Thermal comfort and building energy consumption implications - A review

To mitigate the impact of climate change and global warming, the use of renewable energies is increasing day by day significantly. A considerable amount of electricity is generated from renewable energy sources since the last decade. Among the potential renewable energies, photovoltaic (PV) has experienced enormous growth in electricity generation. A large number of PV systems have been installed in on-grid and off-grid systems in the last few years. The number of PV systems will increase rapidly in the future due to the policies of the government and international organizations, and the advantages of PV technology. However, the variability of PV power generation creates different negative impacts on the electric grid system, such as the stability, reliability, and planning of the operation, aside from the economic benefits. Therefore, accurate forecasting of PV power generation is significantly important to stabilize and secure grid operation and promote large-scale PV power integration. A good number of research has been conducted to forecast PV power generation in different perspectives. This paper made a comprehensive and systematic review of the direct forecasting of PV power generation. The importance of the correlation of the input-output data and the preprocessing of model input data are discussed. This review covers the performance analysis of several PV power forecasting models based on different classifications. The critical analysis of recent works, including statistical and machine-learning models based on historical data, is also presented. Moreover, the strengths and weaknesses of the different forecasting models, including hybrid models, and performance matrices in evaluating the forecasting model, are considered in this research. In addition, the potential benefits of model optimization are also discussed.

Forecasting of photovoltaic power generation and model optimization: A review

Urban building energy modeling – A review of a nascent field

In the last decades, 3D city models appear to have been predominantly used for visualisation; however, today they are being increasingly employed in a number of domains and for a large range of tasks beyond visualisation. In this paper, we seek to understand and document the state of the art regarding the utilisation of 3D city models across multiple domains based on a comprehensive literature study including hundreds of research papers, technical reports and online resources. A challenge in a study such as ours is that the ways in which 3D city models are used cannot be readily listed due to fuzziness, terminological ambiguity, unclear added-value of 3D geoinformation in some instances, and absence of technical information. To address this challenge, we delineate a hierarchical terminology (spatial operations, use cases, applications), and develop a theoretical reasoning to segment and categorise the diverse uses of 3D city models. Following this framework, we provide a list of identified use cases of 3D city models (with a description of each), and their applications. Our study demonstrates that 3D city models are employed in at least 29 use cases that are a part of more than 100 applications. The classified inventory could be useful for scientists as well as stakeholders in the geospatial industry, such as companies and national mapping agencies, as it may serve as a reference document to better position their operations, design product portfolios, and to better understand the market.

/pdf/applications-of-3d-city-models-state-of-the-art-review-3yewcl5e4i.pdf

Applications of 3D City Models: State of the Art Review

CityGML is the international standard of the Open Geospatial Consortium (OGC) for the representation and exchange of 3D city models It defines the three-dimensional geometry, topology, semantics and appearance of the most relevant topographic objects in urban or regional contexts These definitions are provided in different, well-defined Levels-of-Detail (multiresolution model) The focus of CityGML is on the semantical aspects of 3D city models, its structures, taxonomies and aggregations, allowing users to employ virtual 3D city models for advanced analysis and visualization tasks in a variety of application domains such as urban planning, indoor/outdoor pedestrian navigation, environmental simulations, cultural heritage, or facility management This is in contrast to purely geometrical/graphical models such as KML, VRML, or X3D, which do not provide sufficient semantics CityGML is based on the Geography Markup Language (GML), which provides a standardized geometry model Due to this model and its well-defined semantics and structures, CityGML facilitates interoperable data exchange in the context of geo web services and spatial data infrastructures Since its standardization in 2008, CityGML has become used on a worldwide scale: tools from notable companies in the geospatial field provide CityGML interfaces Many applications and projects use this standard CityGML is also having a strong impact on science: numerous approaches use CityGML, particularly its semantics, for disaster management, emergency responses, or energy-related applications as well as for visualizations, or they contribute to CityGML, improving its consistency and validity, or use CityGML, particularly its different Levels-of-Detail, as a source or target for generalizations This paper gives an overview of CityGML, its underlying concepts, its Levels-of-Detail, how to extend it, its applications, its likely future development, and the role it plays in scientific research Furthermore, its relationship to other standards from the fields of computer graphics and computer-aided architectural design and to the prospective INSPIRE model are discussed, as well as the impact CityGML has and is having on the software industry, on applications of 3D city models, and on science generally

CityGML – Interoperable semantic 3D city models

https://architecture.mit.edu/sites/architecture.mit.edu/files/attachments/lecture/large%20scale%20integration%20of%20photovoltaics.pdf

Large scale integration of photovoltaics in cities

Building energy evaluation tools available today are only able to effectively analyse individual buildings and usually either they require a high amount of input data or they are too imprecise in energy predictions at a city (district) scale because of too many assumptions made. In this paper, two tools based on 3D models are compared to see whether there is an approach that would probably be able to fit both – the amount of data available and the number of assumptions made. A case study in the German town of Essen was chosen in the framework of the research project WeBest, where six building types representing the most important building periods were analysed. The urban simulation tool SimStadt, an in-house development of HFT Stuttgart, based on 3D urban geometry, is used to calculate the heat demand for both single building scale and city district scale. The individual building typology results are compared with the commercial dynamic building simulation software TRNSYS. The influence of the availability and quality of data input regarding the geometrical building parameters on the accuracy of simulation models are analysed. Different Levels of Details (LoDs) of the 3D building models are tested to prove the scalability of SimStadt from single buildings to city districts without loss of quality and accuracy in larger areas with a short computational time.

/pdf/comparison-of-building-modelling-assumptions-and-methods-for-5bmwuan0xs.pdf

Comparison of building modelling assumptions and methods for urban scale heat demand forecasting

This study aims to derive an estimating method for the energy performance of urban quarters. To quantify the energy performance of city quarters, the influence of the surrounding urban form must be considered, for instance, the street distance, height of the neighboring buildings, or urban site coverage. In this work, the lighting, heating, and cooling performance of urban districts with different urban forms was simulated in detail using software tools such as EnergyPlus, Radiance, and Daysim. Interrelations between those effects are analyzed with respect to thermal and visual comfort condition. Electric lighting consumption is calculated first, and the thermal effect of artificial lighting is set as an input to the heating and cooling performance calculation. The analyses show that the site thermal performance depends on the arrangement of the urban geometry according to solar gains, and there is a correlation between energy savings and efficient urban design. The simulation results are validated with m...

A method to quantify the energy performance in urban quarters

A forecast of the individual heating energy demand of each building can be used for energy planning and management in a district heating network. The goal of this research work is to estimate such a potential for an urban quarter in Ostfildern, Germany. To achieve this goal, a method for the automatic extraction of the building’s heating volume via a geo-information system is used. These geometries serve as an interface for the simulation model which calculates the building heating energy demand. The additional publication of the monitored consumption data via a Web Application is done to make residents aware of the sustainable urban development in their city.

http://ibpsa-usa.org/index.php/ibpusa/article/download/309/298

Modeling energy demand for heating at city scale

This study is a part of a large scale urban development project called POLYCITY dealing with how to make cities more energy efficient. The project is already in progress in three different countries like Italy, Spain and Germany. We will keep our analysis focused only on German part Scharnhauser Park, which is located in Stuttgart. In this project the working and living places are integrated in order to get a sustainable city quarter with special emphasis on minimum travel distance and low energy consumption. As renewable energies are an additional source to conventional ones, they are more and more important for the production of the energy. The interesting feature is that a great deal of the necessary energy will be provided from roof top PV-systems and wood fired cogeneration plants. Laser Scanning data along with GeoMedia are used for finding the potentials of roof top. The analysis is also supported with Web Application to disseminate the information to the public. This approach will set a good example for supplying green energy in residential quarters and will provide a basis for the sustainability of similar communities.

http://ieeexplore.ieee.org/iel5/5446613/5454174/05454212.pdf

Potential of roof top PV-systems for supplying electricity in residential area Scharnhauser Park

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Aneta Strzalka

Author Tools

Chat about Author