Estimating the Photovoltaic Potential of Building Facades and Roofs Using the Industry Foundation Classes

Photovoltaic energy generation has gained wide attention owing to its efficiency and environmental benefits. Therefore, it has become important to accurately evaluate the photovoltaic energy generation potential of building surfaces. As the number of building floors increases, the area of the facades becomes much larger than that of the roof, providing improved potential for photovoltaic equipment installation. Conventional urban solar potential evaluation methods are usually based on light detection and ranging (LiDAR). However, LiDAR can only be used in existing buildings, and the lack of semantic information in the point cloud data generated by LiDAR makes it impossible to evaluate the photovoltaic potential of facades (including details such as windows) in detail and with accuracy. In this study, we developed a method to accurately extract facades and roofs in order to evaluate photovoltaic potential based on the Industry Foundation Classes. To verify the feasibility of this approach, we used a building from Xuzhou city, Jiangsu province, China. The simulation results indicate that, out of the total building photovoltaic installable area (8995 m2), that of the facade is 8240 m2. The photovoltaic potential of the simulated building could reach 1054.69 MWh/year. The sensitivity studies of the grid resolution, the time interval and the computation time confirmed the reasonability of the determined conditions. The method proposed offers great potential for energy planning departments and the improved utilization of buildings.

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The Combination of Building Greenery and Photovoltaic Energy Production—A Discussion of Challenges and Opportunities in Design

Sustainability ◽

10.3390/su13031537 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1537

Author(s):

Irene Zluwa ◽

Ulrike Pitha

Keyword(s):

Energy Production ◽

Substrate Surface ◽

Relevant Literature ◽

Green Roofs ◽

Cooling Effect ◽

Photovoltaic Energy ◽

Pv Systems ◽

System A ◽

Challenges And Opportunities ◽

Building Surfaces

In the case of building surfaces, the installation of green roofs or green facades can be used to reduce the temperature of the environment and the building. In addition, introducing photovoltaic energy production will help to reduce CO2 emissions. Both approaches (building greenery and photovoltaic energy production) compete, as both of them are located on the exterior of buildings. This paper aims to give an overview of solutions for the combination of building greenery (BG) systems and photovoltaic (PV) panels. Planning principles for different applications are outlined in a guideline for planning a sustainable surface on contemporary buildings. A comprehensive literature review was done. Identified solutions of combinations were systematically analysed and discussed in comparison with additional relevant literature. The main findings of this paper were: (A) BG and PV systems with low sub-construction heights require shallow substrates/low growing plants, whereas in the case of the combination of (a semi)-intensive GR system, a distance of a minimum 60 cm between the substrate surface and lower panel edge is recommended; (B) The cooling effect of the greenery depends on the distance between the PV and the air velocity; (C) if the substrate is dry, there is no evapotranspiration and therefore no cooling effect; (D) A spectrum of different PV systems, sub-constructions, and plants for the combination of BG and PV is necessary and suitable for different applications shown within the publication.

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BIM Supported Surveying and Imaging Combination for Heritage Conservation

Remote Sensing ◽

10.3390/rs13081584 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1584

Author(s):

Pedro Martín-Lerones ◽

David Olmedo ◽

Ana López-Vidal ◽

Jaime Gómez-García-Bermejo ◽

Eduardo Zalama

Keyword(s):

Laser Scanning ◽

Point Clouds ◽

Cloud Data ◽

Industry Foundation Classes ◽

3D Point Clouds ◽

Conservation Actions ◽

Heritage Building ◽

2D Imaging ◽

Digital Survey ◽

Level 2

As the basis for analysis and management of heritage assets, 3D laser scanning and photogrammetric 3D reconstruction have been probed as adequate techniques for point cloud data acquisition. The European Directive 2014/24/EU imposes BIM Level 2 for government centrally procured projects as a collaborative process of producing federated discipline-specific models. Although BIM software resources are intensified and increasingly growing, distinct specifications for heritage (H-BIM) are essential to driving particular processes and tools to efficiency shifting from point clouds to meaningful information ready to be exchanged using non-proprietary formats, such as Industry Foundation Classes (IFC). This paper details a procedure for processing enriched 3D point clouds into the REVIT software package due to its worldwide popularity and how closely it integrates with the BIM concept. The procedure will be additionally supported by a tailored plug-in to make high-quality 3D digital survey datasets usable together with 2D imaging, enhancing the capability to depict contextualized important graphical data to properly planning conservation actions. As a practical example, a 2D/3D enhanced combination is worked to accurately include into a BIM project, the length, orientation, and width of a big crack on the walls of the Castle of Torrelobatón (Spain) as a representative heritage building.

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Deep learning for pattern recognition of photovoltaic energy generation

The Electricity Journal ◽

10.1016/j.tej.2020.106882 ◽

2021 ◽

Vol 34 (1) ◽

pp. 106882

Author(s):

Mahdi Khodayar ◽

Mohammad E. Khodayar ◽

Seyed Mohammad Jafar Jalali

Keyword(s):

Pattern Recognition ◽

Deep Learning ◽

Energy Generation ◽

Photovoltaic Energy

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Photovoltaic Energy Generation and Control for an Autonomous Shunt Active Power Filter

Smart Grids ◽

10.1201/b16908-12 ◽

2017 ◽

pp. 275-309

Author(s):

Ayman Blorfan ◽

Damien Flieller ◽

Patrice Wira ◽

Guy Sturtzer ◽

Jean Mercklé

Keyword(s):

Active Power Filter ◽

Energy Generation ◽

Active Power ◽

Shunt Active Power Filter ◽

Photovoltaic Energy ◽

Power Filter ◽

And Control

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Conversor Doubler Output Coupled Inductor para Aplicações de Fontes Alternativas

10.53316/sepoc2021.003 ◽

2021 ◽

Author(s):

HENRIQUE JAHNKE HOCH ◽

TIAGO MIGUEL KLEIN FAISTEL ◽

ADEMIR TOEBE ◽

ANTóNIO MANUEL SANTOS SPENCER ANDRADE

Keyword(s):

High Voltage ◽

Duty Cycle ◽

Low Voltage ◽

Energy Generation ◽

Boost Converter ◽

Voltage Gain ◽

Switched Capacitors ◽

Number Of Components ◽

Photovoltaic Energy ◽

High Voltage Gain

High step-up DC-DC converters are necessary in photovoltaic energy generation, due the low voltage of the panels source. This article propose the Doubler Output Coupled Inductor converter. This converter is based in boost converter and utilize switched capacitors and a coupled inductor to maximize the static voltage gain. The converter achieve a high voltage gain with low turns ratio in the coupled inductor and an acceptable duty cycle. Can highlight the converter utilize low number of components and have low voltage and current stresses in semiconductors. To validate and evaluate the operation of the converter a 200W prototype is simulated.

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Monitoring High Throughput Distributed System using Statistical Data Analysis

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.f9810.038620 ◽

2020 ◽

Vol 8 (6) ◽

pp. 4590-4596

Keyword(s):

Time Series ◽

Statistical Analysis ◽

Distributed System ◽

High Throughput ◽

Statistical Data ◽

Time Interval ◽

Statistical Data Analysis ◽

Cloud Data ◽

Data Pipeline ◽

Cloud Data Centers

Monitoring high throughput distributed system by using a statistical analysis of the “historical time series” of an Instrumentation Data”. “The Pipeline has been made to process the information which can be otherwise called data pipeline, is a lot of information handling components associated in arrangement, where yield of one component is the contribution of the next one”. Several codes are giving different visualization for statistical analysis of data. “Network and Cloud Data Centers” generate a lot of data every second; this data can be gathered as period arrangement information. A timeseries is a grouping taken at progressive similarly dispersed focuses in time that implies at a particular time interval to a particular time, the estimations of explicit information that was taken is known as information of a time-series. “This time-series information can be gathered utilizing framework measurements like CPU, Memory, and Disk utilization”. The TICK and ELK Stack is abbreviation for a foundation of open source instruments worked “to make collection, storage, graphing, and alerting” on time arrangement data incredibly easy. As an information collector, using Telegraf, “for storing and analyzing” information and the time-series database InfluxDB and Elasticsearch. For plotting and visualizing used Grafana and Kibana. Watchman is utilized for alert refinement and once system metrics usage exceeds the specified threshold, the alert is generated and sends it to the Telegram.

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Automatic 2D Floorplan CAD Generation from 3D Point Clouds

Applied Sciences ◽

10.3390/app10082817 ◽

2020 ◽

Vol 10 (8) ◽

pp. 2817 ◽

Cited By ~ 1

Author(s):

Uuganbayar Gankhuyag ◽

Ji-Hyeong Han

Keyword(s):

Point Clouds ◽

Detection Algorithm ◽

Information Modeling ◽

Ongoing Research ◽

Cloud Data ◽

Industry Foundation Classes ◽

Automated Method ◽

3D Point Clouds ◽

Building Information ◽

Geometric Quality

In the architecture, engineering, and construction (AEC) industry, creating an indoor model of existing buildings has been a challenging task since the introduction of building information modeling (BIM). Because the process of BIM is primarily manual and implies a high possibility of error, the automated creation of indoor models remains an ongoing research. In this paper, we propose a fully automated method to generate 2D floorplan computer-aided designs (CADs) from 3D point clouds. The proposed method consists of two main parts. The first is to detect planes in buildings, such as walls, floors, and ceilings, from unstructured 3D point clouds and to classify them based on the Manhattan-World (MW) assumption. The second is to generate 3D BIM in the industry foundation classes (IFC) format and a 2D floorplan CAD using the proposed line-detection algorithm. We experimented the proposed method on 3D point cloud data from a university building, residential houses, and apartments and evaluated the geometric quality of a wall reconstruction. We also offer the source code for the proposed method on GitHub.

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