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Development of Energy-Efficient Solutions for Smart Buildings

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 3157

Special Issue Editor


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Guest Editor
Department of Industrial and Information Engineering and Economics (DIIIE), University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, I 67100 L’Aquila, Italy
Interests: building physics; energy efficiency; lighting systems; dynamic simulations; lighting control systems; heat transfer; renewable energy
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Special Issue Information

Dear Colleagues,

The building sector is one of the main contributors to final energy consumption, with 104.9 exajoules globally [1], and it is still highly dependent on the consumption of oil products and natural gas, resulting in a high production of greenhouse gas emissions.

Thus, in this scenario, it is essential to study innovative and advanced technological solutions that can contain the energy consumption of buildings while ensuring high indoor environmental quality.

This Special Issue on the “Development of Energy-Efficient solutions for Smart Buildings“ aims to collect high-quality scientific papers varying from innovative HVAC and lighting systems solutions to smart and green building proposals.

The Special Issue welcomes papers on the following topics:

  • HVAC systems solutions;
  • Lighting systems solutions;
  • HVAC and lighting control systems;
  • Building simulation;
  • Smart and green buildings;
  • Sustainable and innovative materials;
  • Climate change and weather data;
  • Renewable energy sources for buildings;
  • Thermal and visual comfort;
  • Heat transfer in multilayer building components;
  • Daylight harvesting;
  • Nondestructive testing;
  • Smart and innovative HVAC control strategies;
  • Urban building energy modeling;
  • Machine learning approaches;
  • Smart solutions;
  • Case studies.

Reference

[1] https://www.iea.org/data-and-statistics/data-tools/energy-statistics-data-browser?country=WORLD&fuel=Energy%20consumption&indicator=TFCShareBySector

Dr. Tullio De Rubeis
Guest Editor

Manuscript Submission Information

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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

  • smart buildings
  • energy efficiency
  • HVAC and lighting systems
  • case studies
  • optimization
  • comfort
  • renewable sources
  • sustainable buildings

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Published Papers (2 papers)

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Research

20 pages, 8289 KiB  
Article
Optimizing Solar Heating for Thangka Exhibition Halls: A Case Study in Malkang Cultural Village
by Wenyang Han, Yan Bai, Miao Du, Yujie Tao, Yin Zhang and Qianru Yang
Energies 2024, 17(9), 2091; https://doi.org/10.3390/en17092091 - 27 Apr 2024
Viewed by 1051
Abstract
With the continuous development of rural revitalization and urbanization in China, the sustainable transformation of traditional rural architecture has become increasingly important. This study takes the Thangka exhibition hall in rural Malkang, Sichuan Province, as the research object and proposes a Thangka exhibition [...] Read more.
With the continuous development of rural revitalization and urbanization in China, the sustainable transformation of traditional rural architecture has become increasingly important. This study takes the Thangka exhibition hall in rural Malkang, Sichuan Province, as the research object and proposes a Thangka exhibition hall architectural design centered around solar heating and aiming for near-zero energy consumption. The research method involves establishing a solar energy system model on the roof of the exhibition hall and utilizing solar angle and area calculation formulas along with simulation software to calculate the optimal installation angle and area of solar panels, with the aim of achieving indoor temperatures that meet Thangka protection requirements while achieving zero-energy heating. Preliminary results indicate that this solar-centric near-zero energy architectural design can effectively promote the increase in indoor temperature through solar thermal conversion. Additionally, through calculation and simulation, the optimal installation angle for the solar panels achieving zero-energy heating is determined to be 24.25 with an azimuth angle of −1.2. The optimum installation area for solar panels is 8.2 square meters in the showroom and 2.7 square meters in the storeroom. Among these, the solar panel area for the Thangka exhibition hall constitutes 4.12% of the total area and is required for maintaining Thangka protection temperature requirements throughout the year, while the solar panel area for the storage room constitutes 1.88% and is also needed for the same purpose. Studying the optimal installation angle and area of solar panels can transform the exhibition hall into a near-zero-energy building, meeting the temperature requirements for Thangka preservation and human thermal comfort, while also achieving optimal economic benefits. This provides guidance and a reference for promoting near-zero-energy buildings in rural areas. Full article
(This article belongs to the Special Issue Development of Energy-Efficient Solutions for Smart Buildings)
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28 pages, 758 KiB  
Article
EECO: An AI-Based Algorithm for Energy-Efficient Comfort Optimisation
by Giacomo Segala, Roberto Doriguzzi-Corin, Claudio Peroni, Matteo Gerola and Domenico Siracusa
Energies 2023, 16(21), 7334; https://doi.org/10.3390/en16217334 - 29 Oct 2023
Cited by 1 | Viewed by 1589
Abstract
Environmental comfort takes a central role in the well-being and health of people. In modern industrial, commercial, and residential buildings, passive energy sources (such as solar irradiance and heat exchangers) and heating, ventilation, and air conditioning (HVAC) systems are usually employed to achieve [...] Read more.
Environmental comfort takes a central role in the well-being and health of people. In modern industrial, commercial, and residential buildings, passive energy sources (such as solar irradiance and heat exchangers) and heating, ventilation, and air conditioning (HVAC) systems are usually employed to achieve the required comfort. While passive strategies can effectively enhance the livability of indoor spaces with limited or no energy cost, active strategies based on HVAC machines are often preferred to have direct control over the environment. Commonly, the working parameters of such machines are manually tuned to a fixed set point during working hours or throughout the whole day, leading to inefficiencies in terms of comfort and energy consumption. Albeit effective, previous works that tackle the comfort–energy tradeoff are tailored to the specific environment under study (in terms of geometry, characteristics of the building, etc.) and thus cannot be applied on a large industrial scale. We address the problem from a different angle and propose an adaptive and practical solution for comfort optimisation. It does not require the intervention of expert personnel or any customisations around the environment while it implicitly analyses the influence of different agents (e.g., passive phenomena) on the monitored parameters. A convolutional neural network (CNN) predicts the long-term impact on thermal comfort and energy consumption of a range of possible actuation strategies for the HVAC system. The decision on the best HVAC settings is taken by choosing the combination of ON/OFF and set point (SP), which optimises thermal comfort and, at the same time, minimises energy consumption. We validate our solution in a real-world scenario and through software simulations, providing a performance comparison against the fixed set point strategy and a greedy approach. The evaluation results show that our solution achieves the desired thermal comfort while reducing the energy footprint by up to approximately 16% in a real environment. Full article
(This article belongs to the Special Issue Development of Energy-Efficient Solutions for Smart Buildings)
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