Advanced Technologies in Energy Consumption and Optimization for Residential Buildings

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: 1 January 2026 | Viewed by 379

Special Issue Editors


E-Mail Website
Guest Editor
School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds LS6 3QR, UK
Interests: energy consumption prediction; load forcasting; machine learning; artificial intelligence; hyperspectral image processing; biometric identification techniques; assisted living technologies; image/video processing; embedded systems
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
Interests: spectrum sharing and management for beyond 5G and 6G wireless networks; AI/deep learning applications in wireless communications; Integrated Sensing and Communication (ISAC); Reconfigurable Intelligent Surfaces (RIS) for 6G communications and Internet of Things (IoT) networks

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, Aarhus University, Aarhus 8000, Denmark
Interests: energy integration systems; machine learning; control systems; quantum technology
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Physics, Engineering & Computer Science, Department of Engineering and Technology, University of Hertfordshire, Hatfield AL10 9AB, UK
Interests: applications of signal processing; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The pursuit of energy-efficient, resilient, and intelligent residential buildings is driving significant advancements in technology, sustainability, and construction design. This Special Issue invites pioneering research that explores how advanced technologies and interdisciplinary strategies can optimize energy consumption and enhance energy efficiency, specifically within the context of the building sector.

To ensure alignment with the scope of Buildings, the focus is on innovations that directly impact residential building design, construction, operation, and performance. We aim to integrate diverse fields—including energy systems, Artificial Intelligence (AI), Internet of Things (IoT), Machine Learning (ML), and sustainable living environments—to highlight the latest methodologies and technologies contributing to energy-efficient residential buildings.

We welcome original research and review articles addressing, but not limited to, the following areas:

  • Energy efficiency in residential buildings;
  • Smart energy management systems;
  • Renewable energy integration in homes;
  • Energy optimization algorithms for buildings;
  • Building energy modeling and simulation;
  • Home energy management systems (HEMSs);
  • Monitoring and analytics of residential energy consumption;
  • AI and ML applications in building energy optimization;
  • Energy storage solutions for residential use;
  • Zero-energy and net-zero buildings;
  • Building automation and control systems;
  • IoT-enabled energy management in homes;
  • Smart metering and lighting control;
  • User behavior and energy use in residential settings;
  • Energy efficiency standards and regulations in housing;
  • Policy implications for residential energy systems.

This Special Issue aims to bring together cutting-edge research that advances the design and operation of energy-efficient residential buildings. We encourage submissions that present innovative solutions, practical implementations, and theoretical advancements with clear relevance to the building sector.

We look forward to receiving your valuable contributions to this impactful area of research.

Dr. Akbar Sheikh Akbari
Dr. Faheem Khan
Dr. Mohammad Hassan Khooban
Prof. Dr. Iosif Mporas
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. Buildings 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 efficiency
  • smart energy management systems
  • renewable energy integration
  • energy optimization algorithms
  • building energy modeling
  • home energy management systems (HEMS)
  • energy consumption monitoring
  • artificial intelligence in energy optimization
  • energy storage systems
  • machine learning for energy efficiency
  • zero-energy buildings
  • energy performance simulation
  • building automation systems
  • IoT in energy management
  • smart metering
  • lighting control systems
  • energy consumption analytics
  • energy policy and regulation
  • user behavior and energy consumption and energy efficiency standards

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 2857 KB  
Article
Measuring the Impact of Occupancy Numbers on Energy Consumption in a High-Density Building
by Bashar Alfalah, Mehdi Shahrestani and Li Shao
Buildings 2025, 15(19), 3598; https://doi.org/10.3390/buildings15193598 - 7 Oct 2025
Viewed by 199
Abstract
Buildings significantly impact the environment, accounting for 36% of global final energy consumption and 37% of total carbon emissions. Therefore, reducing energy consumption and mitigating carbon emissions in the building sector is of paramount importance. To achieve this, several factors should be considered. [...] Read more.
Buildings significantly impact the environment, accounting for 36% of global final energy consumption and 37% of total carbon emissions. Therefore, reducing energy consumption and mitigating carbon emissions in the building sector is of paramount importance. To achieve this, several factors should be considered. Among them, building occupants are key drivers in the operation of building services that directly influence energy consumption and energy-related emissions. In this paper, one year of raw energy consumption data from a high-density higher education building in the UK was processed to study the correlation between energy consumption and occupancy level. Additionally, a simulation model was developed to measure the impact of occupancy numbers on building energy consumption. Various data analyses were performed, including correlation, regression, and sensitivity analysis. The results demonstrate a strong correlation between occupancy numbers and electricity consumption of 71.5%. Conversely, 18% was found between occupancy numbers and heat energy consumption, indicating no correlation. The sensitivity analysis results on the impact of changing occupancy numbers in the simulated model, ranging from –30% to +30%, aligned with the results of the analyses performed. Full article
Show Figures

Figure 1

Back to TopTop