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Buildings
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Advanced Building Technologies for Energy Savings and Decarbonization
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Advanced Building Technologies for Energy Savings and Decarbonization

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: 30 September 2024 | Viewed by 6326

Special Issue Editors

Dr. Piljae Im

E-Mail Website
Guest Editor
Integrated Building Deployment and Analysis, Building and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Interests: empirical validation of building energy simulation model; advanced control; measurement and verification; building energy modeling; HVAC system; field measurement; development of prototype models; fault detection and diagnosis
Dr. Yeobeom Yoon

E-Mail Website
Guest Editor
Integrated Building Deployment and Analysis Group, Buildings and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Interests: building energy modeling; EnergyPlus; building optimal control; energy performance evaluation; data analysis; measurement and verification
Dr. Sungkyun Jung

E-Mail Website
Guest Editor
Integrated Building Deployment and Analysis, Building and Transportation Science Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA
Interests: building energy codes and standards; building energy modeling; enrgy efficiency; energyplus; doe-2; measurement and verification; data analysis

Special Issue Information

Dear Colleagues,

The building sector is one of the primary consumers of energy. Since decarbonization and electrification are our new goals, new and/or advanced building operation strategies or building equipment are needed to maintain or improve indoor environmental quality while minimizing building energy consumption.

The aims and scope of this Special Issue are to introduce advanced building energy technologies, measurement and verification approaches, and fault detection and diagnosis methods using simulation and/or experimental studies to minimize building energy consumption, reduce CO2 emissions, and improve indoor environmental quality.

To achieve the goals of this Special Issue, we welcome submissions from interdisciplinary and multidisciplinary professional areas, such as computer science, mechanical engineering, and civil engineering, in collaboration with building science and architecture researchers.

We welcome the submission of research that presents views on the utilization of new and advanced technologies in various professional areas to save energy, reduce CO2 emissions, and improve indoor environment quality in buildings.

Dr. Piljae Im
Dr. Yeobeom Yoon
Dr. Sungkyun Jung
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 monthly 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

  • building energy
  • building energy simulation modeling
  • experimental study
  • energy-efficient technologies
  • advanced control
  • HVAC systems
  • indoor environmental quality
  • building control optimization
  • fault detection and diagnosis

Published Papers (6 papers)

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Research

16 pages, 3646 KiB  
Article
Impact of Insulation Strategies of Cross-Laminated Timber Assemblies on Energy Use, Peak Demand, and Carbon Emissions
by Mikael Salonvaara and André Desjarlais
Buildings 2024, 14(4), 1089; https://doi.org/10.3390/buildings14041089 - 13 Apr 2024
Viewed by 472
Abstract
Cross-Laminated Timber (CLT) panels have many structural benefits but do not have much thermal resistance. We have developed a solution to insulate CLT structures that uses high-performance insulation panels that provide R-values up to R40/inch. The CLT panels are made of layers of [...] Read more.
Cross-Laminated Timber (CLT) panels have many structural benefits but do not have much thermal resistance. We have developed a solution to insulate CLT structures that uses high-performance insulation panels that provide R-values up to R40/inch. The CLT panels are made of layers of wood laminates (three, five, seven or more). The solution replaces some of the wood laminates in the CLT production with the insulation panels in a staggered fashion so that the wood laminates maintain contact throughout the panel, ensuring the CLT panel’s structural integrity. The insulated CLT panels have factory-installed water-resistive barriers reducing the installation time by eliminating installing insulation and water-resistive barriers on site. Per simulations, the CLT/insulation panel achieved code-required insulation levels with commonly available insulation materials. The significance of the thermal mass of CLT/insulation hybrid building envelopes was quantified by comparing the whole building energy performance and peak demand of traditional low mass and CLT wall assemblies resulting in up to 7% reduction in peak demand for cooling in Knoxville, TN, in a multifamily building. Buildings contribute over 40 percent of carbon emissions. The proposed CLT/insulation hybrid building envelope addresses both operational and embodied carbon by having high thermal resistances due to the embedded insulation sections and eliminating the use of high embodied carbon materials such as steel and concrete. The carbon benefit is estimated. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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16 pages, 5884 KiB  
Article
Achieving Energy Self-Sufficiency in a Dormitory Building: An Experimental Analysis of a PV–AWHP-ERV Integrated System
by Su-Kwang Yang, Yul-Ho Kang and Young-Chull Ahn
Buildings 2024, 14(4), 882; https://doi.org/10.3390/buildings14040882 - 25 Mar 2024
Viewed by 565
Abstract
In this study, we investigated the performance of air-to-water heat pump (AWHP) and energy recovery ventilator (ERV) systems combined with photovoltaics (PV) to achieve the energy independence of a dormitory building and conducted an analysis of the energy independence rate and economic feasibility [...] Read more.
In this study, we investigated the performance of air-to-water heat pump (AWHP) and energy recovery ventilator (ERV) systems combined with photovoltaics (PV) to achieve the energy independence of a dormitory building and conducted an analysis of the energy independence rate and economic feasibility by using energy storage devices. Our data were collected for 5 months from July to November, and the building energy load, energy consumption, and system performance were derived by measuring the PV power generation, purchase, sales volume, AWHP inlet and outlet water temperature, and ERV outdoor, supply, and exhaust temperature. When analyzing representative days, the PV–AWHP integrated system achieved an energy efficiency ratio (EER) of 4.49 and a coefficient of performance (COP) of 2.27. Even when the generated electrical energy exceeds 100% of the electricity consumption, the energy self-sufficiency rate remains at 24% due to the imbalance between energy consumption and production. The monthly average energy self-sufficiency rate changed significantly during the measurement period, from 20.27% in November to 57.95% in September, highlighting the importance of energy storage for self-reliance. When using a 4 kWp solar power system and 4 kWh and 8 kWh batteries, the annual energy self-sufficiency rate would increase to 67.43% and 86.98%, respectively, and our economic analysis showed it would take 16.5 years and more than 20 years, respectively, to become profitable compared to the operation of an AWHP system alone. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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18 pages, 1619 KiB  
Article
Development of Building Design Optimization Methodology: Residential Building Applications
by Yeonjin Bae, Donghun Kim and William Travis Horton
Buildings 2024, 14(1), 107; https://doi.org/10.3390/buildings14010107 - 31 Dec 2023
Viewed by 867
Abstract
Building design optimization is a highly complex problem, requiring long computational running processes because of the many options that exist when a building is being designed. This paper introduces an integrated approach through which to perform this optimization within an acceptable time frame. [...] Read more.
Building design optimization is a highly complex problem, requiring long computational running processes because of the many options that exist when a building is being designed. This paper introduces an integrated approach through which to perform this optimization within an acceptable time frame. The approach includes the methods of variable selection, model simplification, and a sequential optimization process. Using singular value decomposition, a large number of design variables is reduced to a smaller subset that can be solved more quickly through the optimization algorithm. To expedite the variable selection process, a modeling approach that quickly simulates annual energy consumption was developed to replace full annual energy simulations. The developed methodology was applied to two residential buildings in the US, and the results are discussed herein. To assess the accuracy of the integrated optimization methodology, the optimized life cycle costs are compaa variables demonstrating the strongest contributions in the optimization study were identified. The proposed methodology significantly shortened the time requirements for the optimization processes of the two case studies by 74% and 84%; the optimized life cycle costs were within 0.05% and 0.06%, respectively, of the optimum point. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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27 pages, 4595 KiB  
Article
Comparative Analysis of ANN and LSTM Prediction Accuracy and Cooling Energy Savings through AHU-DAT Control in an Office Building
by Byeongmo Seo, Yeobeom Yoon, Kwang Ho Lee and Soolyeon Cho
Buildings 2023, 13(6), 1434; https://doi.org/10.3390/buildings13061434 - 31 May 2023
Cited by 2 | Viewed by 1266
Abstract
This paper proposes the optimal algorithm for controlling the HVAC system in the target building. Previous studies have analyzed pre-selected algorithms without considering the unique data characteristics of the target building, such as location, climate conditions, and HVAC system type. To address this, [...] Read more.
This paper proposes the optimal algorithm for controlling the HVAC system in the target building. Previous studies have analyzed pre-selected algorithms without considering the unique data characteristics of the target building, such as location, climate conditions, and HVAC system type. To address this, we compare the accuracy of cooling load prediction using ANN and LSTM algorithms, widely used in building energy research, to determine the optimal algorithm for HVAC control in the target building. We develop a simulation model calibrated with actual data to ensure data reliability and compare the energy consumption of the existing HVAC control method and the two algorithms-based methods. Results show that the ANN algorithm, with a CV(RMSE) of 12.7%, has a higher prediction accuracy than the LSTM algorithm, CV(RMSE) of 17.3%, making it a more suitable algorithm for HVAC control. Furthermore, implementing the ANN-based approach results in a 3.2% cooling energy reduction from the optimal control of Air Handling Unit (AHU) Discharge Air Temperature (DAT) compared to the fixed DAT at 12.8 °C in a representative day. This study demonstrates that ML-based HVAC system control can effectively reduce cooling energy consumption in HVAC systems, providing an effective strategy for energy conservation and improved HVAC system efficiency. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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18 pages, 3193 KiB  
Article
Potential Cooling Energy Savings of Economizer Control and Artificial-Neural-Network-Based Air-Handling Unit Discharge Air Temperature Control for Commercial Building
by Yeobeom Yoon, Byeongmo Seo and Soolyeon Cho
Buildings 2023, 13(5), 1174; https://doi.org/10.3390/buildings13051174 - 28 Apr 2023
Cited by 2 | Viewed by 1273
Abstract
Heating, ventilation, and air-conditioning (HVAC) systems play a significant role in building energy consumption, accounting for around 50% of total energy usage. As a result, it is essential to explore ways to conserve energy and improve HVAC system efficiency. One such solution is [...] Read more.
Heating, ventilation, and air-conditioning (HVAC) systems play a significant role in building energy consumption, accounting for around 50% of total energy usage. As a result, it is essential to explore ways to conserve energy and improve HVAC system efficiency. One such solution is the use of economizer controls, which can reduce cooling energy consumption by using the free-cooling effect. However, there are various types of economizer controls available, and their effectiveness may vary depending on the specific climate conditions. To investigate the cooling energy-saving potential of economizer controls, this study employs a dry-bulb temperature-based economizer control approach. The dry-bulb temperature-based control strategy uses the outdoor air temperature as an indicator of whether free cooling can be used instead of mechanical cooling. This study also introduces an artificial neural network (ANN) prediction model to optimize the control of the HVAC system, which can lead to additional cooling energy savings. To develop the ANN prediction model, the EnergyPlus program is used for simulation modeling, and the Python programming language is employed for model development. The results show that implementing a temperature-based economizer control strategy can lead to a reduction of 7.6% in annual cooling energy consumption. Moreover, by employing an ANN-based optimal control of discharge air temperature in air-handling units, an additional 22.1% of cooling energy savings can be achieved. In conclusion, the findings of this study demonstrate that the implementation of economizer controls, especially the dry-bulb temperature-based approach, can be an effective strategy for reducing cooling energy consumption in HVAC systems. Additionally, using ANN prediction models to optimize HVAC system controls can further increase energy savings, resulting in improved energy efficiency and reduced operating costs. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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27 pages, 11909 KiB  
Article
Sensor Incipient Fault Impacts on Building Energy Performance: A Case Study on a Multi-Zone Commercial Building
by Yanfei Li, Piljae Im, Seungjae Lee, Yeonjin Bae, Yeobeom Yoon and Sangkeun Lee
Buildings 2023, 13(2), 520; https://doi.org/10.3390/buildings13020520 - 14 Feb 2023
Cited by 3 | Viewed by 1231
Abstract
Existing studies show sensor faults/error could double building energy consumption and carbon emissions compared with the baseline. Those studies assume that the sensor error is fixed or constant. However, sensor faults are incipient in real conditions and there were extremely limited studies investigating [...] Read more.
Existing studies show sensor faults/error could double building energy consumption and carbon emissions compared with the baseline. Those studies assume that the sensor error is fixed or constant. However, sensor faults are incipient in real conditions and there were extremely limited studies investigating the incipient sensor fault impacts systematically. This study filled in this research gap by studying time-developing sensor fault impacts to rule-based controls on a 10-zone office building. The control sequences for variable air volume boxes (VAV) with an air handling unit (AHU) system were selected based on ASHRAE Guideline 36-2018: High-Performance Sequences of Operation for HVAC Systems. Large-scale simulations on cloud were conducted (3600 cases) through stochastic approach. Results show (1) The site energy differences could go −3.3% lower or 18.1% higher, compared with baseline. (2) The heating energy differences could go −66.5% lower or 314.4% higher, compared with baseline. (3) The cooling energy differences could go −11.5% lower or 65.0% higher, compared with baseline. (4) The fan energy differences could go 0.15% lower or 6.9% higher, compared with baseline. Full article
(This article belongs to the Special Issue Advanced Building Technologies for Energy Savings and Decarbonization)
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