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Combined with the energy consumption data of individual buildings in the logistics group of Yangtze University, the analysis model scheme of energy consumption of individual buildings in the university is studied by using Back Propagation (BP) neural network to solve nonlinear problems and have the ability of global approximation and generalization. By analyzing the influence of different uses, different building surfaces and different energy-saving schemes on the change of building energy consumption, the grey correlation method is used to determine the main influencing factors affecting each building energy consumption, including uses, building surfaces and energy-saving schemes, which are used as the input of the model and the building energy consumption as the output of the model, so as to establish the building energy consumption analysis model based on BP neural network. However, in practical application, BP neural network has the defects of slow convergence and easy to fall into local minima. In view of this, this paper uses genetic algorithm to optimize the weight and threshold of BP neural network, completes the improvement of various building energy consumption analysis models, and realizes the qualitative analysis of building energy consumption. The model verification results show that the viscosity of the building energy consumption analysis model based on genetic algorithm improved BP neural network algorithm (GABP) in this paper is relatively high, which is more accurate than the results of the traditional BP neural network model, and the relative error of the analysis model is reduced from 11.56% to 8.13%, which proves that the GABP can be better suitable for the study of school building energy consumption analysis model, It is applied to the prediction of building energy consumption, which lays a foundation for the realization of carbon neutralization in the South expansion plan of Yangtze University. [ABSTRACT FROM AUTHOR]

The construction industry and associated processes emit about 40%-50% of greenhouse gasses globally, making buildings' lifelong impact on the environment inevitable. Although research and development stakeholders have directed their focus on various sustainable, recycled, and upcycled building materials, as well as circular designs and construction methods to reduce the adverse effects of environmental challenges, researchers have not yet fully addressed a building's post-use treatment. Considering that the gap still remains in knowledge concerning how to fully achieve net-zero waste and emissions from construction materials, designs, and processes at the end of a building's life, this study contributes a concise definition of the concept of adaptability with a holistic review to understand Design for Adaptability (DfA) and its potential to reduce the need for unnecessary new construction and eliminate potential waste. This review used the PRISMA guidelines approach to gather key insights from various articles on the concept of adaptability that are relevant to the scope of buildings. Moreover, this review identifies potential areas of further research that could boost confidence in the use of adaptable strategies in the future. A total of 50 articles out of 170 articles were chosen through a selection process involving a new set of inclusion and exclusion criteria based on PRISMA guidelines. The findings show that demographical, technological, and economic motivations drive adaptability's functional, environmental, economic, and social benefits. However, the regulatory, technical, economic, and social barriers hinder its implementation in construction processes. The findings also demonstrate that various promising frameworks for assessing adaptability still lack comprehensive guidelines, assessment, and validation methods for the overall implementation of adaptable strategies. Existing frameworks are mostly limited to spatial assessment of the reuse of spaces and do not account for the structural flexibility and performance of load-bearing building elements despite the fact that most assessed papers were from the engineering field. Nevertheless, this paper concludes that adaptability strategies can be implemented early during the construction of new buildings or during the repurposing of existing buildings, with the end goal being to increase the longevity of the use of structures, prevent premature demolition, and minimize unnecessary construction waste. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a global focal point, notably affecting vulnerable countries like Pakistan. The country faces heightened risk, prompting concern among many due to its susceptibility to climate-related hazards. An imperative challenge arising from this phenomenon is the necessary shift towards sustainable energy, particularly concerning energy consumption within the building sector. Buildings significantly contribute to daily energy usage and subsequent GHG emissions. In Pakistan, transitioning to energy-efficient building stock holds pivotal importance in mitigating climate change impacts. This hinges on establishing a robust institutional framework and regulatory structure centered around energy efficiency. While Pakistan possesses policies and national guidelines advocating for energy-efficient buildings, their practical enforcement and application remain inadequate. The inception of the Building Energy Code of Pakistan in 1990, based on ASHRAE 90.1 standards, marked a step forward. However, obstacles rooted in institutional weakness and limited capacity building have impeded its effective adoption and adherence. Although the Energy Provisions of 2011 introduced modifications, their scope remained confined mainly to commercial structures. This paper conducts an extensive assessment of Pakistan's existing institutional and regulatory framework for building energy efficiency and transition. Drawing on literature insights and stakeholder perspectives, an in-depth understanding of prevailing policies and institutions uncovers underlying reasons for noncompliance and limited implementation. Additionally, input was gathered from stakeholders through interviews, aiming to identify barriers obstructing the reinforcement of building energy efficiency measures in Pakistan. Discourse and narrative analysis, informed by literature and stakeholder interviews, revealed the significance of awareness, participation, coordination, capacity building, technical expertise, finance, and resources as key factors contributing to deficient compliance and implementation of existing codes and policy guidelines. This paper also proposes actionable recommendations to expedite the transition towards a sustainable, energy-efficient building stock in Pakistan. [ABSTRACT FROM AUTHOR]

Buildings are energy- and resource-hungry: their construction and use account for around 39% of global carbon dioxide emissions; they consume around 40% of all the energy produced; they are responsible for over 35% of the EU's total waste generation; and account for about 50% of all extracted (fossil) materials. Therefore, they present a significant challenge to meeting national and international Net Zero targets of reducing greenhouse emissions and fossil resource use. The CircularB Project, is at the heart of this issue, which will underpin synergies of multi-scale circular perspectives (from materials, to components, to assets and built environments), digital transformation solutions, data-driven and complexity science, stakeholder behavioral science, and interdisciplinary capabilities towards achievable, affordable and marketable circular solutions for both new and existing buildings, for sustainable urban design, and for circular built environments across Europe. This paper contributes to the project by deriving new insights into the stakeholders' influences, inter-relationships, and obstacles in the implementation of circular economy concepts on existing building stocks in Europe, which represent over 90% of whole building assets. In order to identify and derive the insights, our study is rigorously based on (i) a robust critical literature review of key documentations such as articles, standards, policy reports, strategic roadmaps and white papers; and (ii) interviews with relevant stakeholders and decision makers. Uniquely, our work spans across all scales of CE implementation from materials, to products and components, to existing building stocks, and to living built environments. The findings point out the current challenges and obstacles required to be tackled. Inadequacies of financial incentives and governmental enforcement (via policy, legislation, or directive) are commonly found to be the most critical obstacles found throughout Europe. Circular economy is the global challenge and not just a single country can resolve the climate issue without the cooperation of other countries. The insights thus highlight the essential need for harmonized actions and tactical/pragmatic policies promoted and regulated by the European Commission, national and local governments who can dominate the influence, promote inter-relationship, and overcome the barriers towards circular economy much more effectively. [ABSTRACT FROM AUTHOR]

"How can the integration of Internet of Things (IoT) technology enhance the sustainability and efficiency of green building (G.B.) design?" is the central research question that this study attempts to answer. This investigation is important because it examines how green building and IoT technology can work together. It also provides important information about how to use contemporary technologies for environmental sustainability in the building sector. The paper examines a range of IoT applications in green buildings, focusing on this intersection. These applications include energy monitoring, occupant engagement, smart building automation, predictive maintenance, renewable energy integration, and data analytics for energy efficiency enhancements. The objective is to create a thorough and sustainable model for designing green building spaces that successfully incorporates IoT, offering industry professionals cutting-edge solutions and practical advice. The study uses a mixed-methods approach, integrating quantitative data analysis with qualitative case studies and literature reviews. It evaluates how IoT can improve energy management, indoor environmental quality, and resource optimization in diverse geographic contexts. The findings show that there has been a noticeable improvement in waste reduction, energy and water efficiency, and the upkeep of high-quality indoor environments after IoT integration. This study fills a major gap in the literature by offering a comprehensive model for IoT integration in green building design, which indicates its impact. This model positions IoT as a critical element in advancing sustainable urban development and offers a ground-breaking framework for the practical application of IoT in sustainable building practices. It also emphasizes the need for customized IoT solutions in green buildings. The paper identifies future research directions, including the investigation of advanced IoT applications in renewable energy and the evaluation of IoT's impact on occupant behavior and well-being, along with addressing cybersecurity concerns. It acknowledges the challenges associated with IoT implementation, such as the initial costs and specialized skills needed. [ABSTRACT FROM AUTHOR]

Building automation systems installed in large commercial buildings record sub-hourly measurements from hundreds of sensors. The use of such large datasets are challenging because of missing and erroneous data, which can prevent the development of accurate prediction models of the performance of heating, ventilation, and air-conditioning equipment. The use of the transfer learning (TL) method for building applications attracted researchers to solve the problems created by small and incomplete datasets. This paper verifies the hypothesis that the deep neural network models that are pre-trained for one chiller (called the source chiller) with a small dataset of measurements from July 2013 could be applied successfully, by using TL strategies, for the prediction of the operation performance of another chiller (called the target chiller) with different datasets that were recorded during the cooling season of 2016. Measurements from a university campus are used as a case study. The results show that the initial hypothesis of this paper is confirmed. [ABSTRACT FROM AUTHOR]

This paper presents the development of the Workplace Survey on Occupant Perception, Satisfaction, and Adaptive Behavior (WSOPSAB) framework designed in the context of Indian office buildings. It is developed as a potential communication tool, providing a platform for occupants to share their valuable experiences, preferences, and comfort requirements with building operators. It also serves as a means to educate, build awareness, influence, and motivate occupants for pro-environmental behaviors, further contributing positively to building energy performance. The development of WSOPSAB is based on the energy performance gap between actual operational energy use and preconstruction energy performance predictions in green buildings. The selective literature review presented in this paper explores the performance gap and identifies occupants as key stakeholders whose actions and interaction systems within the building need an evaluation for achieving the projected performance targets. The paper also highlights the limitations in existing established methods to investigate various inquiry levels of building and occupant interaction systems like understanding occupants' perception and satisfaction scores, identifying uncomfortable conditions with preferences, linking uncomfortable conditions to adaptive behavior, and its overall impact on building energy performance, thus completing the whole loop of evaluations. The design of WSOPSAB aims to evaluate this complete loop of interaction system of occupants within the building space. Further, the paper discusses the parametric survey sections/domains, various uncomfortable conditions, and possible adaptive behavior that occupants may adopt through available space interfaces. At last, the paper concludes by discussing the further development and implementation of the WSOPSAB tool for various building typologies. [ABSTRACT FROM AUTHOR]

Energy-efficient and sustainable building management has always been a key concern surrounding buildings. The rise of environmental and social concern in today's world has brought more attention to the issue of sustainable and smart building management. This paper aims to review the state-of-the-art research and performance on building management that aims to make more sustainable and energy-efficient decisions. This paper classifies building management based on technologies utilized for management and different aspects of management that should be considered when regarding the larger picture of "sustainability". Additionally, while keeping in mind that long-term sustainability cannot be achieved through energy management alone, this research investigates previous works that also mention diverse aspects that must be taken into consideration when creating a truly successful smart building environment: costs, occupant comfort, and security. Of course, each field deserves an extensive analysis, but the purpose of this review paper is to deliver current research that has brought attention to the rapidly shifting and developing field of smart buildings to provide a macro-level holistic viewpoint on how smart buildings and homes should be approached from a sustainability viewpoint. [ABSTRACT FROM AUTHOR]

In this paper, greywater samples are collected from the kitchens of different types of buildings (residential and commercial) located in different districts within the city of Jeddah, Saudi Arabia. The collected samples are analyzed and compared with the potable water from the same region. The parameters investigated are pH, conductivity, total solids (TS), total dissolved solids (TDS), total suspended solids (TSS), total hardness, temporary hardness, permanent hardness, alkalinity, chloride, and biochemical oxygen demand (BOD). It was found that the amount of total suspended solids is very high in the greywater samples. It shows the presence of both temporary and permanent hardness. Their alkalinity values are greater than hardness. It may be due to the number, lifestyle, age of the occupants, presence of children, and social and cultural behavior of residents. The concentration of BOD level is very low, which shows that the greywater samples have lower concentrations of organic compounds. Design details of the greywater treatment plant are suggested based on the results of the analysis. This includes a screening chamber, grit chamber, settling tank, and filtration unit. The treated greywater is recommended for reuse for gardening, landscaping, and toilet flushing purposes. [ABSTRACT FROM AUTHOR]

In an era of increasing energy demands and environmental concerns, optimizing energy consumption within buildings is crucial. Despite the vast improvements in HVAC and lighting systems, plug loads remain an under-studied area for enhancing building energy efficiency. This paper studies smart plug active operating mode detection, plug-level load forecasting, and plug scheduling methodologies. This research leverages a unique dataset from the University of California, San Diego, consisting of readings from over 150 smart plugs in several office buildings for more than a year, notably during the post-Covid era. This dataset is made publicly available. A comprehensive literature review on plug, i.e. , appliances operating mode detection is presented. Novel unsupervised learning approaches are applied to identify plug operating modes. A pipeline integrating the detected modes with forecasting and scheduling is developed, aiming at building energy consumption reduction. Our findings offer valuable insights and promising results into smart plug management for energy-efficient buildings. • A novel year-long dataset of power readings from 169 office smart plugs is introduced. • The first review of plug load mode detection methods and terminology is presented. • The paper proposes an unsupervised method to identify plugs load operating modes. • The proposed smart plug scheduling pipeline reduces energy consumption by 20%. [ABSTRACT FROM AUTHOR]

This paper investigates the possibilities and challenges of using mass timber as a sustainable alternative for retrofitting existing buildings in Canada. To create the knowledge foundation on which to devise a holistic framework tailored to the specific characteristics of Canada's built environment, a detailed analysis of the types, geographical distribution, structural, and energy features of the local building stock is first presented. Then, previous strategies for enhancing and upgrading existing buildings with engineered timber are reviewed, classified, and evaluated. Finally, to explore economic and environmental implications, a detailed assessment of available life-cycle cost–benefit analysis approaches is conducted alongside their adaptation to Canada's building context. The findings of this paper can inform policymakers, builders, and designers in developing more sustainable building retrofit practices, design, and regulations, in line with Canada's efforts toward net zero emissions. [ABSTRACT FROM AUTHOR]

The management of large enterprises influences their efficiency and profitability. One of the important aspects is the appropriate management of electricity consumption used for production and daily operation. The problem becomes more complicated when you need to manage not one but a large complex of buildings with heterogeneous purposes. In the paper, we examine real-time series data of electrical energy consumption in a complex of heterogeneous buildings, including offices and warehouses, using time series analysis methods such as the Holt–Winters model and ARIMA/SARIMA model, and neural networks (Deep Neural Network, Recurrent Neural Network, and Long Short-Term Memory). Experimental research was performed on a dataset obtained from an energy consumption meter placed in the building complex, built in different periods, and equipped with a variety of automation devices. The data were collected over a period of four years 2018–2021 in the form of time series. Results show that classic models are good at predicting energy consumption in the mentioned type of buildings. The ARIMA model gave the best results—for buildings characterized by seasonality and trends the forecasts were almost perfect with actual values. [ABSTRACT FROM AUTHOR]

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The ongoing research on model predictive control (MPC) for building air conditioning systems predominantly centers on improving the predictive capabilities of system models. In this paper, the impacts of three additional pivotal factors on MPC performance are assessed by examining a generic MPC design for a typical variable air volume (VAV) system that serves large commercial buildings. The three factors encompass the nuanced reformulation of optimization, the judicious relaxation of constraints, and the meticulous tuning of parameters. Detailed case studies with an integrated Modelica and EnergyPlus model of the US Department of Energy's Commercial Reference Building are conducted. The results confirm that the optimization formulation, along with relaxation methods, significantly affects MPC performance in terms of energy savings, zonal thermal comfort level, and computational demand. They also reveal that the impact of the MPC control parameters on the energy savings and thermal comfort may vary by season and can be non-monotonic. [ABSTRACT FROM AUTHOR]

Despite all the literature on building energy management, building-stock-scale models depicting its impact for energy-market-scale optimisation models are lacking. To address this shortcoming, an open-source tool called ArchetypeBuildingModel.jl has been developed for aggregating building-stock-level data into simplified lumped-capacitance thermal models compatible with existing open-source energy-system modelling frameworks. This paper aims to demonstrate the feasibility of these simplified thermal models by comparing their performance against dedicated building simulation software, as well as examining their sensitivity to key modelling and parameter assumptions. Modelling and parameter assumptions comparable to the existing literature achieved an acceptable performance according to ASHRAE Guideline 14 across all tested buildings and nodal configurations. The most robust performance was achieved with a period of variations above 13 days and interior node depth between 0.1 and 0.2 for structural thermal mass calibrations, and with external shading coefficients between 0.6 and 1.0 and solar heat gain convective fractions between 0.4 and 0.6 for solar heat gain calibrations. Furthermore, three-plus-node lumped-capacitance thermal models are recommended when modelling buildings with structures varying in terms of thermal mass. Nevertheless, the ArchetypeBuildingModel.jl performance was found to be robust against uncertain key parameter assumptions, making it plausible for energy-market-scale applications. [ABSTRACT FROM AUTHOR]

In the early stages of building design, decisions are made about the building's form and envelope, but designers rarely base their decisions on sophisticated energy simulations, even though these features are critical to a building's energy performance. This paper employs three methods—empirical, parametric, and uncertainty—to assess the interconnectedness of building form, envelope, orientation, and occupancy regarding thermal comfort and energy consumption for heating and cooling a residential building across three regions: Gdyel (mediterranean climate), Oum El Bouaghi, and Constantine (semi-arid climate). The study variables include indoor air temperature, relative humidity, and energy consumption. The initial findings stem from an experiment conducted in an apartment on the top floor of a building in Gdyel, which allowed us to record the evolution of the variables mentioned throughout the year and validate the parametric results of the multi-zone model created in TRNSYS16 software. This study showed that for the considered climates, a compact form is more suitable; it was found that the top floor with SF = 0.57 needs about 30% to 54% more energy than the inter-floor with SF = 0.21. In addition, the heating and cooling methods and habits adopted by Algerian households are responsible for 18% to 35% on the top floor and the inter-floor, respectively. [ABSTRACT FROM AUTHOR]

Air conditioning systems can play a positive or negative role in the spread of COVID-19 infection. The importance of sufficient outdoor air changes in buildings was highlighted by the World Health Organization, therefore these should be guaranteed by mechanical ventilation systems or adequate air conditioning systems. The proposed case study concerns the optimal number of outdoor air changes to limit COVID-19 contagion for a school building in Central Italy. The Wells–Riley model is used to assess the risk of airborne infection, while energy consumption is calculated by a dynamic energy simulation software. The scope of the paper offers an innovative method to define the optimal ventilation strategy for the building's HVAC system design to reduce the risk of infection with limited increases in energy consumption and greenhouse gas emissions. Results show that the desirable approach is the one in which the same low value of contagion risk is set in all rooms. This new approach results in significant energy savings, compared to the most common ones (setting the same high outdoor air rates for all rooms) to counteract the risk of infection. Finally, the zero-emission building target is verified by introducing a suitable photovoltaic system to offset pollutant emissions. [ABSTRACT FROM AUTHOR]

Torsionally flexible buildings (that have torsional mode as fundamental mode) twist during earthquake shaking, and may collapse partially or completely depending upon the direction and level of shaking. The problem is aggravated when the building is torsionally unsymmetrical. Some design codes (like Eurocode, Indian Code) explicitly prohibit the design of such buildings. This paper presents a simple approximate method to identify torsionally flexible RC Moment Frame and RC Structural Wall buildings at the initial proportioning stage itself without carrying out a detailed structural analysis. It is possible to identify whether or not the first mode is torsional mode of a building (i.e., torsionally flexible building) if Natural Period Ratio τ>1 by modelling the building with rigid diaphragm and distribution of mass & stiffness along the height of building, and estimating: (1) radius of gyration of rotational mass rm of each floor plan geometry by lumping the masses of slabs, beams and all vertical elements at each nodes, (2) radius of gyration of twisting stiffness rKθ of all vertical elements using their translational and torsional stiffnesses (considering flexibility of adjoining beams and vertical elements accounting for both flexural and shear deformations), and (iv) τ (=rm/rKθ). The method is validated with 3D Modal Analysis (using τ =Tθ/T, where Tθ is Uncoupled Torsional Natural Period and T Uncoupled Translational Natural Period) of hypothetical buildings using a commercial structural analysis software. Also, parameters are identified that lead to τ>1, and solutions suggested to avoid torsional flexibility in buildings. Further, the method helps identify vertical stiffness irregularity in buildings. Draft provisions are suggested for inclusion in seismic codes. Also, poor performance of multi-storey building (with τ>1) is demonstrated using nonlinear static and nonlinear time history analyses. [ABSTRACT FROM AUTHOR]

Thermal comfort in indoor environments is perceived as an important factor for the well-being and productivity of the occupants. To practically create a comfortable environment, a combination of models, systems, and procedures must be applied. This systematic review collects recent studies proposing complete thermal-comfort-based control strategies, extracted from a scientific database for the period 2017–2021. The study consists of this paper and of a spreadsheet recording all the 166 reviewed works. After a general introduction, the content of the papers is analyzed in terms of thermal comfort models, indoor environment control strategies, and correlation between these two aspects. Practical considerations on scope, required inputs, level of readiness, and, where available, estimated cost are also given. It was found that the predicted mean vote is the preferred thermal comfort modeling approach, followed by data-driven and adaptive methods. Thermal comfort is controlled mainly through indoor temperature, although a wide range of options are explored, including the comfort-based design of building elements. The most popular field of application of advanced control strategies is office/commercial buildings with air conditioning systems, which can be explained by budget and impact considerations. The analysis showed that few works envisaging practical implementations exist that address the needs of vulnerable people. A section is, therefore, dedicated to this issue. [ABSTRACT FROM AUTHOR]

The presence of smart buildings in a smart grid as prosumers with the ability to both consume and produce clean energy can help to decentralize and decarbonize the electricity industry. An energy community (EC) refers to a collection of energy users and energy sources that participate in peer‐to‐peer (P2P) energy trading and contribute to the energy supply of the community through appropriate communication infrastructure. This paper examines the management of smart grid energy, including ECs, in order to promote energy democracy by incorporating smart buildings into P2P energy trading and demand response programs (DRPs). A model for energy democracy has been developed for a group of energy users consisting of prosumers and managers within ECs, based on user preferences. The paper classifies prosumers into three categories based on their preferences: flexible, economic, and social. Additionally, EC managers have been classified into two categories based on their preferences: interactive and non‐interactive managers. The CPLEX method in the GAMS software was utilized to solve the problem. The results show that the proposed approach improves access to energy within the smart grid system. [ABSTRACT FROM AUTHOR]

The present study offers a thorough scientometric analysis of the practice of bioclimatic retrofitting in commercial buildings, which is considered a crucial approach for mitigating energy consumption and addressing the challenges posed by climate change. Since Scopus offers advanced tools for literature search and analysis, its database was used to acquire bibliographic data for nearly 400 published papers using a bibliometric search, a scientometric methodology, and an in-depth qualitative analysis. The scientometric procedure utilizes various quantitative dimensions, such as the number of intermediate citations, occurrences, average publication year, and general connection power. A retrospective examination of research publication patterns spanning 2008 to May 2022 has unveiled an upward trajectory in scholarly investigations pertaining to commercial buildings during this 15-year period. Nevertheless, research on the topics of bioclimatic design, retrofitting strategies, and green building practices in the context of commercial buildings exhibits a more gradual incline, displaying an almost linear trend between the years 2016 and 2020. Additionally, the study provides qualitative perspectives on the research environment. The paper delineates various focal points of research within the field, encompassing thermal comfort in the context of energy management and climate control, ventilation systems, sustainable development as it pertains to architectural designs and green buildings, retrofitting strategies in commercial buildings to enhance energy efficiency, the interplay between carbon dioxide levels and energy resources, the utilization of solar energy, the relationship between energy conservation and atmospheric temperature, and the application of building energy simulation techniques. [ABSTRACT FROM AUTHOR]

Small and medium commercial buildings account for nearly half of the energy consumed by commercial buildings in the United States. While energy retrofits can significantly reduce building energy consumption, buildings' owners often lack the capital and experience to perform detailed energy audits and retrofit assessments. The purpose of this paper is to introduce a low-investment, bottom-up and simplified methodology for identifying energy retrofit opportunities that benefit the owners of small and medium sized office buildings In particular, the paper addresses small and medium commercial buildings on a university campus as a proof-of-concept for other owner-operators that have small and medium commercial facilities in their portfolio. The methodology consists of an eight-step framework using publicly-available and simplified tools. While energy audits and retrofit opportunity assessments are not new, a low-cost methodology for owner-operators of small and medium commercial buildings to analyze energy consumption and identify retrofit opportunities represents a contribution to knowledge. A medium office building on a university campus in Arizona served as a case study to validate the methodology. The case study showed a maximum potential energy reduction of an estimated 50%, but the figure varies based on the types of retrofit (deep versus light), energy conservation measures selected and implemented, invested resources, and interactive effects between measures. This methodology is extensible to other owner-operators that have building utility data and would like to perform retrofit opportunity assessments themselves. [ABSTRACT FROM AUTHOR]

In the context of rapidly increasing energy demands and environmental concerns, optimizing energy management in commercial buildings is a critical challenge. Smart grids, empowered by advanced Energy Management Systems (EMS), play a pivotal role in addressing this challenge through Demand Side Management (DSM). However, the efficiency of DSM-based building EMS is often limited by the accuracy of load forecasting. This paper addresses this gap by exploring load forecasting models within DSM-based building EMS, focusing on a case study in a commercial building in Ankara, Turkey. Employing Deep Learning (DL) models for load forecasting, we provide inputs for rule-based controllers to enhance energy efficiency. Our major contribution is the development of the ANFIS-IC algorithm, aimed at maximizing demand response participation in commercial buildings. ANFIS-IC, integrating ANFIS controllers with LSTM-based load consumption forecasts, leads to a 33.14% reduction in energy consumption and a 39.22% decrease in energy costs, surpassing the performance of rule-based controllers alone which achieve reductions of 25.34% in energy consumption and 34.03% in energy costs. These findings not only highlight the potential of integrating rule-based controllers with deep learning algorithms but also underscore the importance of accurate load forecasting in improving the effectiveness of DSM-based building EMS. [ABSTRACT FROM AUTHOR]

In the past few years, there has been a notable interest in the application of machine learning methods to enhance energy efficiency in the smart building industry. The paper discusses the use of machine learning in smart buildings to improve energy efficiency by analyzing data on energy usage, occupancy patterns, and environmental conditions. The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and gradient boosting regressor. Real-life case studies on educational buildings are conducted to assess the practical applicability of these models. The data is rigorously analyzed and preprocessed, and performance metrics such as root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are used to compare the effectiveness of the algorithms. The results highlight the importance of tailoring predictive models to the specific characteristics of each building's energy consumption. [ABSTRACT FROM AUTHOR]

Featured Application: The studies presented in the article are useful for designing secondary vibration isolation. They also show that relying solely on indications from one method of assessing the impact of vibrations on people in buildings, a potential investor or later a manager may be exposed to complaints from residents of buildings located near transportation investments. This research paper delves into the nuanced effects of traffic-induced vibrations on human comfort and perception within residential and commercial buildings. By prioritizing the influence of vehicle types—including metro trains, trams, and cars—over their speed or mass, the study presents a novel perspective on addressing vibrational comfort. Conducted in the urban context of Warsaw's metro line construction, this investigation employs a rigorous methodology, utilizing both the Root Mean Square (RMS) and Vibration Dose Value (VDV) analytical methods to quantify vibrational impacts. The findings illuminate the distinct contributions of various transportation modes to the perceived vibrations, offering significant insights into the complex relationship between the Human Perception of Vibration Index (HPVI) and VDV values. It underscores the necessity of integrating a multifaceted consideration of vehicle type, operational dynamics, and urban infrastructure in the strategic planning and design of buildings. Such a holistic approach is essential for mitigating the adverse effects of transportation-induced vibrations, thereby enhancing the quality of life and well-being of urban inhabitants. [ABSTRACT FROM AUTHOR]

In recent years, the focus has been on enhancing user comfort in commercial buildings while cutting energy costs. Efforts have mainly centered on improving HVAC systems, the central control system. However, it's evident that HVAC alone can't ensure occupant comfort. Lighting, blinds, and windows, often overlooked, also impact energy use and comfort. This paper introduces a holistic approach to managing the delicate balance between energy efficiency and occupant comfort in commercial buildings. We present OCTOPUS, a system employing a deep reinforcement learning (DRL) framework using data-driven techniques to optimize control sequences for all building subsystems, including HVAC, lighting, blinds, and windows. OCTOPUS's DRL architecture features a unique reward function facilitating the exploration of tradeoffs between energy usage and user comfort, effectively addressing the high-dimensional control problem resulting from interactions among these four building subsystems. To meet data training requirements, we emphasize the importance of calibrated simulations that closely replicate target-building operational conditions. We train OCTOPUS using 10-year weather data and a calibrated building model in the EnergyPlus simulator. Extensive simulations demonstrate that OCTOPUS achieves substantial energy savings, outperforming state-of-the-art rule-based and DRL-based methods by 14.26% and 8.1%, respectively, in a LEED Gold Certified building while maintaining desired human comfort levels. [ABSTRACT FROM AUTHOR]

Energy efficiency in buildings has a central role to play in reaching the climate neutrality goal set by the European Green Deal. With detailed knowledge of their building stock and the profile of their occupants, regional and local authorities can forge an important link between financiers, industry professionals and homeowners to ensure the successful deployment of financial schemes that support the uptake of energy efficiency upgrades. This paper provides a first assessment of the role of regional and local authorities by reviewing relevant initiatives and programmes on energy efficiency. Based on a questionnaire completed for more than 150 schemes, it explores how European municipalities and regions stimulate energy upgrades in residential, commercial and public buildings through public financial support. It is found that 60% of the examined schemes are offered in the form of grants and subsidies, and 45% of them targeted residential upgrades. The use of EU cohesion policy funds in supporting regional schemes, and promotion of energy efficiency investments at local level through the European Covenant of Mayors initiative are also explored. In spite of possible resource limitations at this level of governance, regional and local authorities are in a good position to utilise European structural or research funds to develop financial schemes, as standalone programmes or blended with national ones, thus providing additional support and funds for deep renovations. The results suggest that energy efficiency in buildings has become an important part of local and regional strategies in several European countries, but could be further enhanced. [ABSTRACT FROM AUTHOR]

Non-residential buildings are responsible for more than a third of global energy consumption. Estimating building energy consumption is the first step towards identifying inefficiencies and optimizing energy management policies. This paper presents a study of Deep Learning techniques for time series analysis applied to building energy prediction with real environments. We collected multisource sensor data from an actual office building under normal operating conditions, pre-processed them, and performed a comprehensive evaluation of the accuracy of feed-forward and recurrent neural networks to predict energy consumption. The results show that memory-based architectures (LSTMs) perform better than stateless ones (MLPs) even without data aggregation (CNNs), although the lack of ample usable data in this type of problem avoids making the most of recent techniques such as sequence-to-sequence (Seq2Seq). [ABSTRACT FROM AUTHOR]

This paper investigates the Indoor Environmental Quality (IEQ) factors influencing occupant satisfaction in commercial buildings in Iran, contrasting the views of building experts (architects and engineers) with those of building occupants. Employing the fuzzy analytical hierarchy process (FAHP), this study focuses on the four primary IEQ factors: thermal comfort, indoor air quality, visual comfort, and acoustic comfort. The study aims to bridge the gap between expert evaluations and occupant perceptions of IEQ factors in commercial buildings in Iran. By examining the disparities in prioritising IEQ factors between these two groups, the study sheds light on the complexities of IEQ assessment and highlights the importance of considering diverse perspectives in optimising indoor environments. Our methodology includes a survey conducted among 30 building experts (15 architects and 15 building engineers) and 102 occupants, employing FAHP to derive the relative importance weights of each IEQ factor. The results highlight significant disparities between architects, engineers, and occupants in prioritising these factors. Architects emphasise visual comfort (42%), while engineers and occupants view thermal comfort (53% and 41%) as the most crucial factor for occupant satisfaction. The study underscores the complexity of IEQ in commercial buildings and the diverse perspectives influencing its assessment. It contributes to the broader discourse on optimising IEQ, emphasising the need for a comprehensive approach that encompasses both technical expertise and occupant experience. [ABSTRACT FROM AUTHOR]

Traditional buildings have a central role to play in Europe's plans to be the first climate-neutral continent by 2050, with the building sector being the single largest energy consumer in the EU with 40 per cent of total energy use. Seventy-five per cent of the existing housing stock is energy inefficient with minute numbers renovated each year. Existing buildings offer huge potential for energy use reduction. Research has shown that a historic retrofit can emit less carbon compared to demolishment and rebuilding. Reductions in carbon emissions of up to 62 per cent were observed across a body of case studies by Historic England, including a 95 per cent reduction in the mews case study described in this paper. Moreover, carefully managed thermal retrofits, taking a 'whole house approach', have many benefits, including improved indoor comfort and air quality as well as reduced operational costs. These are factors which are fundamental in ensuring the continued use of historic constructions while improving their standards of preservation and durability. Thermally upgrading traditional building is still a much-debated topic. Inappropriate thermal interventions with unsuitable materials and finishes can have unforeseen consequences, resulting in building damage and a reduction in internal comfort, health and well-being. This paper aims to contribute to this discussion by providing an overview of key considerations when thermally upgrading the walls of traditional buildings while preserving unique characteristics and functionality. Advantages of adopting thermal mortars such as cork lime are put forward, and their potential efficacy is discussed, concluding with a case study focusing on the deep retrofit of a London mews within a conservation area. [ABSTRACT FROM AUTHOR]

Despite the recognition of the built environment as a sector with high potential for reducing embodied emissions, there is a lack of national-level data on embodied carbon emissions attributed to the US commercial building stocks. Hence, there is a need to benchmark the current state of embodied emissions attributed to the commercial built environment and the impact of circular economy (CE) policies for their decarbonization to facilitate well-informed decision-making. This paper fills this knowledge gap through providing policy makers with a framework that estimates the current and future projections of embodied carbon emissions attributable to the US commercial building stocks and highlighting the decarbonization potential of multiple CE policies. To this end, the following multistep research methodology was adopted: (1) collecting and integrating relevant data; (2) conceptualizing and initializing a system dynamics (SD) model; (3) developing subsystems and coflow structures within the SD model using aggregated stock data from the National Energy Modeling System; (4) verifying and testing the developed SD model; and finally (5) suggesting policies and conducting scenario analysis using CE policy precedents. Findings reveal that in the baseline scenario, cumulative emissions are projected to reach 5,605 MtCO2e by 2050. As for the scenario analysis, the unit size reduction policy emerged as the most impactful single policy, achieving a remarkable 38.8% decarbonization. Whereas the comprehensive CE policy that optimizes floorspace demand and the carbon intensity of materials, exhibited a 52% decarbonization potential by midcentury. As such, this study contributes to the body of knowledge by benchmarking emissions projections, providing insights regarding CE decarbonization strategies, their associated primary stakeholders and implementation pathways. Ultimately, by embracing a holistic approach toward CE policies and harnessing accurate and standardized data on building embodied emissions, stakeholders can effectively attain decarbonization goals and promote a sustainable built environment. [ABSTRACT FROM AUTHOR]

Purpose: Compared to low-rise and mid-rise buildings, commercial high-rise buildings have severe maintenance management deficiencies due to the complex nature of the structure and building services incorporated. Previous studies have shown that implementing lean in maintenance is a recognised prominent strategy to enhance maintenance performance. Thus, this study aims to investigate how lean maintenance can be applied to improve maintenance management in commercial high-rise buildings in Sri Lanka. Design/methodology/approach: This study adopted a case study method. Three commercial high-rise buildings were selected to conduct the empirical study. An expert survey is also conducted to validate the findings. Findings: The findings of the study revealed that out of the eight cardinal types of lean maintenance waste, six are rooted in the selected cases: (i) excessive preventive maintenance, (ii) waiting (maintenance resources, tools, procuring of additional supplies and documentation and permits), (iii) transportation due to centralised maintenance, (iv) poor inventory management, (v) poor information handling and (vi) poor utilisation of labour. Then the study revealed strategies to eradicate identified lean maintenance wastes. Practical implications: The findings of this study can be used to guide maintenance practitioners in implementing lean maintenance in Sri Lankan commercial high-rise buildings. Furthermore, the proposed strategies can be directly applied to mitigate identified maintenance wastes. Originality/value: This paper provides information on how high-rise commercial buildings in Sri Lanka can enhance their maintenance management by mitigating lean maintenance wastes. [ABSTRACT FROM AUTHOR]

Massive data can be collected from meters to analyze the energy use behavior and detect the operation problems of buildings. However, missing and abnormal data often occur for the raw data. Effective data filling and smoothing methods are required to improve data quality before conducting the analysis. This paper introduces a data filling method based on K-SVD. The complete dictionary is trained and then utilized to reconstruct incomplete samples to fill the missing or abnormal data. The impacts of the dictionary size, the data missing continuity, and the sample size on the performance of the proposed method are studied. The results show that a smaller dictionary size is recommended considering the computational complexity and accuracy. The K-SVD method outperforms traditional methods, showing a reduction in the MAPE and CVRMSE by 3.8–5.4% and 6.7–87.8%. The proposed K-SVD filling method performs better for non-consecutive missing data, with an improvement in the MAPE and CVRMSE by 0.1–4% and 5.1–6.7%. Smaller training samples are recommended. The method proposed in this study would provide an effective solution for data preprocessing in building and energy systems. [ABSTRACT FROM AUTHOR]

In the past three decades, fire engineering has experienced fast development worldwide. Fire regulations for building industry were moved from prescriptive description to performance-based specification. This trend started in the UK in the 1980s and spread to other western countries. Hong Kong closely followed the UK development and adopted the approach of performance-based design (PBD) for the Hong Kong International Airport and MTR stations in the early 1990s. The Government of Hong Kong SAR formally recognised the PBD approach in the prescriptive codes of practice in the mid-1990s and developed the performance-based code (PBC) in the 2000s. This PBC was promulgated in 2011. The evolution in fire engineering impacted the fire community in Mainland China. The State Key Laboratory of Fire Science (SKLFS) was established in University of Science and Technology of China (USTC) in 1991. Then fire science and fire engineering stepped into the fast development track. The building industry in Mainland China started to adopt the PBD approach in the early 2000s for the significant developments including large airport terminals, railway and metro stations, super high-rise buildings, and mega commercial centres. However, a structured PBC system is not available within the regulatory framework to date. Adoption of PBD approach is slowing down in recent years. This paper presents a review of fire engineering development in Hong Kong and Mainland China. The review focuses on the development of the PBC in Hong Kong, and the PBD approach and fire research in Mainland China in the past 30 years. [ABSTRACT FROM AUTHOR]

This paper uses SketchUp and OpenStudio to design and optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. By establishing a basic model, the performance parameters such as insulation thickness, typical outer window, window-to-wall ratio, and their contribution rates within the threshold range are optimized for energy conservation; simulate the energy consumption of the determined multiperformance parameter combination scheme, select the most energy-saving scheme, and calculate its energy-saving contribution rate; calculate the life cycle cost of the above schemes, select the scheme with the lowest cost, and analyze its economic benefits; select energy-saving cost and economic benefit, and calculate energy-saving contribution rate and economic benefit. Finally, through the comparative analysis of the design and test data, this paper concludes that EnergyPlus will optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. At the same time, the multiobjective optimization method and process of the passive energy-saving technology of the near-zero energy consumption building proposed in this paper, as well as the technology combination template under different needs, provide a reference for the selection of the technology path. [ABSTRACT FROM AUTHOR]

Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems' performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI's and Elsevier's databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields. [ABSTRACT FROM AUTHOR]

Using thermal insulation materials to reduce energy loss in buildings is a key action. For reducing the building's energy use, firstly, the internal unheated spaces (attics, cellars) should be insulated, followed by the insulation of the external walls, and changing the doors and windows. Finally, the building can be completed with the renovation/maintenance of its service systems. Newly designed and constructed buildings are subject to increasingly strict regulations, which highlight the minimization and elimination of wasteful energy use and the resulting emissions of harmful substances. Therefore, the use of thermal insulation is the first step in making buildings more energy efficient. In this editorial, seven articles covering thermal insulation possibilities and topics are highlighted. This paper reflected on the use of thermal insulations both for internal and external applications. This editorial also promotes the use of super insulation materials such as aerogels and vacuum insulation panels; furthermore, the possible applications of bio-based insulations are also endorsed. In this paper, the sound insulation capabilities of some materials are also emphasized, and they will be presented from the point of view of cost. [ABSTRACT FROM AUTHOR]

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Automatic Digital Orthophoto Map (DOM) generation plays an important role in many downstream works such as land use and cover detection, urban planning, and disaster assessment. Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification; this can consume much time and produce building facade contained results. To address this problem, a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper. Firstly, 3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images, respectively. Then, the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points. Subsequently, the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline (LR-B) interpolation method with triangular mesh constraint for the point clouds void area, and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice. Finally, a seamline network is automatically searched using a disparity map optimization algorithm, and DOM is smartly mosaicked. The qualitative and quantitative experimental results on three datasets were produced and evaluated, which confirmed the feasibility of the proposed method, and the DOM accuracy can reach 1 Ground Sample Distance (GSD) level. The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]