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Adaptive Thermal Comfort and Energy Use in 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 December 2024 | Viewed by 13603

Special Issue Editors


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Guest Editor
Faculty of Environmental Studies, Tokyo City University, Yokohama, Japan
Interests: adaptive thermal comfort; occupant behaviour; thermal environment; energy saving; traditional vernacular building
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Guest Editor
Faculty of Civil and Geodetic Engineering, University of Ljubljana, Ljubljana, Slovenia
Interests: thermal comfort; occupant behavior and built environment interaction; bioclimatic building design and sustainability; building energy simulation; energy performance of building envelopes

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Guest Editor
Sheffield School of Architecture, The University of Sheffield, Sheffield S1 3JD, UK
Interests: adaptive thermal comfort; personal comfort systems; building energy; user behaviour; thermal control

Special Issue Information

Dear Colleagues,

Buildings are usually designed and constructed to address multiple objectives such as shelter, comfort, productivity, security, socioeconomic status and sociocultural status. With the advent of air-conditioning technology in the early 20th century, a new dimension was added to building design. However, soon after that and in the latter part of the 20th century, the global economic recession and heavy dependency of the global economy on fossil fuels led to global warming, and the associated climate change has forced the human race to think otherwise. The problem is compounded manyfold because a human spends almost 90% of their life in different types of built environments.

The building sector is considered one of the highest energy- and resource-intensive sectors, responsible for almost 40% of the world's primary energy use. The building sector also has the highest carbon footprint. With the increasing awareness about climate change and environmental concerns, significant effort has been made through scientific and policy initiatives to reduce the energy intensity and carbon footprint of buildings.

Since humans spend 90% of their time in built environments, indoor environment quality plays an important role in human thermal comfort, health and productivity. Therefore, until the middle of the 20th century, almost the entire focus of building design was maximizing the above three factors. This led to an increase in energy use in buildings. However, global warming and environmental awareness have forced the scientific community to look for ways to reduce energy use in buildings, starting from the design stages.

The thermal adaptation of buildings and people is important for energy-saving building design and there are many different approaches available for reducing the energy use and carbon footprint of buildings. These approaches can be broadly classified as technological interventions (such as intelligent and smart systems, smart building materials, smart sensors, etc.), design interventions (such as low-energy architecture, green buildings, zero- and net-zero-energy buildings, etc.) and functioning interventions (automated façade and window-operation control, maximizing the use of buildings under mixed-mode operation, etc.). We also need to consider the behavioral, physiological and psychological adaptations of occupants in building design.

All the abovementioned interventions and approaches lack conclusive and wide-scale data-backed research conclusions, which sheds light on the complex relationship that exists between indoor thermal comfort and energy use in buildings. A conventional wisdom that persists is that the higher the thermal comfort, the higher the energy use. However, in the context of the present global environmental situation, we need to maximize thermal comfort in the built environment, on the one hand, and minimize energy use in buildings, on the other hand. Due the relevance of the topic in the present context, we invite authors to submit their unpublished and high-impact research to be published in this Special Issue.

The articles submitted for inclusion in this Special Issue must have core research issues relating to “Thermal Comfort and Energy Use in Buildings”. The articles can be from the following areas:

  • The thermal performance of buildings;
  • Climate-adaptive building design;
  • Adaptive building facades;
  • Building energy efficiency;
  • Energy use in buildings;
  • Adaptive thermal comfort;
  • Various occupant behaviors;
  • Personal comfort system;
  • The application of big data management;
  • The application of artificial intelligence;
  • Occupant-centric approaches in building performance;
  • The impact of climate change on thermal comfort;
  • The impact of climate change on building energy performance;
  • Total indoor environment quality issues and impacts;
  • Case studies on the above topics.

Prof. Dr. Hom Bahadur Rijal
Dr. Manoj Kumar Singh
Dr. Sally Shahzad
Guest Editors

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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.

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Published Papers (6 papers)

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Research

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22 pages, 3070 KiB  
Article
Analysis of the Interplay between Indoor Air Quality and Thermal Comfort in University Classrooms for Enhanced HVAC Control
by Giulia Lamberti, Francesco Leccese and Giacomo Salvadori
Energies 2024, 17(20), 5053; https://doi.org/10.3390/en17205053 - 11 Oct 2024
Viewed by 1165
Abstract
While aspects of indoor environmental quality, such as thermal comfort, indoor air quality (IAQ), acoustic, and visual comfort, are usually studied separately, their interactions are crucial yet often overlooked. Understanding how these factors influence each other is essential for a comprehensive perception of [...] Read more.
While aspects of indoor environmental quality, such as thermal comfort, indoor air quality (IAQ), acoustic, and visual comfort, are usually studied separately, their interactions are crucial yet often overlooked. Understanding how these factors influence each other is essential for a comprehensive perception of the indoor environment. This paper investigates the relationship between indoor air quality (IAQ) and thermal comfort using an extensive field investigation conducted in university classrooms during the heating season, collecting 712 samples of subjective responses correlated with environmental measurements. Key findings reveal significant correlations between subjective responses related to the thermal environment and those related to air quality. Perceived control over the thermal environment shows stronger correlations with IAQ responses than with thermal responses, particularly with perceived ventilation (r = 0.41), COVID-19 risk (r = 0.28), and air quality (r = 0.28). Additionally, environmental parameters demonstrate stronger correlations with thermal responses than with IAQ responses. Higher CO2 concentration is associated with increased thermal sensation and decreased thermal preference and perceived control. Conversely, IAQ responses remain relatively stable with changes in indoor operative temperature. The difference between the operative temperature to which the occupants are exposed and their expressed neutral temperature widens as CO2 concentration rises, indicating a reduced adaptive capacity of occupants which is associated with increasing CO2 levels. These insights are crucial for providing HVAC system management strategies that consider the interaction between different aspects of IEQ, aiming to improve occupants’ well-being and reduce energy consumption. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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21 pages, 9949 KiB  
Article
Hygrothermal Performance of the Hemp Concrete Building Envelope
by Aguerata Kaboré, Wahid Maref and Claudiane M. Ouellet-Plamondon
Energies 2024, 17(7), 1740; https://doi.org/10.3390/en17071740 - 4 Apr 2024
Cited by 1 | Viewed by 1674
Abstract
The search for environmentally friendly and low-carbon-footprint construction materials continues progressively. Researchers are now interested in innovative materials that connect with the principles of sustainable construction, and materials such as hemp concrete prove to be promising. This article presents the results of a [...] Read more.
The search for environmentally friendly and low-carbon-footprint construction materials continues progressively. Researchers are now interested in innovative materials that connect with the principles of sustainable construction, and materials such as hemp concrete prove to be promising. This article presents the results of a study that aimed to evaluate the hygrothermal performance of hemp concrete integrated into the building envelope using the hygrothermal tool WUFI Pro 6.2. The simulation model was compared and verified with existing models before its utilization for this study. The results of this verification were in good agreement, which gave us more confidence in its application for further parametric studies of building envelopes in hot climate zones. Three wall systems were simulated: (i) a wall system with hemp concrete, (ii) a compressed earth block wall, and (iii) a cement block wall. The most important variables used in the simulations were the hygrothermal properties of the materials or wall components and the incident solar radiation. The simulation results showed that hemp concrete has good thermal performance and temperature and humidity regulation capabilities of the building envelope. The interior surface temperatures of the hemp concrete walls were between 22.1 °C and 24.6 °C compared to the compressed earth block and cement block walls, where the surface temperatures were between 22.0 °C and 27 °C and between 21.2 °C and 28.7 °C, respectively, and between 23 °C and 45 °C for the exterior temperatures. These values remain the same with the increase in exterior temperatures for hemp concrete walls. In conclusion, hemp concrete could be a great alternative material for use in construction for hot climate zones. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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30 pages, 10698 KiB  
Article
Development of Adaptive Model and Occupant Behavior Model in Four Office Buildings in Nagasaki, Japan
by Kahori Genjo, Haruna Nakanishi, Momoka Oki, Hikaru Imagawa, Tomoko Uno, Teruyuki Saito, Hiroshi Takata, Kazuyo Tsuzuki, Takashi Nakaya, Daisaku Nishina, Kenichi Hasegawa, Taro Mori and Hom Bahadur Rijal
Energies 2023, 16(16), 6060; https://doi.org/10.3390/en16166060 - 18 Aug 2023
Cited by 2 | Viewed by 1657
Abstract
A field survey of indoor environmental measurements and questionnaires on thermal sensation, overall comfort, and behaviors was conducted in four office buildings in Japan by visiting each office every month over a duration of more than a year during the coronavirus disease 2019 [...] Read more.
A field survey of indoor environmental measurements and questionnaires on thermal sensation, overall comfort, and behaviors was conducted in four office buildings in Japan by visiting each office every month over a duration of more than a year during the coronavirus disease 2019 (COVID-19) pandemic. The indoor environment was measured concurrently. We obtained 1047 votes from office workers in their 20s to 60s. The regression and Griffiths’ methods were used to calculate the indoor comfort temperature. A logistic regression analysis was used to develop the occupant behavior model. Over 70% of the occupants found the indoor environment comfortable at a mean comfort temperature of 23.2 to 25.9 °C. Gender differences were observed in thermal sensation and overall comfort, but a gender difference was observed only in the cooling mode for the indoor comfort temperature. An adaptive model was developed for the office buildings in Nagasaki city to predict the indoor comfort temperature from the outdoor air temperature. The proportions of heating, cooling, and fan usage can be predicted from the outdoor air temperature using a logistic regression analysis. The adaptive model and occupant behavior model are useful for the indoor temperature control of the existing buildings and thermal simulation of the new building design. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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15 pages, 3330 KiB  
Article
Virtual Battery Modeling of Air Conditioning Loads in the Presence of Unknown Heat Disturbances
by Seung-Jun Hahm, Ye-Eun Jang and Young-Jin Kim
Energies 2022, 15(24), 9354; https://doi.org/10.3390/en15249354 - 10 Dec 2022
Cited by 1 | Viewed by 1287
Abstract
Air conditioning loads (ACLs) are potential flexible resources that can provide various grid services to the power system. Recent studies have attempted to represent their flexibility using a virtual battery (VB) model for quantification, but the modeling process requires information on thermal parameters [...] Read more.
Air conditioning loads (ACLs) are potential flexible resources that can provide various grid services to the power system. Recent studies have attempted to represent their flexibility using a virtual battery (VB) model for quantification, but the modeling process requires information on thermal parameters and heat disturbances (e.g., solar irradiation and internal heat load) that are difficult to measure. In this paper, we present a new method that models a VB without prior knowledge of such information. First, we construct a thermal dynamic model of an individual ACL using historical input-output data. The linear regression model parameters are identified without using the measurements of disturbances. Second, we derive a VB model from the linear regression parameters using a change of variable technique. We show that the VB can be directly modeled from the regression model of thermal dynamics without estimating the exact thermal parameters and heat disturbances. Third, aggregation of the VB models is implemented. The energy limits of aggregate VB models are designed considering the baseline load prediction error caused by disturbance uncertainty. Finally, simulation results verify the accuracy and effectiveness of the proposed VB modeling strategy. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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Review

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37 pages, 2593 KiB  
Review
Passive Solar Systems for the Promotion of Thermal Comfort in African Countries: A Review
by Michael M. Santos, Ana Vaz Ferreira and João C. G. Lanzinha
Energies 2022, 15(23), 9167; https://doi.org/10.3390/en15239167 - 2 Dec 2022
Cited by 4 | Viewed by 3219
Abstract
Globally, the residential sector consumes a significant amount of energy. Therefore, bioclimatic architectural systems which consider passive solutions should be studied, analyzed, and implemented to reduce energy consumption. This review aims to promote thermal comfort in African countries by using passive solar systems. [...] Read more.
Globally, the residential sector consumes a significant amount of energy. Therefore, bioclimatic architectural systems which consider passive solutions should be studied, analyzed, and implemented to reduce energy consumption. This review aims to promote thermal comfort in African countries by using passive solar systems. It begins with the keyword thermal comfort and then reviews articles published over the last ten years that consider bioclimatic architecture and construction strategies in Africa, the main trends in scientific research in this field, and the possibilities for each climate zone in achieving the highest degree of climate comfort. Following an extensive review, certain bioclimatic architectural strategies adopted in specific countries can be applied in countries with similar climates and this can contribute to significant energy savings through effective functional solar and ventilation design strategies. Several countries have been identified as having the most significant publications on thermal regulations in buildings, and the associated regulations and projects are discussed. Several studies have also examined static and adaptive models of thermal comfort. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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Other

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19 pages, 3701 KiB  
Essay
Transfer Learning in the Transformer Model for Thermal Comfort Prediction: A Case of Limited Data
by Xin Zhang and Peng Li
Energies 2023, 16(20), 7137; https://doi.org/10.3390/en16207137 - 18 Oct 2023
Cited by 4 | Viewed by 2535
Abstract
The HVAC (Heating, Ventilation, and Air Conditioning) system is an important component of a building’s energy consumption, and its primary function is to provide a comfortable thermal environment for occupants. Accurate prediction of occupant thermal comfort is essential for improving building energy utilization [...] Read more.
The HVAC (Heating, Ventilation, and Air Conditioning) system is an important component of a building’s energy consumption, and its primary function is to provide a comfortable thermal environment for occupants. Accurate prediction of occupant thermal comfort is essential for improving building energy utilization as well as health and work efficiency. Therefore, the development of accurate thermal comfort prediction models is of great value. Deep learning based on data-driven techniques has excellent potential for predicting thermal comfort due to the development of artificial intelligence. However, the inability to obtain large quantities of detailed thermal comfort labeling data from residents presents a substantial challenge to the modeling endeavor. This paper proposes a building-to-building transfer learning framework to make deep learning models applicable in data-limited interior building environments, thereby resolving the issue and enhancing model predictive performance. The transfer learning method (TL) is applied to a novel technology dubbed the Transformer model, which has demonstrated outstanding performance in data trend prediction. The model exploits the spatiotemporal relationship of data regarding thermal comfort. Experiments are conducted using the source dataset (Scales project dataset and ASHRAE RP-884 dataset) and the target dataset (Medium US office dataset), and the results show that the proposed TL-Transformer achieves 62.6% accuracy, 57% precision, and a 59% F1 score, and the prediction performance is better than other existing methods. The model is useful for predicting indoor thermal comfort in buildings with limited data, and its validity is verified by experimental results. Full article
(This article belongs to the Special Issue Adaptive Thermal Comfort and Energy Use in Buildings)
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