energy simulations. An exemplary case study is conducted in a hot climate zone to quantify the impacts of PV panel placement on energy generation. Various application scenarios are developed, resulting in 28 scenarios for PV on building facades. Energy simulations using Grasshopper Rhino software and Ladybug plugin components are performed.FindingsThe paper identifies key factors influencing PV panel placement and energy generation through qualitative analysis. It introduces an appropriateness matrix as a decision-making framework to evaluate placement options. The study identifies design configurations and external features impacting PV location selection and performs a qualitative classification to determine their impact on energy generation.Practical implicationsThe results and decision-making framework enable informed choices based on solar radiation levels, shading conditions, and building requirements. Optimizing PV panel placement enhances solar energy harvesting in buildings, benefiting architects and engineers.Originality/valueThe novel contributions of this paper include practical insights and guidance for strategically placing PV panels on building facades.

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.

A renewable approach to electric vehicle charging through solar energy storage.

Developing novel EV chargers is crucial for accelerating Electric Vehicle (EV) adoption, mitigating range anxiety, and fostering technological advancements that enhance charging efficiency and grid integration. These advancements address current challenges and contribute to a more sustainable and convenient future of electric mobility. This paper explores the performance dynamics of a solar-integrated charging system. It outlines a simulation study on harnessing solar energy as the primary Direct Current (DC) EV charging source. The approach incorporates an Energy Storage System (ESS) to address solar intermittencies and mitigate photovoltaic (PV) mismatch losses. Executed through MATLAB, the system integrates key components, including solar PV panels, the ESS, a DC charger, and an EV battery. The study finds that a change in solar irradiance from 400 W/m2 to 1000 W/m2 resulted in a substantial 47% increase in the output power of the solar PV system. Simultaneously, the ESS shows a 38% boost in output power under similar conditions, with the assessments conducted at a room temperature of 25°C. The results emphasize that optimal solar panel placement with higher irradiance levels is essential to leverage integrated solar energy EV chargers. The research also illuminates the positive correlation between elevated irradiance levels and the EV battery's State of Charge (SOC). This correlation underscores the efficiency gains achievable through enhanced solar power absorption, facilitating more effective and expedited EV charging.

Comparative Analysis of Solar Panel Tilt and Lighting in Design Solar Test Simulator

Designing the Solar Panel Test Simulator by means of setting up the solar panel placement holder so that the designed tool is able to provide a simulation of solar panel measurements based on actual conditions. The performance of the solar panels is shown through a monitor display placed on the design which will contain information about the solar panels as a whole. Limitations in placing the position of the solar panels will not provide a reference regarding the measurement conditions based on the angle of incidence of the sun, so further planning needs to be done regarding the position of the solar panels when the measurements are taken. The development carried out in the design of this tool is in the form of setting the solar panel mount in the form of a tilt of the solar panel mount of 00, 900, 1800, and a halogen lamp distance of 30 cm as the energy source for measurements. Measurement results based on design, temperature 46 0C and light 100% Keywords: Solar Panels, Solar Test Simulator, sun angle, inclination, design

How can solar panels collectors enhance energy efficiency? Utilization of the novel optimization techniques

Abstract Solar energy, which is widely acknowledged for its economic feasibility and sustainable nature, functions as a critical substitute for finite fossil fuels, effectively alleviating ecological consequences. The purpose of this study is to investigate the implementation of solar collectors as a means of harnessing the ample and unaltered solar radiation in Iran, specifically in locations situated within the solar belt. The incorporation of solar energy not only aids in the expansion of energy sources through diversification but also mitigates the rising expenses linked to fossil fuels. The preservation of natural resources, coupled with limited renewable energy options, further accentuates the importance of solar energy. The optimization of solar panel collector angles in photovoltaic systems assumes paramount importance for maximizing energy efficiency. This study, conducted in Yazd, Iran, utilized innovative mathematical and particle swarm optimization (PSO) models to assess ideal inclination angles. Results indicate peak solar energy absorption during June and July, contrasting with minimal absorption in January. The Klein model prescribes inclination angles based on γ values, while the PSO algorithm determines optimal slope and azimuth angles across various periods. Significant enhancements in energy generation, ranging from 23.24 to 25.02% across optimization models, were observed compared to a horizontal surface. These findings underscore the imperative of optimizing solar panel placement in urban settings to augment energy generation. Utilizing the optimal orientation for the photovoltaic power supply system can result in an annual reduction of 1169.6 kg of CO2 emissions in the building, emphasizing the positive environmental impact achievable through strategic solar panel configurations.

Contribution of ChatGPT and Other Generative Artificial Intelligence (AI) in Renewable and Sustainable Energy

In the dynamic field of renewable and sustainable energy, Artificial Intelligence (AI) integration has emerged as a crucial catalyst for enhancing efficiency, cost reduction, and addressing multifaceted challenges. This work delves into the performance and contributions of ChatGPT, a prominent representative of large AI language models, within the context of renewable and sustainable energy. The research endeavors to explore ChatGPT's efficacy and role across a diverse spectrum of renewable energy aspects, spanning solar energy, wind energy, biomass energy, hydropower, geothermal energy, energy storage, grid integration, energy efficiency, materials science, policy, economics, environmental impact, energy accessibility, and advanced biofuels. The investigation commences with solar energy, where ChatGPT showcases impressive capabilities in data analysis, modeling, and forecasting. It facilitates solar panel placement optimization, energy production prediction, and overall efficiency enhancement. Likewise, in the realm of wind energy, ChatGPT proves invaluable for tasks such as wind turbine control, maintenance scheduling, and wind speed prediction. In biomass energy, ChatGPT aids in feedstock selection, process optimization, and emissions reduction. In the hydropower sector, it supports reservoir management and river flow prediction, thereby optimizing energy output. Geothermal energy benefits from ChatGPT's geological analysis, reservoir modeling, and exploration strategies. Energy storage solutions are indispensable for grid stability, and ChatGPT contributes to the advancement of cutting-edge battery technologies, augmenting energy storage capacity and lifespan. Furthermore, ChatGPT's insights foster the evolution of smart grids, ensuring efficient energy distribution and effective demand management. Additionally, ChatGPT provides invaluable insights into policy and economics, offering recommendations for incentivizing the adoption of renewable energy sources while considering environmental impact and sustainability. It also contributes to the advancement of tidal and wave energy technologies, as well as the development of advanced biofuels. The outcomes of this research paper underscore the potential of AI and ChatGPT in shaping the future of renewable energy, expediting progress toward a sustainable energy ecosystem.

Optimizing Solar Panel Placement through Passive Architectural Design

Optimizing Solar Panel Placement through Passive Architectural Design

Rooftop segmentation and optimization of photovoltaic panel layouts in digital surface models

Rooftop photovoltaic panels (RPVs) are being increasingly used in urban areas as a promising means of achieving energy sustainability. Determining proper layouts of RPVs that make the best use of rooftop areas is of importance as they have a considerable impact on the RPVs performance in efficiently producing energy. In this study, a new spatial methodology for automatically determining the proper layouts of RPVs is proposed. It aims to both extract planar rooftop segments and identify feasible layouts with the highest number of RPVs in highly irradiated areas. It leverages digital surface models (DSMs) to consider roof shapes and occlusions in placing RPVs. The innovations of the work are twofold: (a) a new method for plane segmentation, and (b) a new method for optimally placing RPVs based on metaheuristic optimization, which best utilizes the limited rooftop areas. The proposed methodology is evaluated on two test sites that differ in urban morphology, building size, and spatial resolution. The results show that the plane segmentation method can accurately extract planar segments, achieving 88.7% and 99.5% precision in the test sites. In addition, the results indicate that complex rooftops are adequately handled for placing RPVs, and overestimation of solar energy potential is avoided if detailed analysis based on panel placement is employed.

Assessing the Photovoltaic Power Generation Potential of Highway Slopes

The solar photovoltaic (PV) power generation system (PGS) is a viable alternative to fossil fuels for the provision of power for infrastructure and vehicles, reducing greenhouse gas emissions and enhancing the sustainability of road transport systems. A highway slope is generally an idle public area with high accessibility, which is the ideal application scenario for a PV PGS. The assessment of PV power generation potential (PGP) is key for the planning and design of PV PGS projects. Previous approaches to potential assessments are mainly based on digital maps and image processing techniques, which do not fully consider the impacts of the highway orientation, the slope geometric characteristics, and the PV panel placement scheme on the evaluation results. Therefore, this study proposes an assessment method for the PV PGP on highway slopes using the design or calculated highway and slope geometric parameters and the solar radiation received by PV panels under the desirable placement scheme. Highway segmentation and geometric parameter calculation methods were established, and the optimal PV array placement schemes for typical slope orientations were determined by simulating the PV power generation in the software PVsyst (version 7.2). Afterwards, the theoretical PGP could be calculated using the received solar radiation and the available slope area. By subtracting the energy loss caused by temperature changes, the operation of inverters, and the PV modules’ performance decay, the actual PV PGP could be obtained. Finally, a case study of the solar PGP assessment of a 1.97 km long highway section is provided, and the feasibility of the proposed method is verified.

Analysis of System Degrees of Tilts of Solar Panel for Energy Utilization Using Solar Test Simulator

The design of the Solar Panel Test Simulator by means of setting the solar panel placement stand so that the designed tool is able to provide a simulation of solar panel measurements based on actual conditions. The performance of the solar panels is shown through a monitor display placed on the design that will contain information about the solar panels as a whole. Limitations in placing the position of the solar panel will not provide a reference regarding measurement conditions based on the angle of incidence of the sun, so it is necessary to do further design regarding the position of the solar panel when the measurement is carried out. The development carried out in the design of this tool is in the form of setting the solar panel mount in the form of a solar panel mount tilt of 450, 900, 1350, and the distance of the halogen lamp 30cm as the energy source is measured. The measurement results are based on an average design temperature difference of 0.49% with a voltage of 1.55%.

Escape panels in trawls: does placement matter when every individual contacting the panel can escape?

Escape panels are one of the bycatch reduction devices most used in trawl fisheries but their efficiency rely on fish actively contacting the panel to escape. To investigate if contact behaviour changes at different panel placements, we tested a 300 mm square mesh panel placed in the upper panel of the codend at 3, 4 and 7 m from the codline. Seven competing models of contact probability were fitted to the empirical data. Based on the results, we inferred that panel placement significantly affects escape efficiency due to a change in type of contact behaviour. Cod ( Gadus morhua) showed a contact increasing with length when the panel was closest to the codline, while contact probability decreased with length at the other placements. Similarly, contact probability for plaice ( Pleuronectes platessa) was found to increase with length at 3 and 4 m, whereas a length-independent contact best represented the data at 7 m. Finally, Nephrops ( Nephrops norvegicus) had in general low contact probability. The results provide new knowledge regarding species and placement-dependent panel escape.

DEEP LEARNING FOR SEMANTIC 3D CITY MODEL EXTENSION: MODELING ROOF SUPERSTRUCTURES USING AERIAL IMAGES FOR SOLAR POTENTIAL ANALYSIS

Abstract. On a global scale, semantic 3D city models with Level of Detail 2 become more and more available. Automated generation of higher Level of Detail models is an active field of research, but low coverage of dense LiDAR or photogrammetric point clouds is a barrier. Therefore, this paper presents a novel approach for enriching semantic 3D city models with roof superstructures extracted from aerial images using deep learning. The method maps and classifies superstructures in 2D and subsequently transforms them to 3D. Furthermore, we examine the benefit of the enriched model for solar potential analysis. The accuracy of solar potential analysis is improved by avoiding invalid simplifications of slope, shadow and panel placement. The enriched model reduces overestimation of accumulated solar potential by around 20% compared to an analysis based on aerial images only. The novel method contributes to increasing the availability of Level of Detail 3 models for larger areas, while posing further research opportunities.

Case Study: RTU on the Way to Participate in Race to Zero Challenge

Race to Zero challenge is a world-wide activity for the universities and colleges to foster the climate goals. This paper analyses the potential of Riga Technical University (RTU) for this action. Different renewable energy sources (PV, wind generators) have been discussed to be installed around the RTU campus. The profiles of electric power consumption are analysed for one faculty and sport centre. The consumption profiles show the amount of power demanded during the working hours, weekends and at night. Energy yield assessment on the roofs is made for two buildings where the configuration of PV panel placement and orientation are analysed that in turn is reflected in the energy generation profile. SCADA system is considered as a monitoring and control tool to visualize power generation and control of the power flow within the system elements.

Exploration of the photo voltaic (PV) energy generation and scope for Sonipat: A Review

This review article explores photovoltaic (PV) energy generation and its potential scope in Sonipat. It delves into the current state of PV technology and its applications in the region. Sonipat's geographic location and solar potential are examined to assess its suitability for PV energy generation. The study also investigates factors such as solar panel placement, energy storage, and maintenance practices. By reviewing existing literature and research, it aims to provide insights into the feasibility and opportunities for expanding PV energy generation in Sonipat, ultimately contributing to sustainable energy solutions in the region. The review offers a comprehensive analysis of PV energy generation in Sonipat, encompassing its environmental and economic benefits. It examines Sonipat's solar irradiance patterns and the potential for harnessing solar energy for electricity generation. Furthermore, it explores the challenges and opportunities in integrating PV systems into the local energy infrastructure, considering factors like grid integration and policy support. The review ultimately aims to shed light on the untapped potential of PV energy in Sonipat, highlighting the importance of sustainable energy sources in the region's energy landscape and emphasizing the need for further research and development in this field.

Impacts of a floating photovoltaic system on temperature and water quality in a shallow tropical reservoir

A three-dimensional hydrodynamic-ecological lake model combined with field measurements and sampling was applied to investigate the impacts of floating photovoltaic (PV) systems on hydrodynamics and water quality in a shallow tropical reservoir in Singapore. The model was validated using field data and subsequently applied to predict temperature and water quality changes for a hypothetical 42 ha placement of floating photovoltaic panels, covering about 30% of the water surface and capable of generating up to 50 MW of energy. The impact of the panel placement was studied numerically. The area of the reservoir where panels are placed experiences both light limiting and reduced wind stress conditions. The model indicated an average water temperature increase of 0.3 °C beneath the panels, consistent with the field observation from a 1 ha demonstration installation. Comparisons of model results between the uncovered and covered areas reveal greater stability of the water column (increase in Richardson number from 2.3 to 3.3) and reduction in mixing energy (from 9 × 10–7 to 7 × 10–7 W/kg) under the PV panels. Furthermore, the model predicted that chlorophyll a, total organic carbon and dissolved oxygen concentrations would decline by up to 30%, 15% and 50%, respectively, under the photovoltaic panels. Total nitrogen and total phosphorus, averaged over the water column, increased by 10% and 30%, respectively, under the panels. Distant from the floating solar panels, temperature, stability and water quality were unaffected.

Techno-economic Analysis of Rooftop Photovoltaic System (RPVS) using Thin-Frameless Solar Panels for Household Customers in Indonesia

The availability of thin-frameless solar panels on the market today makes the installation of rooftop Photovoltaic (RPVS) systems more attractive. The purpose of this research is to analyze financially the use of thinframeless solar panels for on-grid RPVS by household electricity customers in Indonesia. The investment cost, the maintenance costs, and the electricity cost savings were involved for the financial analysis, such as Internal Rate of Return (IRR), Net Present Value (NPV), and Pay Back Period (PBP). The calculation is carried out for ideal conditions, the direction of a non-ideal rooftop and the yearly increase of electricity prices is 15 %. The analysis results show that the minimum available rooftop area is still sufficient for the rooftop area needs for solar panel placement, the thin solar panels are safer than standard solar panels, and savings on electricity payments for the return on investment of the RPVS is to be attractive with the IRR > 12 %. The average investment cost of the non-ideal condition is 8 % higher than the ideal condition. This study provides an overview to the policymakers and developers in exploiting the potential of RPVS, especially in Indonesia. For future research directions, this study needs to analyze the technical and economic feasibility of using hybrid smart-grid technology with batteries.

Quantification of existing rooftop PV hourly generation capacity and validation against measurement data

The spatio-temporal patterns of the existing rooftop photovoltaic (PV) production can provide valuable insights for the design of effective strategies for PV integration at large scale. In this work, we quantify the hourly production of existing rooftop PV installations by combining two large-scale methods, for detecting rooftop solar panels and for estimating their hourly PV generation, which are both applicable at the Swiss national scale. A validation against measured data of PV installations from 16 roofs in the Swiss Canton of Aargau shows that the existing PV area is detected accurately, while the hourly profiles overestimate the PV production, with higher errors in winter than in summer. These errors result in a mean overestimation of the annual PV production by 16%, assuming a triangular panel placement at low tilt (15°) on flat roofs.

Sensor-Guided Assembly of Segmented Structures with Industrial Robots

This paper presents a robotic assembly methodology for the manufacturing of large segmented composite structures. The approach addresses three key steps in the assembly process: panel localization and pick-up, panel transport, and panel placement. Multiple stationary and robot-mounted cameras provide information for localization and alignment. A robot wrist-mounted force/torque sensor enables gentle but secure panel pick-up and placement. Human-assisted path planning ensures reliable collision-free motion of the robot with a large load in a tight space. A finite state machine governs the process flow and user interface. It allows process interruption and return to the previous known state in case of error condition or when secondary operations are needed. For performance verification, a high resolution motion capture system provides the ground truth reference. An experimental testbed integrating an industrial robot, vision and force sensors, and representative laminated composite panels demonstrates the feasibility of the proposed assembly process. Experimental results show sub-millimeter placement accuracy with shorter cycle times, lower contact force, and reduced panel oscillation than manual operations. This work demonstrates the versatility of sensor guided robotic assembly operation in a complex end-to-end tasks using the open source Robot Operating System (ROS) software framework.