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Energy Efficiency in Buildings and Its Sustainable Development
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Energy Efficiency in Buildings and Its Sustainable Development

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: 10 June 2025 | Viewed by 4358

Special Issue Editors

Dr. Javier M. Rey Hernández

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Guest Editor
Mechanical Engineering, Thermal Engines and Fluid Mechanics Department, University of Malaga, Malaga, Spain
Interests: zero energy buildings; HVAC; IAQ; zero carbon buildings; renewable energy systems in buildings; geothermal recovery systems
Special Issues, Collections and Topics in MDPI journals
Dr. Juan Pablo Jimenez Navarro

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Guest Editor
Thermal and Fluid Engineering Department, Engineering School, University of Málaga, Málaga, Spain
Interests: heating and cooling; energy policy; energy efficiency
Dr. Andrea Rocchetti

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Guest Editor
Department of Industrial Engineering, University of Florence, Florence, Italy
Interests: energy; refrigeration cycles; energy efficiency; irreversibility
Prof. Dr. Charles Yousif

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Guest Editor
Institute for Sustainable Energy, University of Malta, Barrakki Street, MXK 1531 Marsaxlokk, Malta
Interests: energy performance of buildings; solar photovoltaic systems; solar heating systems; heat pumps for heating & cooling; shallow-ground geothermal systems; solar and UV radiation monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Special Issue titled "Energy Efficiency in Buildings and Its Sustainable Development" focuses on advancing the concept of zero-energy buildings (ZEBs) as a cornerstone of sustainable development in the construction sector. It aims to explore innovative strategies, technologies, and policies that promote energy efficiency and reduce environmental impacts across the entire building life cycle, including design, construction, operation, renovation, and dismantling. Topics include passive design principles, renewable energy integration, building envelope optimization, smart energy management systems, and occupant behavior analysis. Through interdisciplinary research and case studies, this issue seeks to highlight the potential of ZEBs to minimize energy consumption, mitigate climate change, and foster resilient communities.

Prof. Dr. Javier M Rey Hernandez
Dr. Juan Pablo Jimenez Navarro
Dr. Andrea Rocchetti
Prof. Dr. Charles Yousif
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. Applied Sciences 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 2400 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

  • zero-energy buildings
  • HVAC systems
  • energy efficiency
  • sustainable development
  • renewable energy
  • passive building design
  • zero-carbon building
  • smart energy management
  • climate change mitigation
  • LCA

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Published Papers (4 papers)

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Research

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21 pages, 2374 KiB  
Article
Optimizing Energy Efficiency and Sustainability in Winter Climate Control: Innovative Use of Variable Refrigerant Flow (VRF) Systems in University Buildings
by Yolanda Arroyo Gómez, Julio F. San José-Alonso, Luis J. San José-Gallego, Javier M. Rey-Hernández, Ascensión Sanz-Tejedor and Francisco J. Rey-Martínez
Appl. Sci. 2025, 15(5), 2374; https://doi.org/10.3390/app15052374 - 23 Feb 2025
Viewed by 573
Abstract
This study presents a comprehensive analysis of the energy efficiency and sustainability of Variable Refrigerant Flow (VRF) systems in university buildings during the winter season, offering significant contributions to the field. A novel methodology is introduced to accurately assess the real Seasonal Coefficient [...] Read more.
This study presents a comprehensive analysis of the energy efficiency and sustainability of Variable Refrigerant Flow (VRF) systems in university buildings during the winter season, offering significant contributions to the field. A novel methodology is introduced to accurately assess the real Seasonal Coefficient of Performance (SCOP) of VRF systems, benchmarked against conventional Heating, Ventilation, and Air Conditioning (HVAC) technologies, such as natural gas-fueled boiler systems. The findings demonstrate outstanding seasonal energy performance, with the VRF system achieving a SCOP of 5.349, resulting in substantial energy savings and enhanced sustainability. Key outcomes include a 67% reduction in primary energy consumption and a 79% decrease in greenhouse gas emissions per square meter when compared to traditional boiler systems. Furthermore, VRF systems meet 83% of the building’s energy demand through renewable energy sources, exceeding the regulatory SCOP threshold of 2.5. These results underscore the transformative potential of VRF systems in achieving nearly Zero-Energy Building (nZEB) objectives, illustrating their ability to exceed stringent sustainability standards. The research emphasizes the strategic importance of adopting advanced HVAC solutions, particularly in regions with high heating demands, such as those characterized by continental climates. VRF systems emerge as a superior alternative, optimizing energy consumption while significantly reducing the environmental footprint of buildings. By contributing to global sustainable development and climate change mitigation efforts, this study advocates for the widespread adoption of VRF systems, positioning them as a critical component in the transition toward a sustainable, zero-energy building future. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings and Its Sustainable Development)
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18 pages, 4024 KiB  
Article
Proposal for an Intelligent Methodology to Manage Energy in Buildings and Detect Anomalies as a Compass Towards Zero Energy Buildings (ZEB)
by Irati Prol-Godoy, Roberto Santana, Francisco-Javier Rey-Martinez and Ana Picallo-Perez
Appl. Sci. 2024, 14(23), 10918; https://doi.org/10.3390/app142310918 - 25 Nov 2024
Cited by 1 | Viewed by 766
Abstract
This work aims to advance the optimisation of the efficiency of thermal installations in buildings, contributing to the achievement of Zero Energy Buildings (ZEB) in the context of maintenance and operation. This is achieved through an innovative proposal that merges machine learning techniques [...] Read more.
This work aims to advance the optimisation of the efficiency of thermal installations in buildings, contributing to the achievement of Zero Energy Buildings (ZEB) in the context of maintenance and operation. This is achieved through an innovative proposal that merges machine learning techniques with thermoeconomics to perform diagnoses in building thermal systems and identify cost overruns generated by intrinsic anomalies in the components and quantify their induced effects on the rest of the components. To date, the few contributions combining these techniques have been limited to industrial applications and cost calculation, without addressing their application to building thermal systems, both from a dynamic perspective and for maintenance purposes. Research using Physics-Informed Neural Networks, PINNs, in this area is even scarcer, which underlines the complexity of defining a suitable methodology. Thus, the proposal integrates PINNs with a thermoeconomic diagnosis based on characteristic curves, allowing the comparison of the current operating condition with an anomaly-free reference condition to assess the existence of anomalies and their effects. For this reason, reference models are generated for the first time with PINNs, which represents a break with the conventional maintenance approaches used by professionals in the sector. Therefore, this methodology incorporates techniques that require specialised knowledge in thermodynamic and informatics areas, which motivates the present work to be focused on the exhaustive description of the methodology and to highlight the importance of continuing to explore lines of research in this unexplored field. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings and Its Sustainable Development)
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20 pages, 16364 KiB  
Article
Performance and Economic Analysis of Two Types of High-Temperature Heat Pump Based on New Refrigerants
by Dahan Sun, Jiang Qin and Zhongyan Liu
Appl. Sci. 2024, 14(17), 7735; https://doi.org/10.3390/app14177735 - 2 Sep 2024
Viewed by 1167
Abstract
This paper proposes, for the first time, the research concept of comparing energy and economy between transcritical cycle high-temperature heat pumps and subcritical cycle high-temperature heat pumps with new refrigerants. Experiments and simulations are conducted to compare the system performance and economy of [...] Read more.
This paper proposes, for the first time, the research concept of comparing energy and economy between transcritical cycle high-temperature heat pumps and subcritical cycle high-temperature heat pumps with new refrigerants. Experiments and simulations are conducted to compare the system performance and economy of two heat pumps, and the effects of different factors on the performance of two heat pumps are analyzed. The results show that R744/R1234yf (90/10) and R515-1 are the preferred refrigerants for transcritical cycle heat pumps and subcritical cycle heat pumps, respectively. The COP of the R744/R1234yf (90/10) transcritical heat pump is generally higher than that of the R515B-1 subcritical heat pump, and compared to the R515B-1 subcritical heat pump, the cost recovery period of the R744/R1234yf (90/10) transcritical heat pump is about 9–15 years. Therefore, it is recommended that users who use heat pumps for a long time choose transcritical cycle heat pumps. Meanwhile, with the change of evaporation temperature, the system COP of the R515B-1 subcritical heat pump and R744/R1234yf (90/10) transcritical heat pump increases by 61.11% and 65.91%, respectively. In addition, the optimal charge amount for the R515B-1 subcritical heat pump is 81.8% of that of the R744/R1234yf (90/10) transcritical heat pump. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings and Its Sustainable Development)
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Review

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30 pages, 2202 KiB  
Review
Total Cost of Ownership Prediction in Chilled Water Plants: Contributing Factors and Role of Artificial Intelligence
by Rubaiath E Ulfath, Toh Yen Pang, Ivan Cole, Iain Stewart and Chi-Tsun Cheng
Appl. Sci. 2025, 15(3), 1618; https://doi.org/10.3390/app15031618 - 5 Feb 2025
Viewed by 689
Abstract
This study investigates key parameters and applications of artificial intelligence (AI) in predicting the total cost of ownership (TCO) for chilled water plants (CWPs). Forecasting the TCO of CWPs is challenging due to the diverse and dynamic factors and parameters that influence it, [...] Read more.
This study investigates key parameters and applications of artificial intelligence (AI) in predicting the total cost of ownership (TCO) for chilled water plants (CWPs). Forecasting the TCO of CWPs is challenging due to the diverse and dynamic factors and parameters that influence it, necessitating understanding their complex correlations and causations. While AI and non-AI approaches have improved parameter prediction accuracy in different engineering applications, comprehensive literature reviews on chiller TCO prediction methodologies and their influencing factors are limited. This systematic review addresses three objectives: (1) to identify the key parameters in estimating TCO of CWPs, (2) to examine the existing techniques employed in TCO forecasting and their benefits in energy and cost savings, and (3) to evaluate how AI enhances TCO prediction accuracy and robustness. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, this review analyzed studies from 2017 to 2024 sourced from the Web of Science and Scopus databases. This study identifies several key parameters influencing TCO, including cooling load, energy consumption, chiller capacity, and the Coefficient of Performance (COP). The review shows that AI-driven models, such as deep learning and machine learning algorithms, have improved the accuracy and robustness of TCO predictions, and it further demonstrates scenarios where AI outperforms conventional prediction and forecasting methods. Notably, the current review shows that AI techniques are predicted to be capable of reducing total life cycle costs by up to 18%, based on modeling estimates. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings and Its Sustainable Development)
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