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Special Issue "Feature Paper Collection: Energy and Buildings"

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

Deadline for manuscript submissions: 18 May 2024 | Viewed by 2145

Special Issue Editors

Faculty of Engineering, University of West Attica, 12243 Athens, Greece
Interests: computational intelligence and evolutionary computation; fuzzy systems; fuzzy control and modelling; fuzzy cognitive maps and petri nets in decision support systems; intelligent control; time series prediction; automation systems in renewable energy resources; intelligent energy management systems and smart buildings; design and management of autonomous smart micro grids; power electronics in photovoltaic systems; control electrochromic devices; modelling and control of reverse osmosis desalination
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are delighted to invite you to contribute a research or review paper for this Collection on reducing the energy needs of buildings, improving building energy efficiency, and improving how energy is managed in buildings. The main topics are presented below:

  • Solar and other renewable energy sources in buildings;
  • Intelligent buildings;
  • Data science (AI, machine learning) for building energy management;
  • Zero-energy, low-energy, and carbon-neutral buildings;
  • Life-cycle energy efficiency of buildings and embodied energy;
  • Life-cycle assessment (LCA) of buildings;
  • Building physics as applied to energy;
  • Energy consumption in buildings;
  • Building energy demand management;
  • District heating and cooling;
  • Heat recovery systems for buildings;
  • Building energy storage;
  • Lighting and other factors related to energy;
  • Smart energy scheduling in hospitals and public buildings.

Prof. Dr. Anastasios Dounis
Dr. Paulo Santos
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 submissions that pass pre-check are 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 2600 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.

Published Papers (1 paper)

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31 pages, 4482 KiB  
In Situ Thermal Transmittance Assessment of the Building Envelope: Practical Advice and Outlooks for Standard and Innovative Procedures
Energies 2023, 16(8), 3319; https://doi.org/10.3390/en16083319 - 07 Apr 2023
Cited by 6 | Viewed by 1704
Different standard methods for the assessment of the thermal performance of the building envelope are used: analogy with coeval building, theoretical method, heat flow meter measurement, simple hot box, infrared thermography, and thermometric method. Review papers on these methods, applied in situ and [...] Read more.
Different standard methods for the assessment of the thermal performance of the building envelope are used: analogy with coeval building, theoretical method, heat flow meter measurement, simple hot box, infrared thermography, and thermometric method. Review papers on these methods, applied in situ and in laboratory, have been published, focusing on theory, equipment, metrological performance, test conditions and data acquisition, data analysis, benefits, and limitations. However, steps forward have been done and not been deepened in previous works: in fact, the representative points method and the weighted area method have been proposed, too, whilst artificial intelligence and data-driven methods have begun to prove the reliability also in the U-value prevision using available datasets. Considering this context, this work aims at updating the literature background considering exclusively in situ methods. The work starts from bibliometric and scientometric analysis not previously conducted: this helped to group the methods and to sketch the innovations and the future perspectives. Indeed, from the bibliometric and scientometric literature analysis what emerged was (i) the richness of the background on this topic, especially in the recent years, (ii) two macro-groups (methods with and without measurements), and (iii) the importance of paper keywords (otherwise, interesting papers are eluded by the output of simple database queries). The method study that followed aims at providing (i) a broader view of the thermal transmittance (U-value) assessment procedures, including the utmost recent applications, proposal, and outlooks in this field, (ii) the understanding on the fundamental theories of the techniques, (iii) practical advice for building-envelope assessment, focusing on the advantages and limitations useful for professionals and researchers involved in the energy audit, conservation, or refurbishment of building stock, (iv) the identification of the interconnection between the techniques that often rely on one another, and (v) final remarks and future perspective of the procedures, which embrace the use of artificial intelligence (AI). From the topic analysis, as a result, it emerged that this is an open field for future research, especially with the implementation of AI, which requires good datasets and trials on the models’ architectures, in terms of input layer, number of hidden layer and neurons, and percentage of data to be employed for model training and testing. Full article
(This article belongs to the Special Issue Feature Paper Collection: Energy and Buildings)
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