Building Performance Research Articles

Thermal and energy efficiency in 3D-printed buildings: Review of geometric design, materials and printing processes

Applying 3D printing in construction is a promising, sustainable alternative to conventional methods. However, the thermal and energy performance of 3D-printed buildings remains underexplored, particularly regarding the interactions between geometric design, material selection, and printing parameters. This review addresses this gap by critically examining how the main steps of the printing process impact the thermal efficiency of 3D-printed buildings. Key findings indicate that material development needs to focus on mixes that balance thermal properties,printability,and structural integrity. The review demonstrates how optimising wall cross-sections and cavity shapes can reduce thermal conductivity and enhance energy efficiency. Innovative geometric designs, such as cellular and honeycomb structures, have shown improvements in thermal insulation. Optimising printing parameters, such as extrusion rate and nozzle travel speed, is crucial to minimising thermal bridges and reducing material anisotropy. Advanced numerical models, validated by experimental data and incorporating factors like inhomogeneous porosity, anisotropy, and surface roughness, are essential for accurately predicting the thermal behaviour of 3D-printed structures. The review underscores the need for large-scale, long-term performance studies of 3D-printed buildings under diverse climatic conditions. Additionally, developing standardised fabrication protocols and testing methods is essential for ensuring consistent quality and broader adoption. Addressing these research gaps is crucial to fully realising the potential of 3D printing in sustainable construction and accelerating the adoption of additive manufacturing in the construction sector.

Actions to improve energy efficiency on the example of selected historic buildings in Poland in the context of European Union guidelines

The article presents, in the context of the guidelines of the "Long-Term Strategy for Renovation of Buildings" valid until 2050, examples of renovations of historic buildings carried out in Poland in 2018-2021, which serve as public facilities. They were designed and constructed in a manner consistent with the guidelines for the transformation of a climate-neutral economy, which stem from Article 2a of Directive 2010/31/EU of the European Parliament and of the Council of May 19, 2010. The purpose of the article is a comparative analysis of selected Polish examples of revaluation of public buildings from the point of view of the Architecture of these objects. These are: the Wagner Villa in Kostrzyn on Oder, the railway station in Białystok, the Teodor Sixt Villa in Bielsko-Biała, the office building of the Forestry Commission in Elbląg, the building of the Savings Bank in Ropczyce and the former granary in Żukowo. Also cited are the current financial tools available and the basic measures needed to ensure high energy efficiency and low-carbon performance of public buildings in the run up to 2050.

Enhancing Vendor Management for Successful IT Project Delivery

Effective vendor management plays a critical role in ensuring the successful delivery of IT projects. In today’s complex business environment, organizations often rely on third-party vendors for specialized services, technology, and support. However, the collaboration between organizations and vendors presents challenges related to communication, quality control, cost management, and timely delivery. Enhancing vendor management practices can address these issues and lead to improved project outcomes. This paper explores strategies to optimize vendor management for IT project delivery. Key areas of focus include establishing clear contractual agreements, fostering transparent communication, and aligning vendor performance with project goals. Additionally, it examines the role of relationship building and regular performance evaluations to maintain high standards throughout the project lifecycle. By implementing risk management techniques and utilizing performance metrics, organizations can mitigate potential issues and ensure vendors meet their deliverables on time and within budget. The study also highlights the growing importance of technology in vendor management, such as the use of automated tools for monitoring vendor performance and improving collaboration. In conclusion, strengthening vendor management practices can lead to increased efficiency, reduced project delays, and enhanced overall success in IT projects, making it a crucial aspect for organizations aiming to deliver high-quality outcomes in today’s technology-driven landscape.

The role of passive, active, and operational parameters in the relationship between urban heat island effect (UHI) and building energy consumption

The energy performance of buildings located in urban areas is strongly influenced by the UHI phenomenon, which usually leads to higher cooling energy consumption and lower heating energy consumption. Despite the known effects of UHI on building energy consumption, there is a lack of detailed knowledge on the role of building design and operational parameters in determining the effects of UHI on building energy use. To address this knowledge gap, this study analyzes the impacts of UHI on annual, heating, and cooling energy consumption of 16 prototype buildings located in 16 climate zones in the United States. The objective is to determine the relative relevance of building types (e.g., residential, commercial, healthcare facilities etc.), occupancy parameters (e.g., occupancy schedule) and the Heating, Ventilation and Air Conditioning (HVAC) systems in governing the impact of UHI on the building energy use matrices. Additionally, the thermal properties of the building envelope were evaluated to determine their relative importance in mitigating the effects of UHI on building energy performance. We found that, among the studies building types, while the cooling energy use of restaurant and outpatient healthcare buildings was most affected by UHI (higher cooling energy demands), the outpatient healthcare buildings were most impacted by UHI in terms of their heating energy use (lower heating energy use). The selection of HVAC systems type was found to have negligible influence on the energy impacts of UHI. Lastly, with regard to the thermal properties of the building envelope, window insulation was noted to be the most influential thermal property, followed by roof and wall insulation. Also, the role of insulation as well as other thermal properties was higher in the context of UHI’s impact on heating energy consumption as compared to cooling energy consumption. Not only are the results of this study useful for urban planning purposes to determine the vulnerability of different buildings to UHI, but they also are beneficial to UHI-resilient building designs.

Practical solutions for global buckling analysis in tall buildings: classic sandwich continuous model

Static stability analysis of global buckling and critical load ratio calculation are among the fundamental and most important parameters for structural analysis and design in numerous engineering applications across various fields. Particularly in the field of structural engineering, the critical load ratio is a parameter that determines the overall performance of tall buildings; however, due to the complexity of coupled differential equations with variable coefficients associated with different classical continuous models, its analysis has not been widespread, and only specific cases have been solved. This article utilizes the classic sandwich beam, widely studied in the literature, to propose an analytical solution and a generalized numerical solution to address the elastic buckling problem with applications in tall building stability analysis. The analytical solutions are applicable to uniform structures and consider point, uniform, and variable compression loads along their length that can be expressed through polynomial functions. The generalized numerical solution addresses the general case of structures with uniform or variable properties. Numerical applications and parametric analyses show excellent agreement between the results of the proposed methods and those of one-dimensional finite element methods. The influences of key parameters on the behavior of the eigenvalue associated with global buckling analysis are analyzed, and graphs and tables are proposed for direct practical application by engineers. Due to their mathematical formulation and excellent precision in results, the proposed methods can be safely used in the preliminary and final analysis of tall buildings and can be easily adapted to other engineering fields.

High-resolution regional climate–CFD integrated modelling to inform climate responsive design of northern buildings in a changing climate

In permafrost regions, where climate change poses significant challenges to infrastructure stability, understanding the thermal behaviour of buildings is crucial. This study conducts a detailed investigation into the thermal performance of elevated buildings in permafrost regions within the context of a changing climate. High-resolution regional climate simulation-informed computational fluid dynamics (CFD) models were developed for northern buildings. The findings indicate that the presence of elevated buildings can disrupt the permafrost’s natural thermal equilibrium in the future. This disturbance can extend vertically and horizontally, potentially leading to altered ground temperature gradients and increased air and ground temperatures by 4.25% and 3.85%, respectively. The research findings also highlight a 12.75% reduction in wind speed beneath the study building when transitioning from the local scale (i.e., single-building) to the neighbourhood scale (i.e. with surrounding buildings). These results underscore the critical significance of exploring the neighbourhood scale in building design and planning within permafrost regions, emphasizing the need for comprehensive assessment tools to inform effective strategies and decisions. The holistic approach adopted in this study, sets out a clear vision to guide northern adaptation initiatives that address some of the climate change issues in the buildings’ design by utilizing integrated climate system-built environment modelling.

Thermal Performance of Lightweight Earth: From Prediction to Optimization through Multiscale Modeling

This study investigates the prediction of the thermal conductivity of lightweight earth and raw earth blocks incorporating plant aggregates. Given the high variability of raw materials, it is not currently possible to predict the thermal performance of this type of material before sample production. This is a major obstacle to using these eco-materials, although their use is widely encouraged to improve building performance under evolving regulatory frameworks such as The French RE2020 standard. The incorporation of plant aggregates into earth-based materials offers improved insulation properties without compromising their mechanical integrity, positioning them as promising sustainable alternatives. Mean-field homogenization techniques, including the Mori-Tanaka as well as double inclusion models, are used to develop predictive tools for thermal behavior, using rigorously selected experimental data. The selected methods are particularly relevant. The Mori-Tanaka model appears to be better suited when the proportion of aggregates is limited, whereas the double inclusion scheme proves its worth when a higher proportion of aggregates is incorporated. This study emphasizes the influence of aggregate types and processing methods on thermal conductivity, highlighting the need for precise formulation and processing techniques to optimize performance. This paper demonstrates the relevance of the applied homogenization techniques applied. It enables the real morphology of the materials studied, such as aggregate shape and intrinsic cracking, to be taken into account. It contributes to the advancement of eco-material modeling toward predictive digital twins, with the goal of simulating and optimizing complex material behavior under various environmental conditions.

Balance point concentration: An indicator for classroom performance against outdoor PM2.5

Indoor air quality significantly affects occupants' health, making it crucial to evaluate a building's vulnerability to air pollution. In this study, 17 classrooms in urban areas of Seoul, Korea were monitored to determine how long a clean air environment can be maintained. We propose the balance point concentration (BPC) as the threshold value of outdoor PM2.5 concentration that can maintain PM2.5 in classrooms at the target value of 15 μg/m3. Based on the mass-balance equation, BPC is a comprehensive indicator that considers PM2.5 that can penetrate through building envelope, be generated from indoor activities, and be removed by an air purification system. For non-occupied classrooms, the BPC ranged from 20.6 to 34.3 μg/m3. We find that better airtightness reduced air pollution in buildings. However, due to students' activities, BPC decreased to 7.6–12.0 μg/m3. Lastly, in classrooms with mechanical ventilation systems in operation, the BPC ranged from 24.3 to 34.2 μg/m3, showing improved performance. Under such conditions, students can spend more than 88 % of the year in a classroom environment with clean air. In areas with low outdoor pollution levels, satisfaction can be even higher. Evaluating buildings performance using BPC allows for a more intuitive and clear assessment compared to existing indicators. When outdoor concentrations exceed BPC, additional air quality management in the classroom is necessary. This can be widely utilized when planning improvements to the environment or the operation of air purification system.

Advanced Decision- Making Framework for Sustainable Energy Retrofit of Existing Commercial Office Buildings

In the background of rising global initiatives to combat climate change and promote better energy management, retrofitting of current structures has become a major strategy. This abstract and literature review aims at presenting a full review of a decision-making approach that can be used in choosing sustainable options for energy retrofitting. This particular framework is designed to help guide retrofit decision-making due to the many issues that surround the process by providing an economic as well as an environmental and social context. Energy retrofitting means improving the existing structure or complex to decrease its energy intensity and have a negative impact on the environment. As stated earlier, it is a critical process for attaining sustainability goals and advancing the performance of buildings. But the decision on which retrofit measures should be implemented can be rather difficult because of the availability of a vast number of technologies and because more factors must be considered, such as cost and energy savings. The decision-making framework provided in this article aims at categorizing retrofit selection into this list of features and views the current article as a way of making the process more efficient. It encompasses the life-cycle cost analysis (LCCA), the economic valuation, and the multi-criteria decision analysis tools and criteria. These tools facilitate the evaluation of financial viability, the advantages of climatically retrofitting, and the environmental effects of distinct retrofitting choices. The above-mentioned framework is exemplified with a case study of an office building retrofit project. The following case includes an example of the application of the mentioned framework and illustrates the explanation of how it helps to make decisions. Due to the consideration of costs, energy, and environmental performance, the framework enables the stakeholders to choose appropriate retrofit measures. Other than the case study, the framework also focuses on the need to establish a sustainable energy retrofit DSS. Thus, the DSS supplements collected data on building performance, retrofit technologies, and economic aspects, which can be accessed by the stakeholders in real-time and with built-in facilities for scenario analysis. This system improves decision-making since retrofit results can be monitored and evaluated frequently. Both tools and strategies for the decision-making of sustainable energy retrofits bring a logical and systematic approach aimed at neutralizing the decision-making challenges related to retrofit selection. By applying economic, environmental, and social factors in the decision-making process, the framework assists the stakeholders in reaching energy efficiency and sustainability goals. The development of another strong decision-support system also improves the working of the framework and checks that retrofit projects are done efficiently and are strategic to the general goal of sustainable development.

Importance of Window Installation in Residential Building Envelopes Having Continuous External Insulation in Order to Realize Energy Efficiency

Residential buildings are one of the prime candidates in the United States for reducing energy consumption. Continuous exterior insulation (CEI) is being used increasingly often in residential buildings to improve energy efficiency. Windows constitute 15–40% of a building envelope and are the weakest component in energy performance. The installation of windows in walls with CEI has not been well evaluated. We identified four cases of installing windows in walls with CEI of 25–76 mm (1–3 in.) thickness and analyzed the energy loss between the window and wall interface (flanking loss), structural issues, air leakage, and moisture penetration. Thermal analysis showed that the insulation value (RSI) of the 305 mm (12 in.) perimeter wall surrounding a window decreased by 7.6–34.5% in the four cases when compared with the RSI of the wall without the window. A window installation method is proposed to address the issues likely to occur with installation methods currently being used in the field. An out-of-the-box installation system was also designed to achieve a better thermal performance, cost effectiveness, and structural performance in high-performance residential buildings.

Practice-oriented numerical model for seismic response of cold-formed steel-framed mid-rise buildings

Cold-formed steel (CFS) framed buildings are becoming increasingly common, notably in the high seismic regions of the United States (US). However, research to understand the seismic performance of CFS-framed buildings specifically using large-scale (building-level) specimens has begun only recently. Therefore, efforts to validate and improve numerical modeling of whole building systems have been limited due to this lack of experimental data. A recently completed experimental program, conducted at the Large High-Performance Outdoor Shake Table at the University of California, San Diego, involved earthquake testing of a full-scale 6-story CFS-framed building. The test building adopted an assembly of continuous tie-rod and built-up compression stud pack at the ends of individual shear walls to resist seismic overturning moment and uplift forces within the building. The objective of this paper is to present a practice-oriented phenomenological finite element modeling approach intended for design engineers and compare the predictions from this model against the measured seismic response of the 6-story building. The model aims to provide a robust, yet computationally efficient approach, with minimal degrees-of-freedom, while also capturing the salient features of seismic response of mid-rise CFS-framed buildings suitable for nonlinear time history analyses-based design. The building model, developed within the OpenSeesPy finite element platform, includes the shear walls and gravity walls as well as the lateral strength and stiffness contribution from exterior and interior gypsum sheathing. The continuous tie-rod system is also modeled to capture the cumulative floor displacements caused by the axial elongation in the steel rods. The effect of built-up compression stud packs on the lateral behavior of a shear wall was estimated using available experimental data and a detailed numerical model of an isolated shear wall, then subsequently incorporated in the nonlinear hysteretic material model. The numerical model captured the natural frequencies of the translation modes of the building in its undamaged state with <3% error. It also predicted the peak roof drift ratio within an error of 0.03% drift ratio under the design earthquake event. These results provide confidence in the proposed numerical modeling approach as a tool for seismic response prediction of mid-rise CFS-framed buildings with similar structural detailing features.

Characterization and Energy Performance of WO3 Doped and Undoped Photochromic Films

When exposed to light sources, photochromic (PC) materials change their optical properties and can lessen the transmission of UV and infrared radiation. This results in optimal thermal comfort and a pleasing visual contrast between the internal and external settings. This study uses computer modeling to analyze the annual energy usage in a home with natural ventilation in order to compare the effectiveness of photochromic films with commercial glass. The study is carried out using the EnergyPlus program in the cities of São Carlos and Cuiabá ‐ Brazil. Experiments and numerical simulations with data from doped and undoped tungsten trioxide (WO3) PC films are used in the study. Given the rise in energy usage and the pursuit of thermal comfort, this method is essential for assessing the thermal performance of buildings. Evaluations included a comparison of air conditioner performance and energy savings analysis, which leads to a noteworthy annual reduction in energy usage of up to 216.55 kWh and a 40% improvement in visual comfort. It is determined that PC film's dynamic behavior is the best option for comfort in terms of heat, illumination, and visual comfort.

Seismic Performance Prediction of RC, BRB and SDOF Structures Using Deep Learning and the Intensity Measure INp

The motivation for using artificial neural networks in this study stems from their computational efficiency and ability to model complex, high-level abstractions. Deep learning models were utilized to predict the structural responses of reinforced concrete (RC) buildings subjected to earthquakes. For this aim, the dataset for training and evaluation was derived from complex computational dynamic analyses, which involved scaling real ground motion records at different intensity levels (spectral acceleration Sa(T1) and the recently proposed INp). The results, specifically the maximum interstory drifts, were characterized for the output neurons in terms of their corresponding statistical parameters: mean, median, and standard deviation; while two input variables (fundamental period and earthquake intensity) were used in the neural networks to represent buildings and seismic risk. To validate deep learning as a robust tool for seismic predesign and rapid estimation, a prediction model was developed to assess the seismic performance of a complex RC building with buckling restrained braces (RC-BRBs). Additionally, other deep learning models were explored to predict ductility and hysteretic energy in nonlinear single degree of freedom (SDOF) systems. The findings demonstrated that increasing the number of hidden layers generally reduces prediction error, although an excessive number can lead to overfitting.

Automated Defect Detection on Dry-Hanging Stone Curtain Walls through Colored Point Clouds

Stone curtain walls are widely used in contemporary architectures; however, their regular inspection is always labor-intensive, time-consuming, and hazardous due to the complex and enclosed spatial structure of these high-rise building enclosures. To address this issue, this study proposes an automated and novel inspection method, which is composed of the following three steps: First, we utilize 3D laser scanning technology to capture colored point cloud data of the stone curtain wall system; subsequently, by extracting and processing the integration of color and depth information, the stone panels and end sealants are precisely segmented; finally, various defects, such as cracks, unevenness, and irregularities, are automatically identified through artificial intelligence algorithms in a timely manner. To validate the proposed method, an on-site experiment was carried out to demonstrate the effectiveness in detecting multiple defects concurrently on stone curtain walls. The experimental results showed that our proposed method could provide a non-contact and automated inspection alternative for all the stone curtain walls with a high accuracy of anomaly detection, facilitating rational maintenance plans and strategies to ensure the safety and performance of these modern building enclosures.

Properties of foam concrete containing phase change material impregnated pumice

Energy consumption rises as a result of numerous electrical devices used to maintain thermal comfort of interior building areas. Using building materials with low thermal conductivity and density as well as an effective thermal energy storage plan can help to mitigate this. In order to enhance thermal performance of building, phase change material (PCM) was incorporated to foam concrete mixture in this study. Capric acid (CA)-palmitic acid (PA) eutectic mixture was prepared and impregnated with pumice (50 % by weight), a light and porous material. DSC results indicated that pumice/CA-PA composite exhibited a melting temperature of 22.84˚C and a freezing temperature of 20.85˚C, with corresponding enthalpy values for melting and freezing determined to be 85.4 J/g and 85.1 J/g, respectively. TGA analyses demonstrated that operational temperature of pumice/CA-PA composite was significantly below its thermal degradation temperature (194˚C). The prepared pumice/CA-PA composites were replaced with silica aggregate at different rates and incorporated in foam concrete mixture. Porosity and water absorption values rose as pumice/PCM content increased, yet there was a 7.2–41.1 % drop in dry unit weight when compared to reference. Compressive strength also showed a linear decrease and the lowest compressive strength value was recorded as 4.71 MPa in the presence of 40 % pumice/PCM. Thermal conductivity dropped from 0.487 W/mK to 0.167 W/mK, suggesting that foam concrete samples that were produced are all suitable as insulation materials. In peak solar radiation hours, PCM-impregnated pumice foam concrete (PFC) provided about 11.8 % and 8.72 % surface and room center temperatures compared to that of the reference in maximum case. PFC with PCM provided 6.54 % warmer surface temperature in cold weather. PFC-PCM can provide a cooler indoor temperature during peak temperature hours. Therefore, it may have a great potential to decrease the cooling load of a building.

Auto-WoodSDA: A scalable end-to-end automation framework to perform probabilistic seismic risk and recovery assessment of new residential woodframe buildings

The seismic performance of residential woodframe buildings has a widespread and lasting impact on the socioeconomic vitality of a community. To enable efficient seismic risk and resilience assessment, a comprehensive framework that is rooted in performance-based earthquake engineering (PBEE) methodology is proposed. The framework is formulated as a computational workflow which is operationalized as an automation program dubbed “Auto-WoodSDA”. The end-to-end platform is developed to perform four major tasks: (1) generate code-compliant seismic design, (2) create numerical models, (3) perform nonlinear analyses, and (4) assess earthquake-induced financial losses and functional recovery time. Given the user inputs, Auto-WoodSDA sequentially executes the four tasks without intermediate human intervention to produce seismic performance metrics such as the expected annual loss. It is presented as a ready-to-implement platform that is computationally efficient and scalable in performing large-scale seismic risk and resilience assessment. An example building from the existing literature is used to demonstrate the key features of the automation framework and verify the results. The results underscore the ability of the AutoWoodSDA computational workflow to automate the generation of reliable new code-compliant woodframe building designs, perform nonlinear analysis, and assess the earthquake-induced impacts using PBEE principles.

BIM and virtual reality for pre-design evaluation of building performance

ABSTRACT This study aimed to assess the extent to which design errors that cause construction performance failures in healthcare facilities, typically identified in a Post-Occupancy Evaluation (POE), can be anticipated through Pre-Design Evaluation (PDE). The methodological approach involved comparing two case studies crossing results of a POE with walkthrough, questionnaires, interview, and checklist, and a proposed PDE using a checklist and simulation with an immersive virtual reality device. An exploratory study of POE and PDE, involving user participation in two healthcare facilities in Brazil, was conducted to validate the data. Diagnostic maps were created to assess the relationship between design issues identified in both POE and PDE. The findings indicated that many problems detected in the POE could have been foreseen through the proposed PDE model, with input from a limited number of expert users. Immersive virtual reality integrated with BIM workflows facilitates communication between designer and users, guiding the development of appropriate design solutions related to sizing, space functionality, and furniture and equipment requirements. The practical implications suggest that implementing the proposed PDE in future studies can help anticipate potential performance issues in healthcare buildings, leading to resource optimization and enhanced performance in the built environment. This study demonstrates the implementation of a PDE approach based on the principles of POE, integrating both technical expertise and user perspectives. It confirms that this type of evaluation can significantly contribute to the early stages of the design process.

Effects of impact and microphone positions on heavy-weight floor impact sound pressure levels in concrete buildings

This study aims to analyze the spatial distribution of heavy-weight impact sound transmitted to a receiving room in 59 households within a concrete residential building. The performance of buildings is generally regulated by single number quantities such as L′iA,Fmax. To enhance performance, it is important to understand the effect of the impact sound pressure level at designated impact positions and microphones. Therefore, this study proposes a method to quantify the impac sound pressure level for determining L′iA,Fmax according to the impact and microphone positions. Analysis of the data revealed that significant similarities in frequency spectra were observed when generating impacts at two positions near the window, in addition to two at the area near the corridor, both of which have similar boundary conditions. The central impact position exhibited the highest contribution at 24.6%, while other positions had contributions of 18.2–19.5%. For the microphone positions, those located at the corners on either side of the window showed contributions of 22.8–23.7%, whereas the remaining positions demonstrated lower contributions of 17.3–18.5%. These results can serve as basic data for developing construction methods to reduce floor impact sound.

Designing with building-integrated photovoltaics (BIPV): A pathway to decarbonize residential buildings

The ambitious targets set for greenhouse gas emissions and energy efficiency by 2050 demand a critical increase of building renovation rates. This challenge is shared by most Western nations, including Europe and Switzerland, where the current annual renovation rate stands at a mere 0.6 %. In this context, designing renovation strategies using building integrated photovoltaic (BIPV) components as a new building material is one of the most promising ways to achieve decarbonization of the building stock in an economical and environmentally efficient manner. To this end, building design teams are key, especially in promoting BIPV-based projects to their clients and taking this approach into account from the initial design phase where pivotal decisions with significant impact are made. This article illustrates the potential impact of specific choices in renovation processes on the overall building performance, considering a Life-Cycle Analysis/Cost (LCA/LCC) and multi-criteria analysis. It uses a 1970's residential building as case study, examining different refurbishment scenarios. Findings reveal that scenarios integrating BIPV can significantly enhance energy savings, achieving up to 122 % in energy efficiency gains, and can meet the 2050 targets for cumulative energy demand (CED) and global warming potential (GWP). Additionally, the most effective BIPV scenarios demonstrate economic viability with a payback period of 14–18 years and internal rates of return (IRR) between 5.3 % and 5.9 %. These results underscore the economic and environmental benefits of BIPV in building renovations and advocate for its broader adoption to achieve national and international climate goals.

Analyzing the implementation of predictive control systems and application of stored data in non-residential buildings

In non-residential buildings, building energy management systems (BEMS) and the application of data hold significant promise in reducing energy consumption. Nevertheless, BEMS have different levels of complexity, benefit, and limitation. Despite the advanced technologies and improvements in building operation, there is a clear gap in the actual performance of buildings that has been attributed to the adoption of advanced technologies. Consequently, there is an increasing need for researchers and practitioners to study current practices in order to identify and address the challenges that compromise the core objectives of BEMS. For this reason, this paper aims to validate three research questions: (i) to examine the current state of BEMS and its functionalities; (ii) to analyze the type of control used; (iii) and to determine the availability of historical data compiled by BEMS and its application in non-residential buildings. A survey of 676 buildings and interviews with building professionals were conducted. The findings confirmed that most of the buildings applied BEMS with scheduled control. In addition, a lack of digitized data for analysis and predictions was detected. Indeed, only 0.60% of the investigated buildings implemented predictive control. Finally, using hierarchical clustering analysis, responses were grouped to analyze similarities between them. The study findings help to develop targeted actions for implementing predictive control in non-residential buildings.