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Special Issue "Energy Efficiency in Smart Buildings and Cities: Current and Future Digital Systems"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Energy and Buildings".

Deadline for manuscript submissions: closed (30 November 2020).

Special Issue Editors

Prof. Lu Aye
E-Mail Website
Guest Editor
Renewable Energy and Energy Efficiency Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia
Interests: sustainability; building energy efficiency; lean systems; system dynamics
Special Issues and Collections in MDPI journals
Dr. Samad M. E. Sepasgozar
E-Mail Website
Guest Editor
Faculty of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia
Interests: sustainability; energy efficiency; artificial intelligence; smart city; digital twin; applications of the Internet of Things; advanced GIS; LiDAR; BIM; digital technology in infrastructure; mixed reality applications; information and communication technology; spatial analysis and visualization; authentic education
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

More than 50% of the world’s population live in cities. “Smart cities” that efficiently manage their resources are attracting more and more attention. The energy efficiency of buildings is one of the critical elements in managing those resources. Advances in Machine Learning (ML), Artificial Intelligence (AI), and the Internet of Things (IoT) enable buildings to be smarter by providing better energy control, which leads to improved energy efficiency and less greenhouse gas emissions. Developments in Information and Communication Technology (ICT) provide better user interfaces, the control of smart buildings, and better thermal comfort. GIS and BIM applications are the foundations for the development of smart cities. Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) applications could reduce construction time and enable the provision of cheaper, better quality buildings.

The purpose of this Special Issue is to disseminate leading research findings and new knowledge regarding digital systems, and we welcome high-quality and original articles that have not yet been published. All selected manuscripts will be subject to a careful peer review and editorial process.

Prof. Lu Aye
Assist. Prof. Dr. Samad Sepasgozar
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. Energies 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 2000 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

  • energy efficiency technology
  • smart buildings
  • smart cities
  • digital systems
  • artificial intelligence (AI) and machine learning (ML) applications
  • implementation of unmanned aerial vehicles, laser scanners, IoT, and sensing technology
  • information and communication technology (ICT)
  • BIM and GIS applications
  • virtual reality (VR), augmented reality (AR), and mixed reality (MR) applications
  • construction and infrastructure
  • life-cycle cost assessment of buildings
  • post-occupancy
  • thermal behavior and comfort
  • low carbon and resilient construction and built environments

Published Papers (1 paper)

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Research

Article
A Heating Controller Designing Based on Living Space Heating Dynamic’s Model Approach in a Smart Building
Energies 2021, 14(4), 998; https://doi.org/10.3390/en14040998 - 14 Feb 2021
Viewed by 464
Abstract
Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that [...] Read more.
Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that most smart building energy management systems deploy quite very basic heating control strategies limited to quite simplistic predesigned use-case scenarios. In the present paper, we propose a heating control strategy taking advantage of the overall identification of the living space by taking advantage of the consideration of the living space users’ presence as additional thermal sources. To handle this, an adaptive controller for the operation of heating transmitters on the basis of soft computing techniques by taking into account the diverse range of occupants in the heating chain is introduced. The strategy of the controller is constructed on a basis of the modeling heating dynamics of living spaces by considering occupants as an additional heating source. The proposed approach for modeling the heating dynamics of living spaces is on the basis of time series prediction by a multilayer perceptron neural network, and the controlling strategy regarding the heating controller takes advantage of a Fuzzy Inference System with the Takagi-Sugeno model. The proposed approach has been implemented for facing the dynamic heating conduct of a real five-floor building’s living spaces located at Senart Campus of University Paris-Est Créteil, taking into account the occupants of spaces in the control chain. The obtained results assessing the efficiency and adaptive functionality of the investigated fuzzy controller designed model-based approach are reported and discussed. Full article
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