Buildings

Research

22 pages, 5790 KiB

Open AccessArticle

A Thermal Model for Rural Housing in Mexico: Towards the Construction of an Internal Temperature Assessment System Using Aerial Thermography

by Miguel Moctezuma-Sánchez, David Espinoza Gómez, Luis Bernardo López-Sosa, Iman Golpour, Mario Morales-Máximo and Ricardo González-Carabes

Buildings 2024, 14(10), 3075; https://doi.org/10.3390/buildings14103075 - 26 Sep 2024

Cited by 1 | Viewed by 854

Abstract

Estimating energy flows that affect temperature increases inside houses is crucial for optimizing building design and enhancing the comfort of living spaces. In this study, a thermal model has been developed to estimate the internal temperature of rural houses in Mexico using aerial [...] Read more.

Estimating energy flows that affect temperature increases inside houses is crucial for optimizing building design and enhancing the comfort of living spaces. In this study, a thermal model has been developed to estimate the internal temperature of rural houses in Mexico using aerial thermography. The methodology used in this study considered three stages: (a) generating a semi-experimental thermal model of heat transfer through roofs for houses with high infiltration, (b) validating the model using contact thermometers in rural community houses, and (c) integrating the developed model using aerial thermography and Python 3.11.4 into user-friendly software. The results demonstrate that the thermal model is effective, as it was tested on two rural house configurations and achieved an error margin of less than 10% when predicting both maximum and minimum temperatures compared to actual measurements. The model consistently estimates the internal house temperatures using aerial thermography by measuring the roof temperatures. Experimental comparisons of internal temperatures in houses with concrete and asbestos roofs and the model’s projections showed deviations of less than 3 °C. The developed software for this purpose relies solely on the fundamental thermal properties of the roofing materials, along with the maximum roof temperature and ambient temperature, making it both efficient and user-friendly for rural community management systems. Additionally, the model identified areas with comfortable temperatures within different sections of a rural community, demonstrating its effectiveness when integrated with aerial thermography. These findings suggest the potential to estimate comfortable temperature ranges in both rural and urban dwellings, while also encouraging the development of public policies aimed at improving rural housing. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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24 pages, 19854 KiB

Open AccessArticle

Preserving Woodcraft in the Digital Age: A Meta-Model-Based Robotic Approach for Sustainable Timber Construction

by Zhe Lai, Yingying Xiao, Zitong Chen, Huiwen Li and Lukui Huang

Buildings 2024, 14(9), 2900; https://doi.org/10.3390/buildings14092900 - 13 Sep 2024

Viewed by 932

Abstract

This study presents an innovative approach to sustainable timber construction by integrating traditional woodworking techniques with advanced robotic technology. The research focuses on three key objectives: preserving traditional craftsmanship, enhancing material conservation, and improving production efficiency. A meta-model-based framework is developed to capture [...] Read more.

This study presents an innovative approach to sustainable timber construction by integrating traditional woodworking techniques with advanced robotic technology. The research focuses on three key objectives: preserving traditional craftsmanship, enhancing material conservation, and improving production efficiency. A meta-model-based framework is developed to capture the woodcrafts of mortise and tenon joints, which are prevalent in traditional Chinese wooden architecture. The study employs parametric design and robotic arm technology to digitize and automate the production process, resulting in significant improvements in material utilization and processing efficiency. Specifically, this study utilizes genetic algorithm strategies to resolve the problem of complex mortise and tenon craftsmanship optimization for robotic arms. Compared to conventional CNC machining, the proposed method demonstrates superior performance in path optimization, reduced material waste, and faster production times. The research contributes to the field of sustainable architecture by offering a novel solution that balances the preservation of cultural heritage with modern construction demands. This approach not only ensures the continuity of traditional woodworking skills but also addresses contemporary challenges in sustainable building practices, paving the way for more environmentally friendly and efficient timber construction methods. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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26 pages, 12046 KiB

Open AccessArticle

Exploring the Opportunities and Gaps in the Transformation of Modern Rural Housing in Southern China to Net Zero Energy Buildings

by Dawei Xia, Zonghan Chen, Jialiang Guo and Yukai Zou

Buildings 2024, 14(9), 2822; https://doi.org/10.3390/buildings14092822 - 7 Sep 2024

Viewed by 839

Abstract

This study explores modern residential buildings in rural areas of Wuhan and Guangzhou to assess the feasibility of achieving net zero energy buildings (NZEBs) through the transformation of existing buildings in southern China’s hot-summer–cold-winter and hot-summer–warm-winter regions. Energy simulations under various climatic scenarios [...] Read more.

This study explores modern residential buildings in rural areas of Wuhan and Guangzhou to assess the feasibility of achieving net zero energy buildings (NZEBs) through the transformation of existing buildings in southern China’s hot-summer–cold-winter and hot-summer–warm-winter regions. Energy simulations under various climatic scenarios identify effective energy-saving measures, such as the use of photovoltaic power generation. The results highlight substantial renovation potential, with energy reductions of approximately 85 kWh/m² (RCP2.6), 90 kWh/m² (RCP4.5), and 115 kWh/m² (RCP8.5). Living patterns significantly influence energy use, especially in buildings with more rooms, where the gaps in the energy demand with net zero standards can reach 560.56 kWh. At the monthly scale, different climate scenarios impact the feasibility of achieving NZEBs, particularly under RCP8.5, where eight rural housing types fail to meet the requirements, with six exceeding 200 kWh energy deficits and the largest energy deficit occurs in June 2090 in Guangzhou, reaching 592.53 kWh, while under RCP2.6, only two buildings with more rooms fail to meet NZE. In summary, in the hot-summer cold-winter region, the energy demand is higher but so is the solar yield. Therefore, under the most adverse RCP8.5 scenario, NZEBs are achievable for 9 months of the year, which is 2 months more compared to Guangzhou under similar conditions. Even after net zero transformation, new rural housing will face greater energy-saving challenges in future climatic conditions, especially under higher concentration pathways. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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22 pages, 5936 KiB

Open AccessArticle

Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations

by Nayara Rodrigues Marques Sakiyama, Joyce Correna Carlo, Felipe Isamu Harger Sakiyama, Nadir Abdessemed, Jürgen Frick and Harald Garrecht

Buildings 2024, 14(9), 2803; https://doi.org/10.3390/buildings14092803 - 6 Sep 2024

Cited by 1 | Viewed by 777

Abstract

Natural Ventilation Effectiveness (NVE) is a performance metric that quantifies when outdoor airflows can be used as a cooling strategy to achieve indoor thermal comfort. Based on standard ventilation threshold and building energy simulation (BES) models, the NVE relates available and required airflows [...] Read more.

Natural Ventilation Effectiveness (NVE) is a performance metric that quantifies when outdoor airflows can be used as a cooling strategy to achieve indoor thermal comfort. Based on standard ventilation threshold and building energy simulation (BES) models, the NVE relates available and required airflows to quantify the usefulness of natural ventilation (NV) through design and building evaluation. Since wind is a significant driving force for ventilation, wind pressure coefficients (

C_{p}

) represent a critical boundary condition when assessing building airflows. Therefore, this paper investigates the impact of different

C_{p}

sources on wind-driven NVE results to see how sensitive the metric is to this variable. For that, an experimental house and a measurement period were used to develop and calibrate the initial BES model. Four

C_{p}

sources are considered: an analytical model from the BES software (i), surface-averaged

C_{p}

values for building windows that were calculated with Computational Fluid Dynamics (CFD) simulations using OpenFOAM through a cloud-based platform (ii_a,b,c), and two databases—AIVC (iii) and Tokyo Polytechnic University (TPU) (iv). The results show a variance among the

C_{p}

sources, which directly impacts airflow predictions; however, its effect on the performance metric was relatively small. The variation in the NVE outcomes with different

C_{p}

’s was 3% at most, and the assessed building could be naturally ventilated around 75% of the investigated time on the first floor and 60% in the ground floor spaces. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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30 pages, 9351 KiB

Open AccessArticle

Achieving Financial Feasibility and Carbon Emission Reduction: Retrofit of a Bangkok Shopping Mall Using Calibrated Simulation

by Kongkun Charoenvisal, Atch Sreshthaputra and Sarin Pinich

Buildings 2024, 14(8), 2512; https://doi.org/10.3390/buildings14082512 - 15 Aug 2024

Viewed by 1425

Abstract

This study investigated the building energy retrofit potential of a shopping mall in Bangkok, Thailand, using a combined building energy modeling and economic analysis approach to achieve a balance between carbon emission reduction and financial feasibility. The study adopted ASHRAE Guideline 14, a [...] Read more.

This study investigated the building energy retrofit potential of a shopping mall in Bangkok, Thailand, using a combined building energy modeling and economic analysis approach to achieve a balance between carbon emission reduction and financial feasibility. The study adopted ASHRAE Guideline 14, a standard for energy modeling accuracy, using whole-building calibrated simulation to evaluate the energy, energy cost, and operational carbon emission reduction achievable through the proposed energy conservation measures. The calibrated model demonstrated high accuracy, achieving an NMBE of 1.10% and CVRMSE of 3.77% for energy consumption, and NMBE of 0.15% and CVRMSE of 5.44% for peak energy demand compared to the monthly data. The economic analysis employed indicators such as NS, AIRR, and DPB, along with MACC analysis, to assess the financial viability of the ECMs and examine the impact of carbon credit cost savings on the analysis results. This case study highlights the critical role of energy modeling and economic analysis in evaluating building retrofits. The findings demonstrate the potential for carbon emission reduction and financial benefits with the case study building achieving up to 12.5% energy cost savings and carbon emission reduction based on a prospective building lifespan of 40 years without compromising financial sustainability. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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23 pages, 5296 KiB

Open AccessArticle

Clustering Open Data for Predictive Modeling of Residential Energy Consumption across Variable Scales: A Case Study in Andalusia, Spain

by Javier García-López, Samuel Domínguez-Amarillo and Juan José Sendra

Buildings 2024, 14(8), 2335; https://doi.org/10.3390/buildings14082335 - 28 Jul 2024

Cited by 1 | Viewed by 997

Abstract

The energy budget of households, linked to residential energy consumption (REC), serves as a critical indicator of quality of life and economy trends. Despite the lack of widely available accurate statistics at regional or smaller scales, they are of crucial interest for a [...] Read more.

The energy budget of households, linked to residential energy consumption (REC), serves as a critical indicator of quality of life and economy trends. Despite the lack of widely available accurate statistics at regional or smaller scales, they are of crucial interest for a better understanding of the features influencing REC and its impact on energy poverty, wellbeing, and the climate crisis. This research aims to present a new information model for predictive parameters and REC forecasting through an innovative use of available open data. Geoprocessing, data mining, and machine learning clustering algorithms were applied to open datasets of location, population, and residential building stock parameters highly correlated with their REC, on the ensemble of 785 municipalities of Andalusia, Spain. The model identified 65 clusters of towns sharing the same potential REC, with 73% of the population concentrated in 10 of these. The resulting data-driven bottom-up model of provincial REC had a mean absolute error of only 0.63%. Furthermore, it provided the territorial distribution, with local resolution, of the identified clusters of cities with similar characteristics. This methodology, with a flexible regional- to city-scale analysis, provides knowledge generation that offers numerous practical applications for energy policy planning. Its future implementation would assist stakeholders and policymakers in enhancing the performance and decarbonization of the residential building stock. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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22 pages, 6861 KiB

Open AccessArticle

A Method of Integrating Air Conditioning Usage Models to Building Simulations for Predicting Residential Cooling Energy Consumption

by Jingyun Ao, Chenqiu Du, Mingyi Jing, Baizhan Li and Zhaoyang Chen

Buildings 2024, 14(7), 2026; https://doi.org/10.3390/buildings14072026 - 3 Jul 2024

Viewed by 1049

Abstract

Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants’ air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into [...] Read more.

Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants’ air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into simulations, in order to improve the prediction performance of AC energy consumption. Based on long-term onsite monitoring of household thermal environments and AC usage patterns, two stochastic models were built using unsupervised cluster and statistical methods. Based on the Monte Carlo method, the AC operation schedule was generated through AC opening duration, setpoints, and other relevant parameters, and was further incorporated into EnergyPlus. The results show that the ideally deterministic AC operation settings from the standard significantly overestimate the cooling energy consumption, where the value based on the fixed mode was 6.35 times higher. The distribution of daily AC energy consumption based on the stochastic modeling was highly consistent with the actual situation, thanks to the accurate prediction of the randomness and dynamics of residents’ AC usage patterns. The total cooling energy consumption based on two stochastic models was found to be much closer to the actual values. The work proposes a method of embedding stochastic AC usage models to EnergyPlus 22.1 benefits for an improvement in building energy consumption simulation and the energy efficiency evaluation regarding occupant behavior in the future. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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27 pages, 10624 KiB

Open AccessArticle

Experimental and Numerical Heat Transfer Assessment and Optimization of an IMSI Based Individual Building Block System of the Kingdom of Bahrain

by Payal Ashish Modi, Abdelgadir Mohamed Mahmoud, Yousif Abdalla Abakr and Abdulla Ebrahim Abdulqader

Buildings 2024, 14(7), 2012; https://doi.org/10.3390/buildings14072012 - 2 Jul 2024

Cited by 1 | Viewed by 742

Abstract

The increase in energy consumption in Bahrain is a significant issue. Insulation blocks are crucial for reducing heat transfer from outside to inside buildings. However, there’s limited research on the thermal performance of Bahrain’s insulation building blocks. No research to date has been [...] Read more.

The increase in energy consumption in Bahrain is a significant issue. Insulation blocks are crucial for reducing heat transfer from outside to inside buildings. However, there’s limited research on the thermal performance of Bahrain’s insulation building blocks. No research to date has been conducted in Bahrain to study the effect of plaster and insulation inserts on the R-value of the blocks. This study examines and optimizes the thermal resistance (R-value) of an ‘Integrated Masonry System International, Ltd. (IMSI)’ block, chosen due to its common use in Bahrain’s commercial and residential construction. The study involves experimental analysis using a hot box setup and numerical analysis through the finite element method (FEM), along with assessing the impact of insulation inserts in the block’s cavities. R-values are calculated and validated for accuracy. The R-value discrepancy between numerical and experimental findings is 2.411%, and between numerical and manufacturer’s data is 5.743%. It is also observed that a 25 mm external plaster, as required by Bahrain’s government (EWA), enhances the R-value by 79.34%. Furthermore, optimizing the IMSI block’s height increased the R-value by 10.67%. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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26 pages, 70114 KiB

Open AccessArticle

A Parametric HBIM Approach for Preservation of Bai Ethnic Traditional Timber Dwellings in Yunnan, China

by Yalong Mao, Huifang Lu, Yingying Xiao, Zhe Lai and Lukui Huang

Buildings 2024, 14(7), 1960; https://doi.org/10.3390/buildings14071960 - 27 Jun 2024

Viewed by 1146

Abstract

This paper proposes a meta-model-based parametric Historic Building Information Modelling (HBIM) approach to preserving and renewing traditional timber dwellings, specifically focusing on traditional Bai ethnic residential architecture. The study integrates traditional architectural principles with contemporary digital construction techniques. Traditional Bai dwellings have complex [...] Read more.

This paper proposes a meta-model-based parametric Historic Building Information Modelling (HBIM) approach to preserving and renewing traditional timber dwellings, specifically focusing on traditional Bai ethnic residential architecture. The study integrates traditional architectural principles with contemporary digital construction techniques. Traditional Bai dwellings have complex timber structural and spatial characteristics with various components. Results from the application of HBIM demonstrate improved efficiency in documenting and managing structural information, facilitating the maintenance and preservation of heritage buildings. The study concludes that HBIM, supported by parametric and generative design approaches, offers significant advantages in the digital preservation of architectural heritage. This approach not only ensures the structural integrity and historical accuracy of the models but also provides a scalable solution for managing and preserving traditional dwellings in the face of modernization pressures. This research broadens the scope of parametric design within digital construction theory, particularly concerning ancient timber structures. It offers a crucial framework that can inform both future studies and practical efforts in the preservation of heritage buildings. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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25 pages, 8390 KiB

Open AccessArticle

Comparison of Simulation Methods for Glare Risk Assessment with Roller Shades

by Sichen Lu and Athanasios Tzempelikos

Buildings 2024, 14(6), 1773; https://doi.org/10.3390/buildings14061773 - 12 Jun 2024

Cited by 1 | Viewed by 1013

Abstract

Daylight discomfort glare evaluation is important when selecting shading properties. New standards recommend allowable glare frequency limits but do not specify the modeling accuracy required for annual glare risk assessment. Fast simulation tools allow users to perform hourly glare evaluations within minutes. However, [...] Read more.

Daylight discomfort glare evaluation is important when selecting shading properties. New standards recommend allowable glare frequency limits but do not specify the modeling accuracy required for annual glare risk assessment. Fast simulation tools allow users to perform hourly glare evaluations within minutes. However, reliable evaluation of glare through roller shades requires accurate modeling of their specular and diffuse transmission characteristics, affected by color, materials, and weaving technology. This study presents a systematic comparison between commonly used glare simulation methods against the “ground truth” Radiance ray-tracing tool rpict in terms of hourly daylight glare probability (DGP), hourly vertical illuminance (Ev), and annual visual discomfort frequency. The results are presented for two shade fabrics using light transmission models with and without a peak extraction algorithm (Radiance–aBSDF and Radiance–BSDF) for the specular component. The impact of sky/sun discretization on glare prediction is also discussed. The results show that the Radiance 5–Phase Method (5PM) is superior when modeling direct sunlight and DGP through shades, while other investigated methods (3–Phase Method, imageless DGP, ClimateStudio Annual Glare) are not as robust for that purpose. Users are encouraged to understand the underlying assumptions in the imageless methods to avoid errors when simulating glare, especially due to the contrast effects. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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26 pages, 35355 KiB

Open AccessArticle

Exploring the Impact of Urban Morphology on Building Energy Consumption and Outdoor Comfort: A Comparative Study in Hot-Humid Climates

by Shuyan Zhu, Chenlong Ma, Zhongping Wu, Yuqing Huang and Xiao Liu

Buildings 2024, 14(5), 1381; https://doi.org/10.3390/buildings14051381 - 11 May 2024

Cited by 1 | Viewed by 1868

Abstract

Research simultaneously examining building energy consumption and outdoor thermal comfort within urban environments remains limited. Few studies have delved into the sensitivity of design parameters based on building energy consumption and outdoor thermal comfort. The purpose of this study is to investigate the [...] Read more.

Research simultaneously examining building energy consumption and outdoor thermal comfort within urban environments remains limited. Few studies have delved into the sensitivity of design parameters based on building energy consumption and outdoor thermal comfort. The purpose of this study is to investigate the correlations between urban morphological design parameters and performance indicators, focusing on building energy consumption and outdoor thermal comfort (UTCI), across different urban block layouts in hot-humid regions, like Guangzhou. By establishing six fundamental morphological models—three individual unit layouts and three group layouts—the research explores both control and descriptive parameters through extensive simulation studies. Scatter plot visualizations provide insights into the impacts of various design parameters on energy consumption and UTCI, facilitating a comprehensive analysis of trends and quantitative relationships. Additionally, the study conducts sensitivity analyses on design parameters under different layout conditions to highlight their influences on target performance indicators. The findings reveal common trends, such as the significant impacts of plan dimensions and the Floor Area Ratio (FAR) on energy efficiency and outdoor comfort, as well as differential patterns, such as the varying sensitivities of the Shape Factor (S/V) and the Sky View Factor (SVF), across individual and collective layouts. Ultimately, this study offers a nuanced understanding of urban block morphology’s role in creating sustainable, comfortable, and energy-efficient urban environments, providing valuable guidelines for urban form design in hot-humid climates. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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20 pages, 5706 KiB

Open AccessArticle

Assessment of Passive Solar Heating Systems’ Energy-Saving Potential across Varied Climatic Conditions: The Development of the Passive Solar Heating Indicator (PSHI)

by Wensheng Mo, Gaochuan Zhang, Xingbo Yao, Qianyu Li and Bart Julien DeBacker

Buildings 2024, 14(5), 1364; https://doi.org/10.3390/buildings14051364 - 10 May 2024

Viewed by 947

Abstract

This study aims to evaluate the energy-saving potential of passive solar heating systems in diverse global climates and introduce a new indicator, the passive solar heating indicator (PSHI), to enhance the efficiency of building designs. By collecting climate data from 600 cities worldwide [...] Read more.

This study aims to evaluate the energy-saving potential of passive solar heating systems in diverse global climates and introduce a new indicator, the passive solar heating indicator (PSHI), to enhance the efficiency of building designs. By collecting climate data from 600 cities worldwide through a simulation model, the present study employs polynomial regression to analyze the impact of outdoor temperature and solar radiation intensity on building energy savings. It also uses K-means cluster analysis to scientifically categorize cities based on their energy-saving potential. The findings underscore the benefits of both direct and indirect solar heating strategies in different climates. Significantly, the PSHI shows superior predictive accuracy and applicability over traditional indices, such as the irradiation temperature difference ratio (ITR) and the irradiation degree hour ratio (C-IDHR), especially when outdoor temperatures are close to indoor design temperatures. Moreover, the application of a cluster analysis provides hierarchical guidance on passive heating designs globally, paving the way for more accurate and customized energy-efficient building strategies. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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16 pages, 6757 KiB

Open AccessArticle

Optimizing the Return Vent Height for Improved Performance in Stratified Air Distribution Systems

by Danping Qiao, Shihai Wu, Nan Zhang and Chao Qin

Buildings 2024, 14(4), 1008; https://doi.org/10.3390/buildings14041008 - 5 Apr 2024

Viewed by 853

Abstract

One of the factors that strongly impacts the efficacy of stratified air distribution (STRAD) systems is the return vent height (H), for which different studies have yielded different suggested values. This theoretical research uses a displacement ventilation (DV) system as an [...] Read more.

One of the factors that strongly impacts the efficacy of stratified air distribution (STRAD) systems is the return vent height (H), for which different studies have yielded different suggested values. This theoretical research uses a displacement ventilation (DV) system as an example to examine how the H affects the efficacy of STRAD systems through analysis of the trade-offs between the cost of the vertical temperature gradient and the benefits of energy reduction. The key results are as follows: (a) The energy savings due to a lower H are smaller than the cost of the vertical temperature gradient for all STRAD systems. (b) With a supply temperature (T_s) set at 18 °C, elevated return vent positions can result in excessively cooled areas, while extremely low vent positions create a temperature gradient exceeding 3 °C between the head and ankles. (c) The TOPSIS methodology reveals that the optimal H value lies in the range of 1.5–2.3 m when T_s is 18 °C. (d) When adjusting the T_s value to achieve thermal neutrality, 2.3 m is identified as the optimal H value, demonstrating superior performance over the 1.5 m to 2.3 m range at 18 °C T_s. These findings highlight the benefit of a higher H for STRAD systems and the significance of configuring ventilation systems for thermal neutrality. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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23 pages, 8954 KiB

Open AccessArticle

Evaluation of Design Parameters for Daylighting Performance in Secondary School Classrooms Based on Field Measurements and Physical Simulations: A Case Study of Secondary School Classrooms in Guangzhou

by Jianhe Luo, Gaoliang Yan, Lihua Zhao, Xue Zhong and Xinyu Su

Buildings 2024, 14(3), 637; https://doi.org/10.3390/buildings14030637 - 28 Feb 2024

Cited by 2 | Viewed by 2222

Abstract

The quality of natural lighting within secondary school classrooms can significantly affect the physical and mental well-being of both teachers and students. While numerous studies have explored various aspects of daylighting performance and its related factors, there is no universal standard for predicting [...] Read more.

The quality of natural lighting within secondary school classrooms can significantly affect the physical and mental well-being of both teachers and students. While numerous studies have explored various aspects of daylighting performance and its related factors, there is no universal standard for predicting and optimizing daylighting performance from a design perspective. In this study, a method was developed that combines measurements and simulations to enhance the design parameters associated with daylighting performance. This approach facilitates the determination of precise ranges for multiple design parameters and allows for the efficient attainment of optimal daylighting performance. Daylight glare probability (DGP), point-in-time illuminance (PIT), daylight factor (DF), and lighting energy consumption were simulated based on existing control parameters of operational classrooms. The simulation results were then validated using field measurements. Genetic algorithms (GAs) were employed to optimize the control parameters, yielding a set of optimal solutions for improving daylight performance. The differences between daylighting performance indicators corresponding to the optimal solution set and those of the basic model were compared to test the performance of the optimized parameters. The proposed method is a robust process for optimizing daylight design parameters based on GAs, which not only enhances daylighting performance but also offers scientifically grounded guidelines for the design phase. It is a valuable framework for creating healthier and more productive educational environments within secondary school classrooms. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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15 pages, 2378 KiB

Open AccessArticle

Research on Energy Consumption Prediction Models for High-Rise Hotels in Guangzhou, Based on Different Machine Learning Algorithms

by Jin Zhang, Chuyan Yuan, Junyi Yang and Lihua Zhao

Buildings 2024, 14(2), 356; https://doi.org/10.3390/buildings14020356 - 28 Jan 2024

Cited by 4 | Viewed by 1410

Abstract

With the advancement of information technology, energy consumption prediction models are widely used for various types of buildings (office, residential, and commercial buildings) as guidance during the design and management stages. This article will establish an efficient building energy consumption prediction model for [...] Read more.

With the advancement of information technology, energy consumption prediction models are widely used for various types of buildings (office, residential, and commercial buildings) as guidance during the design and management stages. This article will establish an efficient building energy consumption prediction model for hotel buildings. To achieve this, we collected 78 architectural drawings of high-rise hotel buildings to establish 6 kinds of typical energy consumption models in 2 standard floor layouts and 3 public area levels. Then, on this basis, we used the total energy consumption calculated by EnergyPlus as an indicator to conduct sensitivity analysis on geometric feature parameters, internal heat source parameters, and thermal parameters, respectively. Finally, we generated a building database with 5000 samples through the R programming language to calculate and verify the energy consumption. As a result, it was proved that the energy consumption of hotel buildings can be predicted accurately, and that quadratic polynomial regression, with the best accuracy and stability, is the most suitable optimization model for hotel energy consumption prediction in Guangzhou. These conclusions provide a good theoretical basis for the analysis, prediction, and optimization of energy consumption in high-rise hotel buildings in the future. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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38 pages, 10164 KiB

Open AccessArticle

Data Center Energy Evaluation Tool Development and Analysis of Power Usage Effectiveness with Different Economizer Types in Various Climate Zones

by Ji Hye Kim, Dae Uk Shin and Heegang Kim

Buildings 2024, 14(1), 299; https://doi.org/10.3390/buildings14010299 - 22 Jan 2024

Viewed by 1846

Abstract

Data centers are energy-intensive facilities, with over 95% of their total cooling load attributed to the heat generated by information technology equipment (ITE). Various energy-saving techniques have been employed to enhance data center efficiency and to reduce power usage effectiveness (PUE). Among these, [...] Read more.

Data centers are energy-intensive facilities, with over 95% of their total cooling load attributed to the heat generated by information technology equipment (ITE). Various energy-saving techniques have been employed to enhance data center efficiency and to reduce power usage effectiveness (PUE). Among these, economizers using outdoor air for cooling are the most effective for addressing year-round cooling demands. Despite the simplicity of the load composition, analyzing data center cooling systems involves dynamic considerations, such as weather conditions, system conditions, and economizer control. A PUE interpretation tool was specifically developed for use in data centers, aimed at addressing the simplicity of data center loads and the complexity of system analysis. The tool was verified through a comparison with results from DesignBuilder implementing the EnergyPlus algorithm. Using the developed tool, a comparative analysis of economizer strategies based on the PUE distribution was conducted, with the aim of reducing the PUE of data centers across various climatic zones. The inclusion of evaporative cooling (EC) further improved cooling efficiency, leading to reductions in PUE by approximately 0.02 to 0.05 in dry zones. Additionally, wet zones exhibited PUE reductions, ranging from approximately 0.03 to 0.07, with the implementation of indirect air-side economizer (IASE). Sensitivity and uncertainty analysis were further conducted. The computer room air handler (CRAH) supply temperature and CRAH temperature difference were the most influential factors affecting the annual PUE. For the direct air-side economizer (DASE) and DASE + EC systems, higher PUE uncertainty was observed in zones 1B, 3B, 4B, and 5B, showing ranges of 1.17–1.39 and 1.15–1.17, respectively. In the case of the IASE and IASE + EC systems, higher PUE uncertainty was noted in zones 0A, 0B, 1A, 1B, and 2A, with ranges of 1.22–1.43 and 1.17–1.43, respectively. The distinctive innovation of the tool developed in this study is characterized by its integration of specific features unique to data centers. It streamlines the computation of cooling loads, thus minimizing the burden of input, and delivers energy consumption data for data center cooling systems with a level of precision comparable to that of commercial dynamic energy analysis tools. It provides data center engineers with a valuable resource to identify optimal alternatives and system design conditions for data centers. This empowers them to make informed decisions based on energy efficiency enhancements, thereby strengthening their ability to improve energy efficiency. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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23 pages, 9370 KiB

Open AccessArticle

Urban Building Energy Modeling with Parameterized Geometry and Detailed Thermal Zones for Complex Building Types

by Hongyan Xi, Qilin Zhang, Zhiyi Ren, Guangchen Li and Yixing Chen

Buildings 2023, 13(11), 2675; https://doi.org/10.3390/buildings13112675 - 24 Oct 2023

Cited by 2 | Viewed by 1575

Abstract

Urban building energy modeling (UBEM) has attracted wide attention to the requirement for global carbon emission reduction. This paper presents a UBEM tool, AutoBPS-Param, to generate building energy models (BEMs) with parameterized geometry and detailed thermal zones, especially for complex building types, considering [...] Read more.

Urban building energy modeling (UBEM) has attracted wide attention to the requirement for global carbon emission reduction. This paper presents a UBEM tool, AutoBPS-Param, to generate building energy models (BEMs) with parameterized geometry and detailed thermal zones, especially for complex building types, considering the shading effect from surrounding buildings simultaneously. Three building number scales and four scenarios were analyzed in the hotel-related buildings in Changsha, China. For the prototype modeling of Scenario 1, eighteen prototype building energy models for six building types in three vintages were created, and their simulation results were aggregated based on their representative floor areas. For AutoBPS-Param of Scenario 4, the method created one EnergyPlus (Version: 9.3.0) model for each building. The geometry of the prototype model was scaled and modified based on the target building’s length, width, and number of stories. The surrounding buildings were also added to the AutoBPS-Param simulation to better capture the urban dynamic impact. The results showed that the annual electricity and natural gas energy use intensity (EUI) of the pre-2005 HotelOffice prototype model was 172.25 and 140.45 kWh/m². In contrast, with the AutoBPS-Param method, the annual electricity EUIs of 71 HotelOffice buildings constructed before 2005 ranged from 159.51 to 213.58 kWh/m² with an average of 173.14 kWh/m², and the annual gas EUIs ranged from 68.02 to 229.12 kWh/m² with an average of 108.89 kWh/m². The proposed method can better capture the diversity of urban building energy consumption. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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26 pages, 25415 KiB

Open AccessArticle

Evaluation of an Existing Validated Emirati House versus a New Parametric Design Based on the Local Social Environment through the Application of Advanced Tools

by Lindita Bande, Yosan Asmelash, Anwar Ahmad, Aybin Cyiza and Jose Berengueres

Buildings 2023, 13(10), 2627; https://doi.org/10.3390/buildings13102627 - 18 Oct 2023

Cited by 2 | Viewed by 1650

Abstract

Al Ain is the second-largest city in the Abu Dhabi Emirate, and the population of Al Ain has been growing rapidly for the last 50 years. The residential units in Al Ain are arranged using different concepts in relation to household social and [...] Read more.

Al Ain is the second-largest city in the Abu Dhabi Emirate, and the population of Al Ain has been growing rapidly for the last 50 years. The residential units in Al Ain are arranged using different concepts in relation to household social and economic behaviors. While Al Ain city has mostly low-rise and mid-rise residential buildings, the local population tends to live in traditional low-rise villas. The governmental statistics show a high ratio of energy consumption in the form of electricity for cooling loads, and it is estimated to increase with the rapid growth of the population. In this context, it is important to investigate different strategies to control the energy consumption of residential buildings. The purpose of this study was to assess the energy usage and demand of an existing villa in Al Ain and see how a newer design approach can help to reduce the annual energy consumption of households. The newer design option is based on a parametric (application of a parametric façade) approach whilst taking sustainable design approaches. The newer design options are compared to the existing villa and a traditional extension villa attached to the existing villa in terms of annual electricity consumption. The process of design and energy modeling of all cases used the Estidama baseline standards for technical and construction specifications. The process started with selecting an existing six-bedroom villa in Al Ain. Moreover, the selected villa had a planned extension to be constructed in the future. Then, an annual energy model of the existing villa was created in Rhinoceros 7.0 with the Grasshopper 3D plug-in. The energy results were validated against the real energy bills of the villa. Once the energy model was validated, the newer options of the design were modeled, and the projected energy consumption was compared with the base case results to see how energy-efficient the newer model would be. The research shows that it is possible to save up to 60% of electricity annually by carefully selecting a sustainable design in the early stages. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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17 pages, 4544 KiB

Open AccessArticle

Building Performance under Untypical Weather Conditions: A 40-Year Study of Hong Kong

by Siwei Lou, Zhengjie Peng, Jilong Cai, Yukai Zou and Yu Huang

Buildings 2023, 13(10), 2587; https://doi.org/10.3390/buildings13102587 - 13 Oct 2023

Cited by 5 | Viewed by 1042

Abstract

As a common engineering practice, the buildings are usually evaluated under the Typical Meteorological Year (TMY), which represents the common weather situation. The warm and cool conditions, however, can affect the building performance considerably, yet building performances under such conditions cannot fully be [...] Read more.

As a common engineering practice, the buildings are usually evaluated under the Typical Meteorological Year (TMY), which represents the common weather situation. The warm and cool conditions, however, can affect the building performance considerably, yet building performances under such conditions cannot fully be given by the conventional TMY. This paper gives approaches to constructing the weather data that represents several warm and cool conditions and compares their differences by studying the cumulative cooling demands of a typical building in a hot and humid climate. Apart from the Extreme Weather Year (EWY), the Near-Extreme Weather Year (NEWY) and Common warm/cool Years (CY) data are proposed according to the occurrence distributions of the weather over the long term. It was found that the cooling demands of NEWY and EWY differ by 4.8% from the cooling needs of TMY. The difference between the cooling demands of NEWY and CY for most calendar months can be 20% and 15%, respectively. For the hot months, the cooling demands under NEWY and CY take 7.4–11.6% and 2.3–5.6% differences from those under TMY. The uncertainties of building performance due to the ever-changing weather conditions can be essential to the robustness of building performance evaluations. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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20 pages, 5464 KiB

Open AccessArticle

AppSimV: A Cyber–Physical Simulation and Verification Platform for Software Applications of Intelligent Buildings

by Haining Jia, Qiliang Yang, Ziyan Jiang, Wenjie Chen and Qizhen Zhou

Buildings 2023, 13(10), 2404; https://doi.org/10.3390/buildings13102404 - 22 Sep 2023

Cited by 1 | Viewed by 935

Abstract

Testing and verifying applications (Apps) are essential for a software-driven intelligent building system. Traditional methods connect App programs to hardware devices for debugging and testing on the engineering site. However, App bugs can hardly be found out before they are being deployed and [...] Read more.

Testing and verifying applications (Apps) are essential for a software-driven intelligent building system. Traditional methods connect App programs to hardware devices for debugging and testing on the engineering site. However, App bugs can hardly be found out before they are being deployed and thus always require an extended debugging cycle. To address this issue, we propose a cyber–physical simulation and verification platform named AppSimV, which enables the testing and verification of Apps in a mimic real scene. Taking swarm intelligence building as an example, this paper focuses on the cyber–physical architecture of AppSimV and its implementation mechanisms, including the standardized encapsulation of software components for the building physics model, a multitask scheduling simulation engine, a cyber–physical interaction interface, and the visual monitoring of the simulation process. The implementation mechanisms not only accurately simulate actual engineering scenarios but also facilitate the early detection and correction of issues that may arise during the App’s runtime, thus reducing the debugging time required for the App. With 1200 intelligent physical nodes connected in a swarm hardware system, AppSimV was validated by conducting the strict testing and verification of a set of Apps for an intelligent building. The results show that AppSimV is sound and reliable. Full article

(This article belongs to the Special Issue Advances in Building Performance Simulation and Building Energy Consumption Analysis)

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