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Energy-Saving, Comfort, and Healthier Strategies 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: closed (31 December 2021) | Viewed by 18937

Special Issue Editors

Mechanical & Biomedical Engingineering, Boise State University, Boise, ID 83712, USA
Interests: energy efficiency; renewable energy; smart grid; automation and control; systems modeling
Special Issues, Collections and Topics in MDPI journals
Department of AI Convergence Engineering, Gyeongsang National University, Jinju, Republic of Korea
Interests: internet of things (IoT); artificial intelligence; machine learning; system software
Special Issues, Collections and Topics in MDPI journals
Department of Architectural Engineering, University of Ulsan, Ulsan, Republic of Korea
Interests: building systems; calibrated simulation; energy audit; measurement and verification; solar energy; smart building systems
Special Issues, Collections and Topics in MDPI journals
Department of Building Research, Korea Institute of Civil Engineering and Building Technology, Ilsan, Republic of Korea
Interests: internet of things (IoT); smart building; building energy; thermal comfort; big data; artificial intelligence; building energy management; building energy and information modeling; carbon neutrality
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The same drivers behind the Fourth Industrial Revolution and the Internet of Things are bringing about radical changes in building design and operations. While there have been great strides in building design and operations, a more comprehensive view of occupant comfort, energy savings, environmental quality, and occupant health is called for. Big data from IoT is readily available, and the cost, speed, and accuracy of the sensors are being suitable for personalized comfort and healthier indoor environments. For example, using human-interactive sensors such as wrist bands, air-conditioning systems can provide customized comfort and health conditions while also maintaining energy efficiency. In addition, the building systems based on IoT would be directly relevant to the urgent need to mitigate airborne transmission with illnesses such as COVID-19.

In this Special Issue, we are looking for various topics for smart buildings to help readers and researchers better understand holistic approaches to achieve matured smart buildings. Your papers will help current smart buildings to provide significantly healthier, more comfortable, and energy-efficient indoor environments for occupants.

Prof. Dr. John Gardner
Prof. Dr. Seongjin Lee
Prof. Dr. Kee Han Kim
Dr. Sukjoon Oh
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

  • Smart building 
  • Energy savings 
  • Thermal, visual, aural, and/or olfactory comfort 
  • Healthier building 
  • Virus mitigating system 
  • Sick building syndrome (SBS) 
  • Building energy management system (BEMS) 
  • Home energy management system (HEMS) 
  • Human-interactive building 
  • Smart control 
  • Model-based predictive control (MPC) 
  • Artificial intelligence 
  • Machine learning 
  • Big data 
  • Internet of Things (IoT)

Published Papers (8 papers)

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Research

19 pages, 4892 KiB  
Article
Drone-Assisted Image Processing Scheme using Frame-Based Location Identification for Crack and Energy Loss Detection in Building Envelopes
Energies 2021, 14(19), 6359; https://doi.org/10.3390/en14196359 - 05 Oct 2021
Cited by 9 | Viewed by 2629
Abstract
This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a [...] Read more.
This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a better solution with low computational overhead. Furthermore, a scheme using frame-based location identification was developed to effectively utilize the existing approach by finding the current location of the drone-assisted image frame. The results showed a simplified drone-assisted scheme along with automation, higher accuracy, and better speed while using lower battery energy. Furthermore, this paper found that the cost-effective drone with the attached equipment generated accurate results without using an expensive drone. The new scheme of this paper will contribute to automated anomaly detection, energy auditing, and commissioning for sustainably built environments. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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43 pages, 15285 KiB  
Article
Toward the Renewal of the Sustainable Urban Indicators’ System after a Global Health Crisis. Practical Application in Granada, Spain
Energies 2021, 14(19), 6188; https://doi.org/10.3390/en14196188 - 28 Sep 2021
Cited by 1 | Viewed by 1925
Abstract
The aim of this study is to highlight the need for sustainable urban development by reviewing the different Indicator Systems (SI) and contrasting them with those factors that have had a correlation in the spread of the virus in order to detect its [...] Read more.
The aim of this study is to highlight the need for sustainable urban development by reviewing the different Indicator Systems (SI) and contrasting them with those factors that have had a correlation in the spread of the virus in order to detect its deficiencies. This research carries out an urban diagnosis and analyzes the influence of these factors in order to detect deficiencies and propose a new IS adapted to current needs. Lastly, the new SI is validated through its practical application in one of the Autonomous Communities most affected by the pandemic in Spain. It is concluded that most of the factors causing a worse incidence of the virus are hardly evaluated by the existing IS. The practical analysis shows that there are deficiencies in urban design, resulting in poor environmental quality and urban morphology. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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25 pages, 11243 KiB  
Article
HVAC Operation Schemes and Commissioning Process Resolving Stack Effect Problem and Adjusting According to Changes in the Environment: A Case Study in High-Rise Building in South Korea
Energies 2021, 14(8), 2299; https://doi.org/10.3390/en14082299 - 19 Apr 2021
Cited by 4 | Viewed by 2084
Abstract
Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we [...] Read more.
Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we created a noise level reduction plan by creating a method for pressurizing the high-rise zones of the building according to outdoor conditions. To discover the appropriate pressurization operating modes, we applied a two-year commissioning process to the 50-story building of interest. The 1st- and 47th-floor elevator halls were identified to have the highest noise levels of all other floors. Prior to applying the reduction plan, the maximum noise level on the first floor with the HVAC system turned off was 85 dB(A) and with the HVAC system turned on it was 70 dB(A). Both values exceeded the criteria of 57 dB(A) for a lobby space of a commercial building. In the case of the 47th floor, the maximum noise level with the HVAC system turned off was 58.7 dB(A) and with the HVAC system turned off was 56.0 dB(A), despite the latter having increased airtightness performance and applying preliminary pressurization (i.e., HVAC operation mode 2). These values exceeded the criteria of 48 dB(A) for an elevator hall in a commercial building. Following this initial data, we determined to pressurize the high/mid-rise zones of the building according to the outdoor air temperature and wind velocity conditions, which we categorized into four types (i.e., HVAC operation mode 4). To this effect, the first-floor elevator hall’s maximum noise level was 56.6 dB(A), meeting the criteria, and the 47th-floor elevator hall’s maximum noise level was 49.5 dB(A), still exceeding the criteria but by an insignificant amount. Although the HVAC pressurization operation we utilized resulted in favorable results for the target building A, it may not be as effective in other new high-rise buildings, creating changes to the indoor air environment or to the energy costs in maintaining a building. However, for the purposes of resolving the stack effect, we believe that the commissioning process we took to optimize the HVAC operation that is presented here can be applied to other new and existing high-rise commercial buildings. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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16 pages, 4442 KiB  
Article
Assessment of Indoor Air Parameters in Building Equipped with Decentralised Façade Ventilation Device
Energies 2021, 14(4), 1176; https://doi.org/10.3390/en14041176 - 22 Feb 2021
Cited by 10 | Viewed by 1482
Abstract
The study contains an analysis of a decentralised unit installed in a building façade, where air supply and exhaust cycles are swapped by proper positioning of dampers. The analysis was carried out in real conditions in an office building. The Computational Fluid Dynamics [...] Read more.
The study contains an analysis of a decentralised unit installed in a building façade, where air supply and exhaust cycles are swapped by proper positioning of dampers. The analysis was carried out in real conditions in an office building. The Computational Fluid Dynamics (CFD) simulation is an important element of the system design, and has become more and more widely used. Simulation of the analysed unit has shown air stream distribution in a room. Moreover, it allowed for determination of indoor air temperature. Completed analysis and CFD simulations allow for the observation that façade ventilation systems provide a good way to improve the indoor microclimate, as they effectively reduce air pollution. The decentralised façade ventilation unit reduced the carbon dioxide concentration to a level lower than 1000 ppm and maintained the indoor air temperature in the range of 19.5–22 °C. The error for CFD simulation equals 0.5%, which is not much. The results of research and analysis show that the highest reduction of carbon dioxide concentration occurred when supply/exhaust time equalled 10 min. At the same time, when supply/exhaust time equalled 10 min, the indoor air temperature was the lowest of the recorded values. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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21 pages, 8514 KiB  
Article
Estimation of Self-Sufficiency Rate in Detached Houses Using Home Energy Management System Data
Energies 2021, 14(4), 975; https://doi.org/10.3390/en14040975 - 12 Feb 2021
Cited by 5 | Viewed by 1819
Abstract
Japan’s energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household [...] Read more.
Japan’s energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household sector. The purpose of this paper was to identify ways to reduce household energy consumption without compromising the quality of life in residence. However, the reduction methods vary by region, building specifications, household type, equipment specifications, season, and weather. The value of this paper is based on a systematic analysis of home energy management systems (HEMS) data from about 50,000 households under various conditions. We are analyzing ways to reduce energy consumption. Few studies have analyzed this much back-up data, which is likely to lead to a reduction in CO2 emissions across the household sector. To explore ways to reduce energy consumption in this sector, the company has introduced and provided services for home energy management systems (HEMS) since 2011 and is currently collecting HEMS data for up to 50,000 households. In order to grasp the actual state of energy consumption in each household, HEMS data are systematically analyzed, necessary conditions for energy reduction and self-sufficiency rate (SSR) improvement are analyzed, and energy consumption under certain conditions is estimated using storage batteries (SB) and heat pump water heaters (HPWH). In addition, energy consumption was investigated by actual measurement and simulation for several hundred households. Since power generation and consumption vary greatly depending on the region, building specifications, household type, equipment specifications, season, weather, etc., it is necessary to analyze these factors systematically. As a conclusion, in order to improve SSR, it is necessary to (1) reduce surplus power consumption and energy consumption of heat pump water heaters (HPWHs), (2) increase solar power generation, and (3) increase the size of SB. This study contributes to the spread of advanced housing and the reduction of CO2 emissions in the household sector. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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17 pages, 4940 KiB  
Article
Proposition of Design Capacity of Borehole Heat Exchangers for Use in the Schematic-Design Stage
Energies 2021, 14(4), 822; https://doi.org/10.3390/en14040822 - 04 Feb 2021
Cited by 8 | Viewed by 1820
Abstract
This study proposes a simple ground heat exchanger design capacity that is applicable in the schematic-design stage for several configurations used for borehole heat exchangers (BHEs). Three configurations—single, compact, and irregular types—were selected, and the heat transfer rate per unit BHE was calculated [...] Read more.
This study proposes a simple ground heat exchanger design capacity that is applicable in the schematic-design stage for several configurations used for borehole heat exchangers (BHEs). Three configurations—single, compact, and irregular types—were selected, and the heat transfer rate per unit BHE was calculated considering heat interference. In a case study with a typical configuration and general range of ground thermal conductivity, the BHE heat transfer rate of the compact configuration decreased owing to heat interference as the number of BHEs increased. However, with respect to the irregular configuration, the heat transfer rate increased as the same number increased. This was attributed to the relatively large increment rate of the distance between the boreholes in the irregular configurations, making the heat recovery factor more dominant than the heat interference. The results show that the average heat transfer rate values per BHE applicable to each configuration type in the schematic-design stage were 12.1 kW for the single configuration, 5.8 kW for the compact type, and 10.3 kW for the irregular configuration. However, owing to the large range of results for each case study, the error needs to be reduced by maximally utilizing the information available at the schematic-design stage. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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26 pages, 2868 KiB  
Article
Examining the Journey of a Pay-as-You-Go Solar Home System Customer: A Case Study of Rwanda
Energies 2021, 14(2), 330; https://doi.org/10.3390/en14020330 - 08 Jan 2021
Cited by 16 | Viewed by 3315
Abstract
Solar home systems (SHSs) are successfully addressing energy access deficits across the globe, particularly when combined with pay-as-you-go (PAYG) payment models, allowing households to pay for energy services in small instalments. To increase energy access, it is vital to understand the PAYG SHS [...] Read more.
Solar home systems (SHSs) are successfully addressing energy access deficits across the globe, particularly when combined with pay-as-you-go (PAYG) payment models, allowing households to pay for energy services in small instalments. To increase energy access, it is vital to understand the PAYG SHS customer journey in depth. To aid this, the paper presents unique data from active customers, consisting of structured interviews (n = 100) and two focus groups (n = 24) across two districts in Rwanda. These results are presented under a novel customer journey framework, which describes all the individual stages a customer might experience, including awareness and understanding, purchase, usage, upgrade, recommendation and retaining or switching energy source. The paper reveals that the customer journey is non-linear and cyclical in nature, acknowledging that a household operates in a social network within which they could influence or be influenced by others. It also highlights the growing importance of SHS recommendations in raising awareness of SHSs, pointing to the shifts in the off-grid energy market environment where customer awareness no longer appears to be a main adoption barrier. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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16 pages, 5766 KiB  
Article
Next-Day Prediction of Hourly Solar Irradiance Using Local Weather Forecasts and LSTM Trained with Non-Local Data
Energies 2020, 13(20), 5258; https://doi.org/10.3390/en13205258 - 10 Oct 2020
Cited by 42 | Viewed by 2758
Abstract
Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation [...] Read more.
Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation of various weather data in real time. In this study, a long short-term memory algorithm–based model is proposed using limited input data and data from other regions. The proposed model can predict solar irradiance using next-day weather forecasts by the Korea Meteorological Administration and daily solar irradiance, and it is possible to build a model with one-time learning using national and international data. The model developed in this study showed excellent predictive performance with a coefficient of variation of the root mean square error of 12% per year even if the learning and forecast regions were different, assuming that the weather forecast was correct. Full article
(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)
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