Roof Area Research Articles

Hybrid TDPEEC/FDTD Method for Lightning Transient Analysis in Solar Panels

AbstractSolar energy is one of the clean renewable energy, which plays an important role in energy strategy. As the solar panels of photovoltaic system are installed on the outdoor roof or open area, lightning is an important threat to the safe and stable operation of photovoltaic power generation system. Because of mutual coupling among the fine‐structure solar panel, the ground and the buried wire grid, special techniques are required to develop for simulating transients in the panels. In this paper, a hybrid time domain partial element equivalent circuit/finite difference time domain (TD‐PEEC/FDTD) method was proposed to solve the electromagnetic coupling problem of the coexistence of electrically large targets and electrically small target. The FDTD method was suitable for modeling fields in inhomogeneous media, while the TD‐PEEC method was efficient in modeling elaborate wires. By using the principle of equivalence, the algorithm and the target were parallelized in different regions, which can improve the efficiency of calculation to the greatest extent on the premise of ensuring the correctness and accuracy. Compared with the traditional FDTD method, the feasibility of the hybrid method was verified. Finally, the method was applied to the lightning transient analysis of the inclined photovoltaic panel in the process of indirect lightning stroke. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Cryoballoon left atrial roof ablation for persistent atrial fibrillation-Analysis with high-resolution mapping system.

Additional benefit of cryoballoon left atrial roof line ablation (CB-RA) beyond cryoballoon pulmonary vein isolation (CB-PVI) is suggested in patients with persistent atrial fibrillation (PsAF). We sought to investigate the feasibility of CB-RA for PsAF and to determine the ablation area. Fifty-three PsAF patients (67[58.5-75.5] years, 36 men, 11 longstanding PsAF) underwent CB-PVI. Subsequently, 44(83.0%) out of 53 patients underwent additional CB-RA. Voltage maps were created in all patients with a high-resolution mapping system. The total number and duration of CB-RAs were 3.9 ± 0.7 and 468 ± 84 s. LA roof areas were complete low voltage areas (LVAs) /scar in 37/44(84.1%) patients ("complete roof modification"). The normal LA posterior wall (LAPW) voltage area was 6.1(4.1-8.4) cm2 , and the %LAPW isolation area was 61.0(47.2-71.7)%. The %LAPW isolation area was significantly greater in CB-RA patients than those without (64.0[54.2-73.2] vs. 45.0[39.5-50.5]%, p=.041) despite significantly larger LAs in the former group. The %LAPW isolation area was significantly greater in patients with transverse LA diameters<45mm than those≥45mm (p<.0001). The single procedure 1-year AF freedom was 87.4% (22.5% on antiarrhythmic drug) and tended to be higher in CB-RA patients than those without. Among the 44 CB-RA patients, it was significantly higher in patients with a complete roof modification than those without (94.4%vs. 75.0%, p=.0049). One CB-RA patient experienced a delayed cardiac tamponade requiring drainage at 4-months post-procedure. CB-RA significantly expanded the LAPW isolation area, and a complete roof modification resulted in a high arrhythmia freedom in PsAF patients.

Integration and Verification of PLUG-N-HARVEST ICT Platform for Intelligent Management of Buildings

THe energy-efficient operation of microgrids—a localized grouping of consuming loads (domestic appliances, EVs, etc.) with distributed energy sources such as solar photovoltaic panels—suggests the deployment of Energy Management Systems (EMSs) that enable the actuation of controllable microgrid loads coupled with Artificial Intelligence (AI) tools. Such tools are capable of optimizing the aggregated performance of the microgrid in an automated manner, based on an extensive network of Advanced Metering Infrastructure (AMI). Modular adaptable/dynamic building envelope (ADBE) solutions have been proven an effective solution—exploiting free façade areas instead of roof areas—for extending the thermal inertia and energy harvesting capacity in existing buildings of different nature (residential, commercial, industrial, etc.). This study presents the PLUG-N-HARVEST holistic workflow towards the delivery of an automatically controllable microgrid integrating active ADBE technologies (e.g., PVs, HVACs). The digital platform comprises cloud AI services and functionalities for energy-efficient management, data healing/cleansing, flexibility forecasting, and the security-by-design IoT to efficiently optimize the overall performance in near-zero energy buildings and microgrids. The current study presents the effective design and necessary digital integration steps towards the PLUG-N-HARVEST ICT platform alongside real-life verification test results, validating the performance of the platform.

Characteristic Analysis of Solar Panels on Clay and Ceramic Roof Tiles

In general, the Rooftop PV Panel installation only considers the power capacity to be installed and the available roof area. It does not consider the type of roof material where it is installed. Meanwhile, the roof of the house has the absorption of sunlight and different thermal properties depending on the type of roofing material. In this study, the objective of this research is to observe the temperature characteristics between solar panels and roofs from 2 types of materials, namely clay tile and ceramic tile, the influence of the height between the solar panel and the ceiling on the temperature and its effect on the efficiency of the solar panel. Based on the results of this study, the temperature characteristics between the solar panel of various types of material have an influence on the efficiency value of the solar panel, where the maximum efficiency value obtained for clay tile material is 4.22% and ceramic tile is 5.69%.

Design of Hybrid Solar Power Plant for household Electricity Loads 1300 VA

Indonesia is a country that is rich in sunshine. Based on NASA's Power Data Access Viewer data in 2021, Indonesia has an average radiation level of 5.6 kWh/m2/day. This situation is a big advantage for Indonesia in utilizing solar energy into electrical energy through photovoltaic, especially in the Semarang City area which has an average radiation level of 5.6 kWh/m2/day. The house where the research is located is in Pudakpayung, Semarang City with a roof area of ​​24m2. The Hybrid Solar Power Plant that is designed is an electric power supply system whose sources come from the Solar Power Plant and the State Electricity Company alternately which are regulated automatically by automatic control equipment with battery capacity mode. The results of the calculation, the required components consist of 9 solar modules with a capacity of 120 WP, 4 batteries with a capacity of 12v100Ah, 1 unit of 3000 Watt inverter and 1 unit of Solar Charger Controller 60A. The results of the tests that have been done, the solar panels produce an average power of 5446 wh per day, the battery will be full at 13.00.

Experimental and Numerical Study on the Insulation Performance of a Photo-Thermal Roof in Hot Summer and Cold Winter Areas

The use of a solar architecture system is a feasible way to reduce the energy consumption of a building. The system also has important significance to the “Dual-carbon” plan. In this study, the heat transfer characteristics of a photo-thermal roof were analyzed in hot summer and cold winter zones; a model to calculate insulation performance was established. In the summer climate, the thermal performances of the photo-thermal roof and an ordinary roof were explored through experiments and simulations. The results showed that the heat transfer and temperature of the photo-thermal roof were lower than those of the ordinary roof. Heat transfer through a photo-thermal roof can be changed by adjusting the water flow of collectors. The water saturation of insulation materials is an important factor that affects the insulation performance of a roof. Compared with the ordinary roof, the change in water saturation was shown to have less impact on the insulation performance of the photo-thermal roof. The water saturation increased from 0 to 30%, while the heat transfer per unit area of the photo-thermal roof only increased by 0.9 W/m2; 97.3% lower than that of the ordinary roof. The effect of reducing the insulation material thickness was less for the photo-thermal roof than for the ordinary roof. When the insulation material thickness was reduced from 100 mm to 0 mm, the average temperature in the indoor non-working area reached 38.5 °C and 27.1 °C in the ordinary roof and the photo-thermal roof, respectively. The insulation thickness of the photo-thermal roof had little effect on the indoor air temperature. The research results provide a reference for the roof energy-saving design of new buildings and the roof energy-saving transformation of existing buildings.

Machine learning-based wind pressure prediction of low-rise non-isolated buildings

This paper proposes a novel machine learning-based wind pressure prediction model (ML-WPP) for low-rise non-isolated buildings. ML-WPP combines a gradient boosting decision tree (GBDT) and the Grid search algorithm (GSA) to automatically predict the wind pressure parameters. In comparison with existing ML models, this model is more straightforward and interpretable. The Tokyo Polytechnic University (TPU) non-isolated low-rise wind tunnel dataset is used to develop and test the ML-WPP model. ML-WPP considers the mean pressure coefficient, fluctuating pressure coefficient, and peak pressure coefficient to reflect the wind pressure among the roof area. The ML-WPP model obtained a low mean-squared error and a high coefficient of determination for all wind tunnel test configurations of the non-isolated low-rise buildings. A time history interpolation is proposed in this paper as well. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with wind pressure prediction while considering the effect of the neighboring buildings. With the advantages of ML-WPP, it is possible to reduce the reliance on physical wind tunnel tests. ML-WPP yields a robust, efficient, accurate alternative to predicting the pressure of structures under wind loads while considering the effects of neighboring structures.

Feasibility Study and Passive Design of Nearly Zero Energy Building on Rural Houses in Xi’an, China

Since the advent of reforms and opening-up of China, the focus has been on urban development. However, rural development has garnered attention in recent years. This research explores energy performance improvement methods for rural houses in Xi’an, China. It aims to discuss the feasibility of designing a nearly zero-energy building (nZEB), based on typical residential rural housing in Xi’an, through proposing new construction methods and examining the strategies for the refurbishment of an existing house. Initially, a typical rural house was modelled based on data collected from a field survey and historical documents. Subsequently, suitable passive design strategies were explored in the rural house design both in terms of proposing new construction methods and examining the refurbishment strategies of an existing house. After implementation of the passive design, the annual energy demand was reduced from 112 kWh/m2 to 68 kWh/m2 (new construction) and from 112 kWh/m2 to 85 kWh/m2 (refurbished). Even though the passive design significantly reduced the energy demand of the house, it could not achieve the Chinese nZEB standard. Therefore, a photovoltaic (PV) system and a storage battery were incorporated to meet the standard. Eighty per cent of the south roof area of the newly constructed and refurbished house was installed with a PV system and a storage battery with a capacity of 50 kWh and 52 kWh, respectively. After installation of the proposed renewable energy, the annual energy demand from the house was decreased to 35 kWh/m2 (new construction) and 51 kWh/m2 (refurbished), which both achieved the Chinese nZEB standard (equal to or below 55 kWh/m2). The study shows the effectiveness of the methods used to design the nZEB and can be used to instruct the residents to build the nZEB in rural villages like Xi’an in China.

Heating Load of Residential Buildings Using Multiple Linear Regression Artificial Neural Network

Global warming is one metric of climate change which is defined as an increase in the average global temperature. Residential buildings contribute significantly to the pollution that causes climate change. It is essential to have a comprehensive understanding of the functions of highly energy efficient buildings in view of projected climate projections, the quality of their heating systems, and the impact on human health and well-being. Thus, in this study, the effects of six input variables which are Overall Height, Glazing Area, Wall Area, Relative Compactness, Roof Area, and Glazing Area Distribution on one output variable, namely Heating Load (HL) of residential buildings was investigated using Multiple Linear Regression and Artificial Neural Network (MLR-ANN) approaches. Two-layer hyperbolic tangent-identity transfer functions with 6-3-1 configurations were employed as it was found as the best neural network model. A dataset of 768 residential buildings was used for secondary data. The Mean Square Error (MSE), determination coefficients R2, as well as the percentage of normalized importance analysis were used to assess the statistical prediction capabilities of the MLR-ANN model. Based on the current findings, Wall Area is the most contributing factor towards HL, followed by Relative Compactness, Roof Area, Overall Height, Glazing Area, and Glazing Area Distribution. It can be suggested that HVAC (heating, ventilation, and air conditioning) systems should be implemented in residential buildings to reduce energy use. Natural ventilation is encouraged in buildings through vernacular design, and radiant heating and cooling systems as it is very effective and efficient way of providing thermal comfort within a structure.

Study on the Synchronous Instability Mechanism of the Coal Wall and Direct Roof of High Soft Coal Seam

The advanced mining stress on a large working face can easily lead to the failure of the roof and coal mass; coal wall spalling and roof caving occur. The degree of coal wall failure and the depth of the plastic fracture zone are closely related to the advanced mining stress. The mechanical analysis model is established, and the stress distribution in the fracture and plastic zone is analyzed by the elastic-plastic theory, and the depth function expressions of two zones are determined. Comparative analysis of the factors affecting mining strength shows that the mining depth, mining height, and strength of coal are the key factors affecting the stability of the coal wall. The A1 coal of Zhangji mine in Huainan is soft and thick, and the direct roof is easily separated by the organic membrane, which is easy to form arc-shaped sliding instability. The increase in the unsupported roof area causes the direct roof caving and reduces its bearing capacity and stiffness. It is unable to provide enough support for the broken block of the overlying key stratum, which makes the broken block reverse rotation and further aggravate the roof fall; the synchronous instability of the coal wall and direct roof is formed.

RANCANG BANGUN ENERGI TERBARUKAN BAGI INDUSTRI PERTAHANAN GUNA MENDUKUNG PELAKSANAAN PERANG BERLARUT

The defense industry is important in national defense, therefore energy security is needed. The purpose of this study is to analyze the threat of energy security in the event of a protracted war and the potential for solar energy. The method used in this research is to use PSVsyst in the design of PLTS. The results of energy security at PT Pindad only come from PLN 5,540 kVA and 3,465 kVA, Then for emergencies, PT Pindad has 2 Genset Units with a maximum capacity of 1.8 MW. With this situation, there is a threat of energy security in the event of a protracted war, namely the decision to supply electricity from PLN. Therefore, energy security is needed with the construction of PLTS in the PT Pindad area. From the data, PT Pindad's one hour electricity demand is 6,591 kWh/m2 and the building area that can be used for solar cell roof area is 33,775 m2 at PT Pindad.

CO2 Capture by Virgin Ivy Plants Growing Up on the External Covers of Houses as a Rapid Complementary Route to Achieve Global GHG Reduction Targets

Global CO2 concentration level in the air is unprecedently high and should be rapidly and significantly reduced to avoid a global climate catastrophe. The work indicates the possibility of quickly lowering the impact of changes that have already happened and those we know will happen, especially in terms of the CO2 emitted and stored in the atmosphere, by implanting a virgin ivy plant on the available area of walls and roofs of the houses. The proposed concept of reducing CO2 from the atmosphere is one of the technologies with significant potential for implementation entirely and successfully. For the first time, we showed that the proposed concept allows over 3.5 billion tons of CO2 to be captured annually directly from the atmosphere, which makes even up 6.9% of global greenhouse gas emissions. The value constitutes enough high CO2 reduction to consider the concept as one of the applicable technologies allowing to decelerate global warming. Additional advantages of the presented concept are its global nature, it allows for the reduction of CO2 from all emission sources, regardless of its type and location on earth, and the fact that it will simultaneously lower the air temperature, contribute to oxygen production, and reduce dust in the environment.

The optimization of Low Impact Development placement considering life cycle cost using Genetic Algorithm

Low Impact Development (LID) is an effective measure in controlling the urban runoff and mitigating the non-point source pollution. The determination of LID facilities and layouts for a sub-catchment is important for designing stormwater management system. However, there are remain large uncertainty and challenge exist in determination of LID facilities when consider budget, land use, soil surface and groundwater as well as local climate etc. To address this issue, this study employed Genetic Algorithm (GA) for optimization of the selection and layout of LID. The urban runoff was simulated using Environmental Protection Agency (EPA) Storm Water Management Model (SWMM). The LID planning was encoded as 0 and 1 in GA algorithm. The multiple objectives which include runoff reduction, area of LID and life cycle cost were selected as optimization targets. To test the model performance, the Airport Economic Zone in Tianjin, China was chosen as the study area. The results demonstrate that the combination of LID approaches are most effective measures on runoff reduction through long-term simulation (10 years' rainfall events). The impact of different weights of land area and cost on LID selection were evaluated when considering life cycle cost. Bio-Retention is preferred when considering the area of LID and Green Roof is recommended when the cost is prioritized. The present research proved GA is feasible for LID planning in urban area. The proposed method can help the decision-makers to determine the LID plan more scientific based on SWMM model and GA.

A field study on effects of openings on thermal performance of natural cooling efficiency for atrium buildings

Introduction. In this paper, we investigate the temperature stratification of buoyancy-driven natural ventilation of the atrium of building at ULK-MGSU through field experiments. The process of ventilation with different openings ratios in the translucent roofing and ground floor entrance doors are analyzed to reveal the physical insights. With this aim, the main focus of the study is to consider the temperature fields during cooling the atrium premises that increase the thermal performance of the administrative building at ULK in the summer. An expensive ventilation solution by the optimum design of the inlet-to-outlet opening area ratio in the translucent roofing covering is utilized to improve thermal comfort without reducing the level of illumination. Materials and methods. In this study, field measurements were applied to investigate and compares temperature stratification by floors of naturally ventilated ULK atrium building with different outlet sizes and locations under hot period conditions. The results of field measurement was utilized to develop the baseline model for the computational fluid dynamics (CFD) simulation in future work. Results. These results reveal that the sizes and locations of openings in the atrium building affect on modification of the indoor thermal condition. Moreover, energy efficiency is improved thanks to buoyancy-driven changes in air flow rate in an atrium with multiple openings. Conclusions. This study shows that it can be possible reduce indoor air temperatures by 5 °C during the summer period. In addition to the large inlet openings at different atrium levels, a high ratio of the outlet opening area (&gt;10 %) is recommended. The existing atrium of the building was opened 5 % of the total top-glass roof area, which helps to improve the performance of buoyancy-driven ventilation in order to achieve better atrium cooling performance and prevent the detrimental reverse air movement.

Effect of photovoltaics shading on the growth of chili pepper in controlled greenhouses

The integration of photovoltaic into a greenhouse has been implemented to maximize the energy output and crop production yield from the same land space. The effect of greenhouse external shading of opaque crystalline silicon photovoltaic (PV) panels at 13–26% of the roof area on the microclimate and growth of Chili pepper Capsicum annuum cv. (omega) was investigated. The PV panels were divided into two arrays (each of 4 PVs) and fixed separately on two external pillars of 4 m height in the Southeast and Northwest directions, respectively. Each array of 4 PVs could be tracked from the East-West direction to North-South. There were two greenhouses, one was used as control without shading and the other had the external shading. The results revealed that the external shading of PV slightly decreased air temperatures (1–2 °C) and light intensities (25–40%) but had no effect on the dew point temperatures and relative humidity as compared to the control (unshaded greenhouse). Furthermore, the yield and growth of Chili pepper in the shaded greenhouse was insignificantly higher than that in the unshaded greenhouse. Moreover, the simulation results revealed that the estimated electric energy of photovoltaic panels was 3705 kWh/year at a tilt angle of 25° facing South.

EVALUATION OF THE POTENTIAL OF GREEN ROOFS APPLIED TO AN URBAN FABRIC USING GIS AND REMOTE SENSING DATA CASE OF THE NADOR CITY / MOROCCO

Abstract. Accelerated urban growth has affected many of the planet's natural processes. In cities, most of the surface is covered with asphalt and cement, which has changed the water and air cycles. To restore the balance of urban ecosystems, cities must find the means to create green spaces in an increasingly gray world. Green spaces provide the city and its inhabitants a better living environment. This article uses Nador city as a case study area, this project consists in studying the possibility for the roofs to receive vegetation. The first axis of this project is the quantification of the current vegetation cover at ground level by calculating the Normalized Difference Vegetation Index (NDVI) based on Satellite images Landsat 8, then the classification of the LiDAR point cloud, and the generation of a digital surface model (DSM) of the urban area. This type of derived data was used as the basis for the various stages of estimating the potential plant cover at the roof level. In order to study the different possible scenarios, a set of criteria was applied, such as the minimum roof area, the inclination and the duration of the sunshine on the roof, which is calculated using the linear model of angstrom Prescott based on solar radiation. The study shows that in the most conservative scenario, 21771 suitable buildings that had to be redeveloped into green roofs, with an appropriate surface area of 369.26Ha allowing a 63,40% increase in the city's green space by compared to the current state contributing to the improvement of the quality of life and urban comfort. The average budget for the installation of green roofs in a building with a surface area of 100 m2 varies between 60000dh and 170000dh depending on the type of green roofs used, extensive or intensive. These results would enable planners and researchers in green architecture sciences to carry out more detailed planning analyzes.

Solar fractions of SHIP plants considering the availability of roof area based on OpenStreetMap data

Solar heat for industrial processes (SHIP) can be a key technology to decarbonize the industrial heat demand world-wide. Several national studies use either a bottom-up or a top-down-approach to assess the potential of solar process heat using estimated fixed solar fractions. Due to limited area available for the installation of solar collectors and the seasonality of the load profile, this solar fraction cannot be achieved in all cases. To address this limitation, another estimated factor is used in those studies. However, the impact of the lack of free area on solar fractions and overall solar potential has not been studied in detail so far. Thus, a dataset with load profiles and roof areas from OpenStreetMap GIS data from 489 German companies from secondary and tertiary sector is set up in this study. Based on the standardized pre-design methodology of the VDI 3988 guideline, the evaluations show that one third of the regarded companies lack sufficient roof area whereas two thirds can provide their summer heat demand with solar collectors. Furthermore, the study shows that an ambient temperature dependent heat demand limits the solar potential in terms of solar fraction even more than the available roof area.

Design and Application of the Tank Simulation Model (TSM): Assessing the Ability of Rainwater Harvesting to Meet Domestic Water Demand

Rainwater harvesting (RWH) is a necessary technology to supplement and/or replace insufficient ground and surface water resources for domestic water supplies, especially under changing climate conditions. An accessible and flexible Excel-based RWH simulation tool is developed and applied to investigate the utility of RWH in two regional case studies, under both present conditions and future climate scenarios, through examination of relationships between tank volumes, roof areas, rainfall patterns, and yield. The conversion of complex mathematical formula into a tool with a simple data entry form for infinite combinations of the critical variables enables non-experts to manipulate and optimize designs at the level of RWH implementation. The results clearly show that RWH can augment problematic or insufficient water supplies. Roof area and rainfall distribution have the greatest impact on the ability of a RWH system to meet demand; tank size has a minimal effect, providing a buffer during short dry periods within any given month. Demand met improves in both geographies under future scenarios. Thus, while RWH is insufficient as the sole source of domestic water now and in the future, it is a low-cost supply augmentation solution even in cold climates. RWH solutions are made more accessible through planning tools such as the Tank Simulation Model presented here, which is sufficiently flexible to incorporate climate change scenario planning.

A Case Study for BMPV Systems Optimal Day-Ahead Scheduling and performance evaluation

Optimal scheduling of a distributed energy resources system (DERs) can be beneficial for utilizing renewable energy and relieving the pressures upon the main electric grid. One of the most popular DER systems is the Building mount photovoltaic (BMPV) system. In this paper, a large office building is taken as a case study to develop an optimal day-ahead strategy for the BMPV system considering 24 hours ahead of energy consumption and PV generation uncertainty. This paper mainly includes BMPV system capacity determination, 24 hours ahead of energy usage and PV generation forecasting, and day-ahead optimal strategy development. Firstly, based on collected history energy demands, weather data, and building information, the install capacity of PV is defined by roof area. Furthermore, the battery capacity is constructed by China's latest photovoltaic energy storage capacity standard. Secondly, the ensemble learning model is established using a time-series algorithm and Long Short-term memory (LSTM) to predict day-ahead energy consumption. Moreover, an interval prediction method is used to forecast the PV generation for the next 24 hours. Finally, the accurate energy consumption prediction and PV generation interval are introduced to establish the BMPV system scheduling strategy. The day-ahead optimization scheduling strategy was developed based on Mixed integer linear programming (MILP), targeting minimal economic cost. As a result of the optimization process, the proposed strategy could save 4.8% in economic costs and reduce the peak load of the main grid effectively. Moreover, it can effectively optimize the energy consumption structure of buildings or even distributed energy systems and can provide feasibility to achieve net-zero energy consumption without sacrificing any comfort of occupancy.

Study on the characteristics of airflow at the top of the building with parapet

The presence of the roof structure affects airflow patterns around the building. The recirculation area formed in the roof area is different from the original due to the presence of parapets and billboards. So the traditional formula no longer applies. Pollutant gases emitted by buildings can accumulate in recirculation areas, causing air short circuits and polluting indoor air. However, studies on the flow characteristics of building roofs with parapets are still lacking. In this paper, cfd simulation is used to study the influence of parapets of different heights and summer thermal effects on airflow. The results show that as the height of the parapet increases, the size of the vortex generated at the top also increases gradually. As the temperature difference between the top and the air increases, that is, the Ri increases, the vortices formed on the top will decrease significantly and the amount of reduction is not linear with the temperature difference.