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Energies
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Optimization and Innovation of Energy Efficient Buildings and Smart Cities
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Optimization and Innovation of Energy Efficient Buildings and Smart Cities

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

Deadline for manuscript submissions: 31 July 2024 | Viewed by 6159

Special Issue Editors

Prof. Dr. Rongyue Zheng

E-Mail Website
Guest Editor
Faculty of Civil and Environmental Engineering, Ningbo University, Ningbo 315211, China
Interests: structural safety and engineering risk analysis; construction management based on BIM; energy-efficient buildings and reduction in carbon emission
Dr. Li Huang

E-Mail Website
Guest Editor
Faculty of Civil and Environmental Engineering, Ningbo University, Ningbo 315211, China
Interests: green buildings and smart buildings; latent thermal energy storage systems; renewable energy applications; smart construction

Special Issue Information

Dear Colleagues,

Cities are responsible for the majority of final energy consumption and CO2 emissions. Increased global urbanization has led to energy and water scarcity, traffic congestion, environmental degradation, and safety risks from aging infrastructures. The adoption of the smart city strategy can make cities more efficient and economical, ensure they are more sustainable, and enhance quality of life. In smart cities, both residential and commercial buildings are more efficient and use less energy. Energy-efficient buildings are the essential basis of smart cities.

This Special Issue aims to present and disseminate the most recent advances related to the design, modeling, construction, operation, maintenance, and assessment of energy-efficient buildings and smart cities.

Topics of interest for publication include but are not limited to:

  • Energy-efficient buildings, low-carbon buildings, passive houses, and zero energy buildings;
  • Green buildings;
  • Energy-efficient retrofitting and smart retrofitting;
  • Digital infrastructure;
  • Data collection, storage, analysis, and information processing at a citywide level;
  • Smart city services;
  • Smart transportation and mobility;
  • Renewable energy and energy efficiency;
  • Smart and sustainable buildings;
  • Smart governance;
  • Smart economy;
  • Smart environment.

Prof. Dr. Rongyue Zheng
Dr. Li Huang
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.

Keywords

  • energy-efficient buildings
  • smart cities
  • information and communication technology (ICT)
  • smart data
  • smart grid
  • renewable energy
  • key performance indicators
  • assessment tool
  • critical analysis
  • monitoring
  • modeling

Published Papers (3 papers)

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Research

31 pages, 31881 KiB  
Article
A Retrofit Strategy for Real-Time Monitoring of Building Electrical Circuits Based on the SmartLVGrid Metamodel
by Rubens A. Fernandes, Raimundo C. S. Gomes, Ozenir Dias, Celso Carvalho, Israel G. Torné, Jozias P. Oliveira and Carlos T. C. Júnior
Energies 2022, 15(23), 9234; https://doi.org/10.3390/en15239234 - 6 Dec 2022
Cited by 1 | Viewed by 1818
Abstract
The Internet of things (IoT) paradigm promotes the emergence of solutions to enable energy-management strategies. However, these solutions may favor the disposal or replacement of outdated but still necessary systems. Thus, a proposal that advocates the retrofit of pre-existing systems would be an [...] Read more.
The Internet of things (IoT) paradigm promotes the emergence of solutions to enable energy-management strategies. However, these solutions may favor the disposal or replacement of outdated but still necessary systems. Thus, a proposal that advocates the retrofit of pre-existing systems would be an alternative to implement energy monitoring. In this sense, this work presents a strategy for monitoring electrical parameters in real time by using IoT solutions, cloud-resident applications, and retrofitting of legacy building electrical systems. In this implementation, we adapted the SmartLVGrid metamodel to systematize the insertion of remote monitoring resources in low-voltage circuits. For this, we developed embedded platforms for monitoring the circuits of a building electrical panel and application for visualization and data storage in the cloud. With this, remote monitoring of the consumer unit was carried out in relation to energy demand, power factor, and events of variations of electrical parameters in the circuits of the legacy distribution board. We also carried out a case study with the proposed system, identifying events of excess demand in the consumer unit, mitigating the individual contribution of the installation circuits in this process. Therefore, our proposal presents an alternative to enable energy management and maximum use of existing resources. Full article
(This article belongs to the Special Issue Optimization and Innovation of Energy Efficient Buildings and Smart Cities)
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20 pages, 3490 KiB  
Article
Forecast of Energy Consumption and Carbon Emissions in China’s Building Sector to 2060
by Xingfan Pu, Jian Yao and Rongyue Zheng
Energies 2022, 15(14), 4950; https://doi.org/10.3390/en15144950 - 6 Jul 2022
Cited by 16 | Viewed by 2101
Abstract
The goal of reaching the peak of carbon in the construction industry is urgent. However, the research on the feasibility of realizing this goal and the implementation of relevant policies in China is relatively superficial. In view of the historical data of energy [...] Read more.
The goal of reaching the peak of carbon in the construction industry is urgent. However, the research on the feasibility of realizing this goal and the implementation of relevant policies in China is relatively superficial. In view of the historical data of energy consumption and building CO2 emission from 1995 to 2019, this paper establishes a BP neural network model for predicting building CO2 emissions. Moreover, the influencing factors, such as population, GDP, and total construction output, are introduced as the parameters in the model. Through the scenario analysis method explores the practical path to accomplish the peak of building CO2 emissions. When using traditional prediction methods to predict building carbon emissions, the long prediction cycle will increase the possibility of significant errors. Therefore, this paper constructs the calculation model of building carbon emission and forecasts the future carbon emission value through the BP neural network to avoid the error caused by the nonlinear relationship between influencing factors and predicted value. It will effectively predict the feasibility of the carbon peak and the carbon-neutral target set by government, and provide a useful predictive tool for adjusting the new energy structure and formulating related emission reduction policies. Full article
(This article belongs to the Special Issue Optimization and Innovation of Energy Efficient Buildings and Smart Cities)
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12 pages, 2132 KiB  
Article
How Do Temperature Differences and Stable Thermal Conditions Affect the Heat Flux Meter (HFM) Measurements of Walls? Laboratory Experimental Analysis
by Tullio de Rubeis, Luca Evangelisti, Claudia Guattari, Domenica Paoletti, Francesco Asdrubali and Dario Ambrosini
Energies 2022, 15(13), 4746; https://doi.org/10.3390/en15134746 - 28 Jun 2022
Cited by 1 | Viewed by 1511
Abstract
In recent years, experimental tests related to building components through laboratory facilities have relatively matured. The techniques are based on one-dimensional heat transfer by creating a permanent temperature difference over a specimen to control heat fluxes. The three main methods are the Guarded [...] Read more.
In recent years, experimental tests related to building components through laboratory facilities have relatively matured. The techniques are based on one-dimensional heat transfer by creating a permanent temperature difference over a specimen to control heat fluxes. The three main methods are the Guarded Hot Box (GHB) method, the Calibrated Hot Box (CHB) method, and the Heat-Flow Meter method (HFM). The HFM method is the most widely applied technique for measuring on-site U-values of building components and several scientific works stressed the need for high temperature differences between the environments, suggesting 10 °C or 15 °C. However, temperature stability and high temperature gradients are difficult to obtain, especially for Mediterranean climatic conditions. Starting from this, an experimental study was conducted through a GHB apparatus, setting temperature differences from 2 °C to 20 °C between the hot and cold chambers. Heat flow measurements were performed to compute the thermal conductance of a specimen characterized by a known stratigraphy, thus highlighting the effect of the low thermal gradient on data acquired by the heat flow sensor. It was found that, even for low temperature differences (2 °C) maintained by ensuring stable thermal conditions, the experimental results are comparable with those obtained for higher and usual temperature differences (20 °C). Full article
(This article belongs to the Special Issue Optimization and Innovation of Energy Efficient Buildings and Smart Cities)
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