Building Management Research Articles

Design and assessment of energy infrastructure in new decarbonized urban districts: A Spanish case study

New urban districts have great potential to reduce greenhouse gas emissions by electrifying energy demand in various sectors, such as transportation and buildings. This paper proposes a novel approach that combines different energy models to plan the infrastructure for supplying the energy demand of new, decarbonized, and highly electrified urban districts on a real-world scale. First, a model for energy management in buildings is used to plan and operate equipment for heating, cooling, and solar photovoltaic distributed generation. Second, a model that plans electric vehicle charging infrastructure determines the number and types of charging stations. Then, a large-scale distribution network planning model designs a cost-efficient electricity distribution grid to supply the district. A case study is presented for a new urban district in Madrid, Spain, to demonstrate how this approach can be applied to energy infrastructure planning in a real-world context. This case study presents different scenarios of energy efficiency performances in buildings and penetration levels of solar installations, electric vehicles, and heating and cooling systems. The results show that even in a high electrification scenario, improving energy efficiency in buildings through a district heating network based on heat pumps can lead to a lower peak electricity demand. This peak load reduction allows for integrating more electric vehicles, avoiding further investments in the electricity distribution network. In addition, the results confirm that a highly electrified scenario, which combines energy-efficient buildings with high integration of solar and electric vehicles, significantly reduces non-renewable energy consumption and greenhouse gas emissions.

Exploring determinants of purchase intent for chinese steel and iron goods in Batam

This study aims to investigate the underlying reasons behind the heightened purchase inclination towards imported Chinese steel and iron products within Batam City. Given that iron and steel products emerged as one of the most extensively imported categories in 2020, they serve as the primary focus of this research. Data collection was conducted through Google Forms, completed by 211 building shop owners or managers. Analysis was carried out utilizing SPSS version 26.0.0, encompassing data quality assessment, classical assumption testing, and multiple linear analysis. The findings reveal that subjective norms and perceived behavioral control significantly and positively influence the purchase intention of Chinese steel and iron products.

Heating load prediction in buildings using decision tree machine learning method

In recent years, the burgeoning imperative of energy-efficient building management practices has surged dramatically, underscoring an urgent mandate for comprehensive studies that integrate cutting-edge optimization algorithms with precise heating load forecasting techniques. These studies are not merely endeavors; they represent concerted efforts to increase building energy efficiency and address mounting concerns regarding sustainability and resource utilization. In the intricate domain of heating, ventilation, and air conditioning (HVAC) systems, energy optimization challenges are being meticulously confronted through rigorous exploration and the application of innovative problem-solving methodologies. This pioneering study introduces groundbreaking methodologies by seamlessly integrating two state-of-the-art optimization algorithms— the Red Fox Optimization and the Golden Eagle Optimizer— with the Decision Tree model. This fusion is aimed at enhancing the accuracy of heating load predictions and streamlining HVAC system optimization processes, marking a significant leap toward achieving heightened energy efficiency and operational efficacy in building management practices. The study emphasizes the significance of precise heating load prediction in advancing energy efficiency, realizing cost savings, and fostering environmental sustainability in building management. Furthermore, it delves into the multifaceted impact of various building features on heating load, encompassing variables such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. These insights furnish actionable intelligence for refined decision-making processes in both building design and operation. Based on the results, the DT single model experienced the weakest performance among the three models, with R2 = 0.975 and RMSE = 1.608. The model DTFO (DT + FOX) achieves an extraordinary R2 value of 0.996 and RMSE value of 0.961 for heating load prediction, surpassing the performance benchmarks set by other models. This achievement holds considerable promise for aiding engineers in crafting energy-efficient buildings, particularly within the swiftly evolving landscape of smart home technologies.

A Universal Biomineralization‐Like Interfacial‐Confined Strategy Enables Practicable, Meter‐Scale, Transmittance‐Adjustable, Highly‐Ordered, Photothermal‐Capable, 2D Conducting Polymers

AbstractConducting polymers (CPs) encompass various cutting‐edge fields owing to their combination of polymer and conducting properties. However, the mismatch between the polymer growth process and the carrier mobility design leads to poor material and device consistency, and insufficient long‐term device stability, thus hindering the practical application of CPs. Although 2D construction has been explored to address these challenges, it typically leads to materials instability and lacks methods for large‐scale synthesis, making it unsuitable for many application scenarios. Here a universal biomineralization‐like strategy relying on the joint impaction of hydrogen‐bond and gravity for large‐scale fabrication of 2D CPs is developed. As‐fabricated meter‐scale Polypyrrole films exhibit high orderliness and can be assembled into multilayers, allowing for adjustable thickness and transparency. Notably, these films demonstrate exceptional photothermal properties and remarkable long‐term stability, as their surface temperature can reach 140 °C when irradiated with an 808 nm laser at 0.7 W cm−2, with almost no attenuation after 170 days. Furthermore, under sunlight, the temperature can reach nearly 100 °C, showcasing significant potential in smart building and energy management applications. Importantly, this strategy can be extended to the 2D design of numerous light organic compounds, thus opening up possibilities for their practical applications.

Elicitation of Rank Correlations with Probabilities of Concordance: Method and Application to Building Management.

Constructing Bayesian networks (BN) for practical applications presents significant challenges, especially in domains with limited empirical data available. In such situations, field experts are often consulted to estimate the model's parameters, for instance, rank correlations in Gaussian copula-based Bayesian networks (GCBN). Because there is no consensus on a 'best' approach for eliciting these correlations, this paper proposes a framework that uses probabilities of concordance for assessing dependence, and the dependence calibration score to aggregate experts' judgments. To demonstrate the relevance of our approach, the latter is implemented to populate a GCBN intended to estimate the condition of air handling units' components-a key challenge in building asset management. While the elicitation of concordance probabilities was well received by the questionnaire respondents, the analysis of the results reveals notable disparities in the experts' ability to quantify uncertainty. Moreover, the application of the dependence calibration aggregation method was hindered by the absence of relevant seed variables, thus failing to evaluate the participants' field expertise. All in all, while the authors do not recommend to use the current model in practice, this study suggests that concordance probabilities should be further explored as an alternative approach for the elicitation of dependence.

Integrating machine learning in architectural engineering sustainable design: a sub-hourly approach to energy and indoor climate management in buildings

Integrating machine learning in architectural engineering sustainable design: a sub-hourly approach to energy and indoor climate management in buildings

Site Planning and Material Management of Residential Building

Site Planning and Material Management of Residential Building

Hierarchical-stochastic model predictive control for a grid-interactive multi-zone residential building with distributed energy resources

Using Model Predictive Control (MPC) is a promising method for enabling grid-interactive efficient buildings. Since MPC relies on a building model and the forecasts of external disturbances to derive optimal inputs, the uncertainties due to forecast errors and model inaccuracies can deteriorate the control performance. Most existing MPC studies for the built environment are deterministic MPC without consideration of uncertainties even though several different methods (e.g., stochastic MPC) are available in the literature to deal with them. Even studies that consider forecast uncertainties often neglect model inaccuracies. Hence, in the present paper, a novel hierarchical-stochastic MPC is proposed considering forecast uncertainties and model inaccuracies, and its performance is compared with deterministic, stochastic, and hierarchical MPC for power management in a residential building with distributed energy resources. The control objective is the cost-optimal scheduling of a heat pump, a battery for energy storage, and a rooftop photovoltaic system. Measurement data is used to identify the building model. The results for one-week simulation in winter show that (1) the deterministic MPC results in an unacceptable level of temperature constraint violations in two out of five rooms; (2) the hierarchical MPC can reduce the temperature constraint violations to an acceptable level at the expense of increased cost; (3) the stochastic MPC achieves the same reduction in temperature constraint violations as the hierarchical MPC but at slightly lower costs; and (4) the new proposed hierarchical-stochastic MPC results in both lower temperature constraint violations and lower financial expenses than the use of stochastic or hierarchical MPC individually.

Proposal of a domain model for 3D representation of buildings in Ecuador.

The accelerated urban sprawl of cities around the world presents major challenges for urban planning and land resource management. In this context, it is crucial to have a detailed 3D representation of buildings enriched with accurate alphanumeric information. A distinctive aspect of this proposal is its specific focus on the spatial unit corresponding to buildings. In order to propose a domain model for the 3D representation of buildings, the national standard of Ecuador and the international standard (ISO 19152:2012 LADM) were considered. The proposal includes a detailed specification of attributes, both for the general subclass of buildings and for their infrastructure. The application of the domain model proposal was crucial in a study area located in the Riobamba canton, due to the characteristics of the buildings in that area. For this purpose, a geodatabase was created in pgAdmin4 with official information, taking into account the structure of the proposed model and linking it with geospatial data for an adequate management and 3D representation of the buildings in an open-source Geographic Information System. This application improves cadastral management in the study region and has wider implications. This model is intended to serve as a benchmark for other countries facing similar challenges in cadastral management and 3D representation of buildings, promote efficient urban development and contribute to global sustainable development.

Literature Review on The Whole Life Cycle Assessment of Passive Buildings in The Context of Dual Carbon Emissions

With the increasing global demand for sustainable buildings, passive building design has become an area of concern. The design concept of passive buildings is known for its efficient energy use and excellent indoor environmental quality. However, there is a need to delve deeper in order to fully assess the economics and sustainability of passive buildings. The whole life cycle management of passive buildings is a relatively new management concept, and the evaluation research of the whole life cycle of passive buildings under the dual-carbon target is still limited. This paper reviews the evaluation methods and criteria based on the whole life cycle of passive buildings. The literature review includes research conducted over the past two decades and will focus on evaluation indicators for passive buildings. Many reviews present evaluation indicators for low energy design in the full life cycle evaluation of passive buildings and discuss future design directions. This literature review serves as a preliminary step to guide the evaluation criteria of passive buildings in light of China's two-carbon target, which will help to enrich the evaluation indicators of passive buildings and promote the transition to high-quality development of passive buildings.

Leveraging IoT for Smart Grids and Energy Management in Electrical Systems: Applications, Benefits, and Challenges

The integration of the Internet of Things (IoT) into electrical systems is transforming traditional power grids into intelligent, data-driven networks, capable of real-time monitoring, control, and optimization. This transformation, often referred to as the development of “smart grids,” presents opportunities for improving energy efficiency, enhancing reliability, and ensuring sustainability. IoT facilitates dynamic demand response, predictive maintenance, and seamless integration of renewable energy sources, positioning it as a key enabler of the energy transition. This paper provides a comprehensive overview of the role of IoT in electrical systems, with an emphasis on smart grids, predictive maintenance, and energy management in smart buildings. It explores IoT’s architecture, benefits, and challenges, including cybersecurity concerns and the lack of industry-wide standardization. The study also incorporates real-world data and graphical representations to illustrate the impact of IoT in optimizing power systems. Additionally, this paper discusses future prospects for IoT in electrical systems and suggests solutions to overcome existing challenges.

Empirical assessment of fire safety in high-rise residential buildings in Vietnam and residents’ knowledge and awareness regarding fire safety

With increasing population, the demand for high-rise residential buildings has been increasing. The challenges posed by firefighting and evacuation during fires in high-rise buildings have attracted considerable attention. This study explores the fire safety facilities and management in high-rise residential buildings in Vietnam and the knowledge and awareness of residents regarding fire safety. These aspects were assessed using a questionnaire answered by residents of 32 high-rise buildings in Vietnam. The answers reveal that most residents had basic knowledge of fire safety in high-rise buildings, but their preparedness of a fire event was inadequate. It is recommended that the implementation of safety regulations and measures for reducing the risk of fires in buildings be enforced. Besides analyzing descriptive statistics, a multiple regression analysis was conducted to explore the key factors influencing the level of awareness and knowledge of fire safety among the residents of high-rise buildings. The results indicate that education level, gender, living floor, and participation in fire drills are the key factors influencing residents' levels of knowledge and awareness. The survey results serve as supportive reference for the relevant stakeholders for reducing the risk of fires and the resulting losses. Furthermore, this study offers valuable insights for future studies on high-rise residential buildings in Vietnam at larger scales.

Gender Responsiveness in the Philippine Basic Education Context: Priority Thrusts and Initiatives in the Schools Division of Batangas City

In 2017, the Department of Education (DepEd) issued the Gender Responsive Basic Education Policy mandating schools to pursue initiatives to address enduring and emerging gender issues and to promote gender equality. This explanatory-sequential research explored and analyzed the gender-mainstreaming initiatives implemented in the Schools Division of Batangas City. Based on the Gender Mainstreaming Evaluation Framework (GMEF), the assessment of 255 basic education personnel reveal that the gender-mainstreaming in their Schools Division of Batangas City is currently at the GAD application (Level III). The basic education personnel know the various GAD initiatives institutionalized within the organization and the strategic approach to implementing GAD-related activities. The results and findings from the real-time Delphi survey and focus group discussion underscore the importance of targeted interventions in curriculum development, pedagogy, learning environments, research, capacity building, and knowledge management. The study recommends strengthening awareness programs, addressing knowledge gaps, implementing real-time monitoring and evaluation mechanisms, and fostering collaborative partnerships to enhance gender responsiveness within the Schools Division of Batangas City. These recommendations aim to foster an inclusive and equitable educational environment that supports the holistic development of all students, aligning with the principles of the Gender Responsive Basic Education Policy.

INNOVATIVE ENERGY MANAGEMENT SYSTEM OF RESIDENTIAL COMPLEX “PANORAMA” IN DNIPRO CITY

Problem statement. Improving energy efficiency is a priority for both the European Union and Ukraine, which has a clear and consistent direction of development in accordance with the strategies of the European Green Deal. Residential buildings consume a large percentage of the electricity produced, and improving the energy efficiency of buildings will contribute to energy conservation, as well as energy security and energy independence from energy imports. Significant savings in energy consumption can be achieved through the development and implementation of energy management systems to implement energy-efficient management of modern buildings and the use of smart technologies in buildings, which will allow to control and optimise energy consumption and promote the rational use of energy. The purpose of the article. To develop an energy management system for the residential complex “Panorama” in Dnipro city. The work was carried out within the framework of the international project PRECEPT [1] under HORIZON 2020 programme. Conclusions. An energy management system for a residential complex based on monitoring of climate and air quality parameters is proposed. The system has been successfully put into operation, and in real time receives and processes external data on energy costs, weather conditions and other parameters, analyses and accumulates data, makes the necessary decisions on energy consumption and sends the results to consumers and building managers to save energy or improve comfort.

Sustainable Development in Renewable Energy: Management of Solar Energy Application in Malaysia

The purpose of this study is to explore the factors and benefits that can encourage the building management team to adopt the solar energy usage in Malaysia. Solar energy has been long introduced to the industry as a practical renewable technology, but the adoption rate is still low in Malaysia due to the dependence on oil and fossil fuels. Thus, costs and benefits of solar energy application and the best solar panels to be used in Malaysia have been explored for practitioners’ reference to improve the adoption rate. Mixed method was adopted in this study. First, quantitative method was adopted where 200 sets of online questionnaire survey were distributed to the public to collect the information about the solar energy application. Next, a semi-structured interview was carried out to further investigate the reliability of collected data. Based on the findings of the questionnaires, the most significant benefits of solar energy are renewable and clean source of energy, eco-friendly, and cost saving. The results indicated that Mono-crystalline silicon cell is the most popular type of solar panel that widely used in Malaysia. However, the adoption of solar energy is low due to the high initial cost and insufficient knowledge and awareness among citizens. Through the results of this study, the adoption of solar energy can be doubled in future as the results reveal the factors and benefits that could help the policy makers to utilize the implementation of solar energy in residential buildings that massively consuming the energy in daily basis.

Applicability evaluation of a temperature humidity index-controlled ventilation system in livestock using a building energy simulation model

In general, for livestock building, a simple system for controlling the HVAC system that is based only on the indoor air temperature is applied. This study evaluated the applicability of temperature humidity index (THI)-based ventilation systems installed in livestock buildings using a building energy simulation model. Based on the monitoring data of an actual pig house, the integrated predictive performance of the indoor temperature and humidity of the building energy simulation model was calibrated. Additionally, the indoor environment of the existing temperature-based control and THI-controlled ventilation systems was compared through simulations. The average THI and the section exceeding the THI threshold were both lower compared to the existing system. This was because the part load ratio of the fans of the THI-controlled ventilation system was higher than that of the existing system, indicating better ventilation. These results suggest that THI-based ventilation systems can overcome the limitations of existing temperature-based systems and effectively improve the thermal stress management of livestock buildings. This study portrays that the indoor environment can be improved by simply changing control variables, while presenting the field applicability and research value of THI-based control systems in the management of livestock environments.

Smart Class System Prototyping through Sustainable Infrastructure Based on Mobile Application SPACE (Smart Program - Class Architecture) Integrated Smart Building Management System

Optimizing innovation in the use of health technology in infrastructure will directly impact the conditions of social interaction in the community, including within the scope of the school area. The Smart Class concept collaborates with learning carried out in a hybrid way. However, it is not yet fully optimized by digitizing the existing infrastructure with the concept of managing school facilities and infrastructure. The implementation of the Smart Class uses the intelligent building management system (IBMS), where this system integrates all parts of the building with the Internet of Things (IoT), facilities, and infrastructure and can minimize pandemic transmission in the academic sphere by accessing via mobile app. This research aims to analyze the design of the smart program class architecture integrated monitoring system to implement IoT-integrated health protocols, especially in the middle school scope. This research uses qualitative and quantitative methods with descriptive analysis through the development of user research at the system design stage. The output of this innovation is how schools implement digital technology comprehensively, starting from the application of IoT, sensors, and databases in a real-time mobile app environment. There are three main things: the data input, data processing, and output value. The intervention of school needs can be expanded with the integration of the learning management system in the form of integrated learning management the learning process, which is in line with monitoring the use of infrastructure in schools. Through this Smart Class concept, schools can still operate optimally without any applicable health policies and can provide excellent academic services.
 Keywords: smart class system prototyping, sustainable infrastructure mobile application, SPACE smart building management system

Creation of a System of Cost Management Indicators for the Construction Investment Projects of the Green Healthcare Buildings

Introduction. Construction of the green healthcare buildings is a rather new and priority direction of construction in China. One of the key components of efficient implementation of the projects of green healthcare buildings is the cost management of a construction investment project. The projects of green buildings envisage the advanced technical content of a facility, a wide project scope and large number of participants. Therefore, the cost management requirements have to be more demanding, however, the traditional fragmented management fails to meet the requirements fostering the development of the green healthcare buildings. The present research investigates the issues of cost management of the green healthcare construction projects, analyses the necessity, feasibility, development trends and practical cost management problems thereof. The research strives to develop the cost management assessment indicators for all life cycle stages of the projects of green healthcare buildings.Materials and Methods. The research was conducted using such methods as the literature review and the expert interview methods. The expert interview method allows using the experience of experts from the related fields to assist in decisionmaking. Therefore, a questionnaire was developed as a part of the research.Results. Upon in-depth study of the various factors affecting the cost management of the green healthcare construction projects, the strategies and response measures have been developed based on the advantages and cost management features. By summarizing the cost management assessment indicators referring to implementation of the green healthcare construction projects and by combining the opinions of the experts and scientists from the related fields, the cost management assessment system for a project of green healthcare building has been created. The created assessment indicators make it possible to implement better control over the costs assigned to the green healthcare construction projects, elevate the level of project cost management, enhance the integrated benefits of the project and ensure the cost management and cost control for the similar projects.Discussion and Conclusion. The results of the research provide a theoretical basis for creating a cost management assessment system for the green healthcare construction projects aimed to solve the problems of cost management of the green healthcare buildings. The practical significance consists in providing a real practical approach to improving the cost management of the projects of green healthcare buildings.

건축물 화재안전에 관한 관련법상 연구

Every time a major fire incident occurs, such as the Seocheon Specialized Market fire incident in South Chungcheong Province on January 22, 2024, the fire safety management authorities, including the central government (Ministry of Public Administration and Security, National Fire Agency) and local governments (local governments, fire stations), have revised organizations, mechanisms, and laws and promised to prevent recurrence. However, they are unable to effectively manage fire safety due to overlapping duties between fire safety management departments, dual regulations in fire-related laws, deficiencies in on-site command systems, and the public's insensitivity to disaster safety. Protecting the lives, bodies, and property of citizens from various unexpected fires aligns with the objectives of the「Constitution」,「Basic Fire Fighting Act」,「Fire-related Laws」, and「Building- related Laws」. This paper aims to present the problems and improvement directions of the laws related to fire safety management in buildings, followed by personal opinions and methods for enhancing public fire safety awareness and conducting education.

Optimizing Energy Consumption in Buildings: Intelligent Power Management Through Machine Learning

In the realm of energy conservation, managing power consumption within buildings emerges as a pivotal challenge. This study introduces sophisticated models that optimize energy usage by intelligently managing power distribution in various zones of a building. To achieve this, four machine learning classifiers, Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN) algorithm, and Naive Bayes (NB), were employed. These classifiers were integrated with feature reduction techniques, namely Boruta and Principal Component Analysis (PCA), to diminish model complexity. The study delineates three distinct power management strategies: Full, Selected, and Shutdown. The effectiveness of these models was evaluated using a dataset obtained from a building's energy consumption measurements. A comparative analysis revealed that the integration of the RF classifier with the Boruta feature reduction method significantly excelled, achieving a classification accuracy of 98%. Additionally, this combination demonstrated an execution time of merely 0.4549 seconds. The findings of this research not only underscore the efficacy of combining specific machine learning classifiers with feature reduction techniques but also highlight the potential of such integrations in optimizing energy consumption in building environments. This approach paves the way for more energy-efficient and sustainable building management practices.