Special Issue "Building and Urban Energy Prediction-Big Data Analysis and Sustainable Design"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 31 March 2020.

Special Issue Editors

Dr. Ravi Srinivasan
E-Mail Website
Guest Editor
M.E. Rinker, Sr. School of Building Construction Management, College of Design, Construction and Planning, University of Florida, Gainesville, FL 32611-5703, USA
Interests: building/urban energy modeling, simulation, and visualization
Dr. Mahabir Bhandari
E-Mail Website
Guest Editor
Building Technology Research and Integration Center (BTRIC), Oak Ridge National Laboratory, 1Bethel valley Rd, Oak Ridge, TN, USA
Interests: building energy modeling and calibration, building controls and integration, building envelope

Special Issue Information

Dear Colleagues,

Owing to advancements in computer design, in today’s world, there are two sensational trends that support sustainable building design and engineering, namely, real-time building energy prediction/big data analysis and technology revolution.

On one hand, traditional building energy modeling and simulation tools have been widely employed for prediction analysis. Coupled with empirical validation, the accuracy of these tools has been tested and improved. Among others, existing buildings have benefited from building energy big data analysis such as deep learning to understand the behavior of building systems and their occupants in order to effectively provide thermal comfort yet reduce overall energy use. Low-cost, low-energy sensor technologies coupled with wireless data transfer have enabled onsite building and occupant-related data acquisition and have proved to be effective tools to validate prediction as necessary.

On the other hand, the remarkable and timely evolution of technologies supporting building design, engineering, operation, and maintenance cannot be understated. Technologies such as advances in geographic information system (GIS) mapping technology, unmanned aerial vehicles (UAVs), and virtual/augmented reality (VR/AR) promise superior data acquisition and exploration. These technologies are not only here to stay but poised for exponential growth. UAV or drone technologies have been used in building construction and maintenance phases; for example, UAVs have been used as human safety systems during the building construction phase, and these can be integrated with thermal imaging systems to inspect thermal bridging effects that affect energy use during the building operation phase. Similarly, VR/AR technologies have been re-introduced to the building design and engineering paradigm, although these technologies were “tested” for sustainable design a decade ago, and they were found to be unaffordable and cumbersome to use.

This Special Issue “Building Energy Prediction/Big Data Analysis and Sustainable Design” invites authors to submit papers that explore the nexus between building energy and technology revolution. Topics may include but are not limited to the following:

  • Building energy modeling and simulation;
  • Machine learning and automated building(s) model development;
  • Building energy big data analysis;
  • Sensor technologies for building data acquisition;
  • Building outdoor/indoor air quality and comfort measurements;
  • Virtual reality (VR), augmented reality (AR) in sustainable design and engineering;
  • Urban energy modeling and simulation;
  • Urban energy visualization techniques;
  • Sustainability approaches for large campuses or urban systems.

Dr. Ravi Srinivasan
Dr. Mahabir Bhandari
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Building energy modeling
  • Machine learning
  • Automated building model development
  • Big data analysis
  • Sensor and control technologies
  • Virtual reality and augmented reality visualization
  • Urban energy modeling
  • Sustainability

Published Papers (4 papers)

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Research

Open AccessArticle
Application of a Big Data Framework for Data Monitoring on a Smart Campus
Sustainability 2019, 11(20), 5552; https://doi.org/10.3390/su11205552 - 09 Oct 2019
Abstract
At present, university campuses integrate technologies such as the internet of things, cloud computing, and big data, among others, which provide support to the campus to improve their resource management processes and learning models. Integrating these technologies into a centralized environment allows for [...] Read more.
At present, university campuses integrate technologies such as the internet of things, cloud computing, and big data, among others, which provide support to the campus to improve their resource management processes and learning models. Integrating these technologies into a centralized environment allows for the creation of a controlled environment and, subsequently, an intelligent environment. These environments are ideal for generating new management methods that can solve problems of global interest, such as resource consumption. The integration of new technologies also allows for the focusing of its efforts on improving the quality of life of its inhabitants. However, the comfort and benefits of technology must be developed in a sustainable environment where there is harmony between people and nature. For this, it is necessary to improve the energy consumption of the smart campus, which is possible by constantly monitoring and analyzing the data to detect any anomaly in the system. This work integrates a big data framework capable of analyzing the data, regardless of its format, providing effective and efficient responses to each process. The method developed is generic, which allows for its application to be adequate in addressing the needs of any smart campus. Full article
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Open AccessArticle
Quantifying Impacts of Urban Microclimate on a Building Energy Consumption—A Case Study
Sustainability 2019, 11(18), 4921; https://doi.org/10.3390/su11184921 - 09 Sep 2019
Abstract
This paper considered an actual neighborhood to quantify impacts of the local urban microclimate on energy consumption for an academic building in College Park, USA. Specifically, this study accounted for solar irradiances on building and ground surfaces to evaluate impacts of the local [...] Read more.
This paper considered an actual neighborhood to quantify impacts of the local urban microclimate on energy consumption for an academic building in College Park, USA. Specifically, this study accounted for solar irradiances on building and ground surfaces to evaluate impacts of the local convective heat transfer coefficient (CHTC), infiltration rate, and coefficient of performance (COP) on building cooling systems. Using computational fluid dynamics (CFD) allowed for the calculation of local temperature and velocity values and implementation of the local variables in the building energy simulation (BES) model. The discrepancies among the cases with different CHTCs showed slight influence of CHTCs on sensible load, in which the maximum variations existed 1.95% for sensible cooling load and 3.82% for sensible heating load. The COP analyses indicated windward wall and upstream roof are the best locations for the installation of these cooling systems. This study used adjusted infiltration rate values that take into account the local temperature and velocity. The results indicated the annual cooling and heating energy increased by 2.67% and decreased by 2.18%, respectively. Full article
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Open AccessArticle
Constructal Macroscale Thermodynamic Model of Spherical Urban Greenhouse Form with Double Thermal Envelope within Heat Currents
Sustainability 2019, 11(14), 3897; https://doi.org/10.3390/su11143897 - 17 Jul 2019
Abstract
Urban agriculture is becoming a timely environmental friendly practice to strengthen cities’ resilience to climate change. However, there is a lack of academic literature regarding the thermodynamic potential of interior urban agriculture. Furthermore, there is always a need to develop, from scratch, an [...] Read more.
Urban agriculture is becoming a timely environmental friendly practice to strengthen cities’ resilience to climate change. However, there is a lack of academic literature regarding the thermodynamic potential of interior urban agriculture. Furthermore, there is always a need to develop, from scratch, an updated methodological approach that aims to assist architects of conceiving such specific thermodynamically complex interior environments. In this paper, urban space is identified as a ‘flow system’, and Bejan’s constructal law of generation of flow structure is used to morph and discover the system flow architecture that offers greater global performance (greater access to what flows). More precisely, a macroscale thermodynamic model of spherical urban greenhouse form with double thermal envelope has been developed while the methodological approach resulted in the definition of a decisional flowchart that can be reproduced by other researchers. On the basis of this macroscale constructal model, the present paper proposes reduced models that link thermodynamic and geometric parameters in an accurate manner and can be used at early design stages for pedagogic and qualitative optimization purposes, integrating urban farming to architectural programming. Full article
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Open AccessArticle
Occupant Behavior for Energy Conservation in Commercial Buildings: Lessons Learned from Competition at the Oak Ridge National Laboratory
Sustainability 2019, 11(12), 3297; https://doi.org/10.3390/su11123297 - 14 Jun 2019
Abstract
Accompanying efforts worldwide to deploy sustainable building technologies shows a pressing need for expanded research on occupant behavior. Discourse is lacking concerning drivers of occupant behavior for energy conservation, especially in the case of commercial buildings. This paper explores potential determinants of occupant [...] Read more.
Accompanying efforts worldwide to deploy sustainable building technologies shows a pressing need for expanded research on occupant behavior. Discourse is lacking concerning drivers of occupant behavior for energy conservation, especially in the case of commercial buildings. This paper explores potential determinants of occupant behavior for energy conservation in commercial buildings. This is investigated in a case study of a two-month energy conservation competition involving eight office buildings at the Oak Ridge National Laboratory. Four buildings achieved energy savings based on the previous year’s baseline. Potential challenges and success factors of occupant behavior for energy conservation during the competition were explored based on an explanatory research design incorporating energy data, participant interviews, and surveys. The findings suggest that both social and technological aspects may be important drivers of energy conservation. The determinants of occupant behavior for energy conservation in commercial buildings suggested for further research include bottom-up involvement, stakeholder relationship management, targeted information, real-time energy visualization, and mobile social platforms. This paper presents initial implications, with a need for further research on these propositions and on their impacts on occupant behavior. This paper aims to contribute to both academia and practitioners in the arena of commercial building sustainability. Full article
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