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Zero-energy buildings have attracted great attention in China. Limited research about typical high-rise, zero-energy residential buildings in China was found. To figure out the potential of zero-energy buildings in northern China, a techno-economic analysis of a typical residential building adapted to the nearly zero energy building (NZEB) standards in the cold region of China was carried out in detail in this paper. Firstly, the feasibility of different building energy efficiency technologies was figured out in the passive design level. Secondly, the annual energy balance of the nearly zero-energy building model was investigated. Finally, detailed economic and environmental analyses were performed. The results show that the energy consumption of space heating and cooling of a typical high-rise, nearly zero-energy building could decrease to 11.1 kWh/(m2·a) in Beijing. The conclusions could provide a reference and design basis for the development of zero-energy residential buildings in northern China in the near future. [ABSTRACT FROM AUTHOR]

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m2 was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m2 and 2.0–32.6 MJ/m2 for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO2/m2 and 1.0–28.9 kgCO2/m2 for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively. [ABSTRACT FROM AUTHOR]

With the trend of achieving both energy efficiency in buildings and occupants' comfort, gamification strategies have started to be developed and applied as incentive mechanisms to increase social interaction and facilitate human energy behavior transformation. In this article, 306 published papers are reviewed, and 21 studies are identified to determine the challenges and potential for the development of gamification strategies to improve building energy efficiency. Specifically, this work reviews the implementation techniques of gamification and methods to assess the impact of gamification mechanisms on human energy behavior changes. This analysis demonstrates that, firstly, the choice of an optimal gamification implementation method should be inherently attuned to the distinct characteristics of the building type and its occupants. Secondly, it is imperative to strike a judicious balance between extrinsic and intrinsic motivations, in which customization of gamification design elements are based on users' unique personality traits and preferences, to properly tailor gamification mechanisms. Thirdly, integrating a fusion of quantification of energy savings and qualitative interpretation of user behaviors to improve the energy efficiency in buildings is essential for a more holistic understanding of the impact of gamification on users' energy-related behavior change. The findings indicate that gamification techniques can enable the effective reduction of energy consumption in buildings. [ABSTRACT FROM AUTHOR]

It difficult for buildings in cold regions to reasonably meet ultra-low energy consumption requirements. To explore the influencing factors of building energy consumption in this type of climatic region, this paper takes a typical public building in Zhengzhou, China as a case study to dynamically simulate an entire building. The influence of the window glass, window-to-wall ratio (WWR), thermal insulation material thickness and other factors on building energy consumption is considered. The sensitivity of envelope design factors to energy consumption is analyzed by the orthogonal test. The results indicate that the effect of changing the technical parameters of the external envelope structure on building energy efficiency is significant. Moreover, range analysis is used to determine the primary and secondary factors with regard to their influence on the energy consumption of the building. The WWR, the type of external window glass and the thickness of the external wall insulation layer should be considered first in energy-saving design; the energy-saving potential of the roof insulation thickness is not as significant as these factors. The results of the study can provide a reference for the energy-saving design of public buildings in Central China. [ABSTRACT FROM AUTHOR]

The traditional energy-saving evaluation method for industrial buildings is intended for all industrial buildings; however, substation buildings belong to a special category of industrial buildings, and their energy consumption characteristics are different from those of general industrial buildings. Consequently, it is necessary to establish an energy-saving evaluation system for substation buildings according to the characteristics of their energy consumption. In view of the issue that the energy consumption characteristics of substation buildings are different from those of other industrial buildings, an analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) are used to establish a more comprehensive energy saving evaluation model that is more applicable to substation buildings. This paper determines 19 quantitative indicators and 13 qualitative indicators through the screening of relevant standards and norms, as well as the literature, and then determines the weight of each indicator by using AHP before finally establishing a secondary evaluation model based on FCE. In this paper, a substation in Shandong, China was selected as a case study to verify the proposed evaluation model, scoring 80.4 points, which falls within the "Good" grade. This method is of great significance for the future establishment of energy-saving evaluation system for substation buildings. [ABSTRACT FROM AUTHOR]

Buildings consume a significant part of the world's resources and energy. The growing environmental awareness and urgent need to reduce energy consumption have highlighted the importance of introducing innovative solutions as nature-based systems in new buildings' construction and retrofitting. In this regard, green façades that integrate vegetation into building envelopes are attractive. This paper presents a bibliographic analysis, based on science mapping, of the available literature on green façades from 1999–2022 with a focus on the thermal effect on the building and on the surroundings. The objective of this study is to reveal the structure and the evolution of the research activity in the field, outlining the main research topics and the future research directions. The analysis was performed on a dataset of 270 documents. The results indicate a growing interest in this topic over the last six years and the multidisciplinary dimension of the studies. The keyword cluster analysis indicates the emergence of three main search topics: thermal behavior and energy modeling; urban design and large-scale effects; sustainable buildings management. A greater future dissemination of green façades could be enabled by further research results based on the application of a multidisciplinary approach and of standardized methods. [ABSTRACT FROM AUTHOR]

Single-side natural ventilation is a commonly used means of ventilation to effectively regulate the thermal environment in building interiors without any fossil energy consumption. To achieve most of the potential for the efficiency of single-side natural ventilation, research needs to be undertaken into the forces that drive single-side natural ventilation. This paper examines the single-side natural ventilation of a single vertical single opening (SSO) and a vertical double opening (SDO) in a freestanding building under wind and thermal pressure. The change in the trajectory of vortex shedding when the building is leeward as well as the frequency of vortex shedding in square buildings was investigated by large eddy simulation (LES), and computational fluid dynamics was used to analyze the difference in the air exchange rate of single-side natural ventilation of SSO and SDO in the windward and leeward conditions of the building. Both of these methods were used in conjunction with one another. According to the findings, the creation of vortices at SSO and SDO in the presence of low wind speeds reduces the ventilation effect of thermal pressure under windward circumstances. Consequently, the influence of thermal stress and wind stress ultimately cancel each other out, and this phenomenon finally disappears as the wind blowing from the outside of the structure increases. The shedding of vortices in the leeward state accomplishes a form of air supply pumping with a particular periodicity of airflow fluctuations in the lateral direction. The Strouhal number computed using the LES simulation acts in a manner consistent with the experimental findings. [ABSTRACT FROM AUTHOR]

PCMs are attractive for the future generation of buildings, where energy efficiency targets and thermal comfort expectations are increasingly prioritized. Experimental analysis of local thermal processes in these dynamic components and whole-building energy consumption predictions are essential for the proper implementation of PCMs in buildings. This paper discusses the experimental analysis of the thermophysical characteristics of both a latent heat storage material (PCM) and a product containing this PCM. The prototype product under investigation is a panelized PCM technology containing inorganic, salt-hydrate-based PCM. The thermal analysis includes studies of melting and freezing temperatures, enthalpy changes during phase change processes, nucleation intensity, sub-cooling effects, and PCM stability. The PCM's stability is also investigated, as is the ability of PCM products to control local temperatures and peak load transmission times. Two inorganic PCM formulations based on calcium chloride hexahydrate (CaCl2.6H2O) were prepared and tested in laboratory conditions. Material-scale testing results were compared with outcomes from the system-scale analysis, using both laboratory test methods as well as field exposure in test huts. This work demonstrates that PCM technologies used in buildings can effectively control both the magnitude of thermal storage capacity as well as the time of the peak thermal load. It was found that commonly used material-scale testing methods may not always be beneficial in assessing the dynamic thermal performance characteristics of building technologies containing PCMs. [ABSTRACT FROM AUTHOR]

The Renovation Wave for Europe highlighted the role of the public building stock for which Directive 2012/27/EU has set an annual renewal rate of 3%, which should rise to reach the goal of decarbonization by 2050. In this paper, the energy retrofit of an educational building—at the academic level—in Southern Italy was investigated. The aim was to evaluate the incentive share, which could accelerate the energy efficiency process, to achieve a cost-effective nZEB. The results show that the highest incentive rate is required for interventions on the opaque building envelope, which are also those that allow the least energy savings. An incentive rate of about 45% for the energy efficiency of the transparent envelope is necessary to reduce the payback time by about 7 years. The efficiency of the plants and the installation of a PV system are energetically and economically convenient even without forms of economic incentive. Finally, if the building is brought to high energy standards—a primary energy saving of 46% and energy class A3—an incentive rate of 40% is required to repay the intervention in about 10 years. [ABSTRACT FROM AUTHOR]

It has been suggested in the literature that by reducing the incoming voltage at a distribution feeder head or at the supply side of buildings, significant electricity savings can be achieved. This technique is called Conservation Voltage Reduction (CVR). Data-based analysis with and without CVR is primarily used to support such assertions, which does not explain the physics behind reduction in energy consumption with CVR. This paper presents a new approach for evaluating the impact of CVR on cooling equipment. In this approach, a thermal-electric model of the cooling process is developed in MATLAB's SIMSCAPE toolbox that can be used to explain the physics behind energy reduction with CVR. This model includes an accurate model of a compressor coupled to an induction motor whose supply voltage can be varied to simulate CVR. Simulations performed using this model show that the Coefficient of Performance (COP) of cooling equipment improves with a reduction in supply voltage. However, the energy lost in the motor windings may nullify the impact of the improvement in the COP and render the CVR programs ineffective if the range of speed change is small over the allowable voltage change. The simulation results show an increase in energy consumption of 4% at 90% rated voltage compared to the energy consumed at the rated voltage. However, if variable frequency drives-based cooling equipment is appropriately controlled, it is possible to reduce their net energy consumption using CVR. Simulations performed keeping the ratio of the supply voltage and the frequency constant showed a reduction in energy consumption of 2.5% at 90% rated voltage compared to the energy consumed at the rated voltage. Thermal-electric modeling of building cooling equipment is, therefore, vital to accurately evaluating the benefits of CVR as smart, power electronics-based end-use equipment is globally adopted. [ABSTRACT FROM AUTHOR]

Since approximately 75% of Europeans currently live in cities, and this number will rise, urban areas are the most important testbeds for energy transition, climate change adaptation measures, and decarbonisation models, on which studies and efforts for concrete change must focus. The teaching of mitigation and adaptation measures to climate change and decarbonisation models has gradually taken up space within university courses. However, the complexity of the decarbonisation issue is raising awareness on the urgency of an interdisciplinary approach that can be conveyed by spatial planning. Currently, this approach is not widespread in Higher Education Institutions in Europe but is nonetheless necessary to let new professional profiles emerge who are able to coordinate different stakeholders, data, and information sources. The Erasmus+ project CITY MINDED (2020–2022) has worked in this direction, by developing and testing a methodology for the design of a structured ordinary practice for teaching urban decarbonisation to students in Higher Education. This practice (at the same time, interdisciplinary, collaborative, experiential, and place-based) aims to offer students a combination of different approaches and working methods to investigate and improve urban neighbourhoods and districts, resulting in the definition of an operative roadmap for decarbonisation in the medium-to-long-term. The aim of this article is to highlight the learning-by-doing experience developed by the project consortium, with reference to the testing of the methodology conducted within an Intensive Course in the City of Valletta (Malta). In particular, the paper illustrates how this experience succeeded in stimulating students with different academic backgrounds to establish connections across disciplines, in raising their awareness about the complexity of city decarbonisation processes. Overcoming the strict time and budget constraints of an EU-funded project, such an approach can be further developed, replicated on theoretical grounds, and implemented within different degree programmes dealing with urban sustainability. [ABSTRACT FROM AUTHOR]

India's fossil-fuel-based energy dependency is up to 68%, with the commercial and residential sectors contributing to the rise of building energy demand, energy use, and greenhouse gas emissions. Several studies have shown that the increasing building energy demand is associated with increased space-cooling ownership and building footprint. The energy demand is predicted to grow further with the conditions of global warming and the phenomenon of urban heat islands. Building designers have been using state-of-the-art transient simulation tools to evaluate energy-efficient envelopes with present-day weather files that are generated with historical weather datasets for any specific location. Designing buildings with historical climatic conditions makes the buildings vulnerable to the predicted climate change impacts. In this paper, a weather file generator was developed to generate Indian future weather files using a geo-filtering-based spatial technique, as well as the temporal downscaling and machine learning (ML)-based bias correction approach proposed by Belcher et al. The future weather files of the three representative concentration pathways of 2.6, 4.5, and 8.5 could be generated for the years 2030, 2050, 2070, 2090, and 2100. Currently, the outputs of the second-generation Canadian Earth System Model are being used to create future weather files that will aid architects, urban designers, and planners in developing a built environment that is resilient to climate change. The novelty lies in using observed historical data from present-day weather files on the typical meteorological year for testing and training ML models. The typical meteorological weather files are composed of the concatenation of the monthly weather datasets from different years, which are referred to for testing and training ML models for bias correction. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative method for making cement-based composites from corn straw plants, and investigates the strength, thermal conductivity, and hydration characteristics of the composites. Corn straw is a natural, renewable, and breathable thermal insulation composite that contains cellular sealed pores. Corn straw contains a large amount of soluble cellulosic sugar, which hinders the hydration reaction of Portland cement and affects the use of corn straw as a building material. In this study, a 3 wt.% siliceous solution was used for surface treatment of corn straw particles to prevent cellulosic sugar from affecting the hydration performance of Portland cement. The composition of added cement-based composite materials with treated corn straw at the dosage of 11–20 wt.% was investigated. The test results showed that the corn straw cement-based composite (CSCC) had an optimal thermal conductivity of 0.102–0.112 (W/(m·K)) and a minimum compressive strength of above 1 MPa. The hydration performance of four typical CSCCs was examined using XRD, SEM, and EDS. The experimental results of this study may help to increase the comprehensive utilization of corn straw. The manufacturing method of the composite materials is simple, effective, and convenient for popularization and application, and it provides a new important technical measure to solve the problem of high energy consumption in rural houses. [ABSTRACT FROM AUTHOR]

The construction industry is recognized as a major cause of environmental pollution, and it is important to quantify and evaluate building energy. As interest in big data has increased over the past 20 years, research using big data is active. However, the links and contents of much literature have not been summarized, and systematic literature studies are insufficient. The objective of this study was a holistic review of building energy efficiency/reduction based on big data. This review study used a holistic analysis approach method framework. As a result of the analysis, China, the Republic of Korea, and the USA had the most published papers, and the simulation and optimization area occupied the highest percentage with 33.33%. Most of the researched literature was papers after 2015, and it was analyzed because many countries introduced environmental policies after the 2015 UN Conference on Climate Change. This study can be helpful in understanding the current research progress to understand the latest trends and to set the direction for further research related to big data. [ABSTRACT FROM AUTHOR]

Featured Application: Proper design of a chiller plant is considered as one of the most effective ways to reduce the energy consumption of commercial buildings. Due to the improper treatment of uncertainty and reliability, existing design methods in practice often result in oversized systems. This paper proposes a design optimization method for chiller plants based on life-cycle total cost minimization with quantified analysis of uncertainty and reliability. It can ensure a chiller plant operates at its high efficient region under various cooling load conditions and provide sufficient cooling capacity even some equipment/systems with failures. Conventional and most optimal design methods for chiller plants often address the annual cooling load distribution of buildings and their peak cooling loads based on typical meteorological year (TMY) data, while the peak cooling load only appears a few times during the life-cycle and the sized chiller plant usually operates within its low efficient region. In this paper, a robust optimal design method based on life-cycle total cost was employed to optimize the design of a chiller plant with quantified analysis of uncertainty and reliability. By using the proposed design method, the optimized chiller plant can operate at its highly efficient region under various cooling load conditions, and provide sufficient cooling capacity even alongside some equipment/systems with failures. The minimum life-cycle total cost, which consists of the capital cost, operation, and availability-risk cost, can be achieved through optimizing the total cooling capacity and the numbers/sizes of chillers. A case study was conducted to illustrate the detailed implementation process of the proposed method. The performance of this design method was evaluated by comparing with that of other design methods. [ABSTRACT FROM AUTHOR]

Featured Application: The use of this new regression method increases the available toolkit for system modeling and machine learning techniques. Their main advantages are simplicity and easy geometric meaning, allowing the treatment of a big class of modelling problems. The application to the study of a problem related with energy efficiency on buildings reviews a widely used dataset introducing some additional considerations that serve as a benchmark of the proposed methodology. System modeling is a main task in several research fields. The development of numerical models is of crucial importance at the present because of its wide use in the applications of the generically named machine learning technology, including different kinds of neural networks, random field models, and kernel-based methodologies. However, some problems involving the reliability of their predictions are common to their use in the real world. Octahedric regression is a kernel averaged methodology developed by the authors that tries to simplify the entire process from raw data acquisition to model generation. A discussion about the treatment and prevention of overfitting is presented and, as a result, models are obtained that allow for the measurement of this effect. In this paper, this methodology is applied to the problem of estimating the energetic needs of different buildings according to their principal characteristics, a problem that has importance in architecture and civil and environmental engineering due to increasing concerns about energetic efficiency and ecological footprint. [ABSTRACT FROM AUTHOR]

Our work is dedicated to enhancing sustainability through improved energy efficiency in buildings, with a specific focus on heating and cooling control and the optimization of thermal comfort of occupants. With an energy consumption of more than 60% in buildings, HVAC systems are the biggest energy users. By integrating advanced technology, data algorithms, and digital twins, our study aims to optimize energy performance effectively. We have developed a Neural Network-based Model Predictive Control (NNMPC) to achieve this goal. Leveraging technologies such as MQTT communication, Wi-Fi modules, and field-programmable gate arrays will enhance scalability and flexibility. Our findings demonstrate the efficacy of the NNMPC system deployed on the PYNQ board for reducing sensible thermal energy usage for both cooling and heating purposes. Compared to traditional On/Off control systems, the NNMPC achieved an impressive 40.8% reduction in heating energy consumption and a 37.8% decrease in cooling energy consumption in 2006. In comparison to the On/Off technique, the NNMPC demonstrated a 25.6% reduction in annual heating energy consumption and a 28.8% drop in annual cooling energy consumption in the simulated year of 2017. We observed that, across all strategies and platforms, there were no instances where the Predicted Mean Vote (PMV) fell below − 0.5 . However, a significant proportion of PMV values (ranging from 65% to 83%) were observed between − 0.5 and 0.5, signifying a high level of occupant comfort. Additionally, for PMV values between 0.5 and 1.0, percentages ranged from 16% to 33% for both years. Importantly, the NNMPC exhibited notable efficiency in maintaining occupants' comfort within this range, requiring less energy while ensuring highly satisfactory environments. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, researchers from different fields have been striving to improve the sustainability and proper utilization of energy resources. Passive radiative cooling, as a natural energy transport method, can achieve cooling without additional external energy input. This review provides a comprehensive examination of passive radiative cooling, including its fundamental theories and latest development. A particular emphasis is placed on the diverse range of fields where passive radiative cooling has been applied, notably including but not limited to construction and architecture. The current state of applications, potential challenges that may arise with wider adaption and promising research directions for each field are thoroughly discussed. This review emphasizes the extensive potential and practical viability of passive radiative cooling in diverse applications and identifies pressing challenges and future research directions aimed at scaling up real-world implementation. [ABSTRACT FROM AUTHOR]

The objective of energy transition is to convert the worldwide energy sector from using fossil fuels to using sources that do not emit carbon by the end of the current century. In order to achieve sustainability in the construction of energy-positive buildings, it is crucial to employ novel approaches to reduce reliance on fossil fuels. Hence, it is essential to develop buildings with very efficient structures to promote sustainable energy practices and minimize the environmental impact. Our aims were to shed some light on the standards, building modeling strategies, and recent advances regarding the methods of control utilized in the building sector and to pinpoint the areas for improvement in the methods of control in buildings in hopes of giving future scholars a clearer understanding of the issues that need to be addressed. Accordingly, we focused on recent works that handle methods of control in buildings, which we filtered based on their approaches and relevance to the subject at hand. Furthermore, we ran a critical analysis of the reviewed works. Our work proves that model predictive control (MPC) is the most commonly used among other methods in combination with AI. However, it still faces some challenges, especially regarding its complexity. [ABSTRACT FROM AUTHOR]

Buildings remain pivotal in global energy consumption, necessitating a focused approach toward enhancing their energy efficiency to alleviate environmental impacts. Precise energy prediction stands as a linchpin in optimizing efficiency, offering indispensable foresight into future energy demands critical for sustainable environments. However, accurately forecasting energy consumption for individual households and commercial buildings presents multifaceted challenges due to their diverse consumption patterns. Leveraging the emerging landscape of the Internet of Things (IoT) in smart homes, coupled with AI-driven energy solutions, presents promising avenues for overcoming these challenges. This study introduces a pioneering approach that harnesses a hybrid deep learning model for energy consumption prediction, strategically amalgamating convolutional neural networks' features with long short-term memory (LSTM) units. The model harnesses the granularity of IoT-enabled smart meter data, enabling precise energy consumption forecasts in both residential and commercial spaces. In a comparative analysis against established deep learning models, the proposed hybrid model consistently demonstrates superior performance, notably exceling in accurately predicting weekly average energy usage. The study's innovation lies in its novel model architecture, showcasing an unprecedented capability to forecast energy consumption patterns. This capability holds significant promise in guiding tailored energy management strategies, thereby fostering optimized energy consumption practices in buildings. The demonstrated superiority of the hybrid model underscores its potential to serve as a cornerstone in driving sustainable energy utilization, offering invaluable guidance for a more energy-efficient future. [ABSTRACT FROM AUTHOR]

Energy efficiency is currently a hot topic in engineering due to the monetary and environmental benefits it brings. One aspect of energy efficiency in particular, the prediction of thermal loads (specifically heating and cooling), plays a significant role in reducing the costs associated with energy use and in minimising the risks associated with climate change. Recently, data-driven approaches, such as artificial intelligence (AI) and machine learning (ML) techniques, have provided cost-effective and high-quality solutions for solving energy efficiency problems. This research investigates various ML methods for predicting energy efficiency in buildings, with a particular emphasis on heating and cooling loads. The review includes many ML techniques, including ensemble learning, support vector machines (SVM), artificial neural networks (ANN), statistical models, and probabilistic models. Existing studies are analysed and compared in terms of new criteria, including the datasets used, the associated platforms, and, more importantly, the interpretability of the models generated. The results show that, despite the problem under investigation being studied using a range of ML techniques, few have focused on developing interpretable classifiers that can be exploited by stakeholders to support the design of energy-efficient residential buildings for climate impact minimisation. Further research in this area is required. [ABSTRACT FROM AUTHOR]

The potential to reduce energy consumption in buildings is high. The design phase of the building is very important. In addition, it is vital to understand how to measure the energy efficiency in the building operation phase in order to encourage the right efficiency efforts. In understanding the building energy efficiency, it is important to comprehend the interplay of building occupancy, space efficiency, and energy efficiency. Recent studies found in the literature concerning energy efficiency in office buildings have concentrated heavily on the technical characteristics of the buildings or technical systems. The most commonly used engineering indicator for building energy efficiency is the specific energy consumption (SEC), commonly measured in kWh/m2 per annum. While the SEC is a sound way to measure the technical properties of a building and to guide its design, it obviously omits the issues of building occupancy and space efficiency. This paper studies existing energy efficiency indicators and introduces a new indicator for building energy efficiency which takes into account both space and occupancy efficiency. [ABSTRACT FROM AUTHOR]

Building energy consumption in China recently surpassed the US building consumption, and it is expected to increase significantly in the next decade pushed by the continuous population and urbanization increase. In response to that situation, the Chinese government introduced a series of building energy codes and rating systems to assess and enhance the building energy performance. The purpose of this study is to develop a rating system for the building energy efficiency, based on in situ measurement. The system is intended for office buildings in China's cold zone. An evaluation framework, graphic dominant point, and principle of data collection and processing are illustrated in this paper. Three existing buildings were rated under the new rating system. The authors believe that the new system will contribute to a more accurate and comprehensive understanding for asset holders and occupants, that report on the extent to which energy efficiency buildings have been reached. Rating results are expected to be a reference for the retrofitting of existing buildings and the design of new buildings. In addition, the outlook for the rating system was also discussed. [ABSTRACT FROM AUTHOR]

Pursuing innovations in sustainable architectural solutions, this study examines the impact of a climate-adaptive building envelope with dynamic photovoltaic integrated shading devices (PVSDs) on building performance. A major challenge in designing PVSDs is the lack of established guidelines for geometry and operations. We delve into the complexities and potential benefits of integrating dynamic PVSD designs into building performance simulations, particularly considering their time-varying geometric and operational aspects. This research assesses a range of similar PVSD design options with differing patterns, emphasizing their effects on solar energy potential, daylighting, and thermal efficiency. We conducted tests on south-oriented PVSDs (featuring two-axis rotation) in Houston, Texas, focusing on variables such as panel count (4 or 36), rotation angle range, and operational patterns (synchronized or individual). Regarding solar potential, the four-panel synchronized PVSD option outperformed static shading by 2.1 times. For daylighting and thermal performance, the 36-panel synchronized option with a wide rotation range and the four-panel individual option proved superior to other PVSD configurations, improving up to an average of 36% (sDA300/50%) and 1.5 °C, respectively. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness and highlight PVSD design and application limitations. Our findings emphasize the critical role of integrating geometric design and operational patterns in PVSDs for enhanced system effectiveness. Furthermore, they shed light on the limitations in the PVSD design process and practical applications. [ABSTRACT FROM AUTHOR]

The research about energy efficiency in buildings has exponentially increased during the last few years. Nevertheless, both research and practice still cannot rely on complete methodologies tailored for building portfolios as a whole, because the attention has always been drawn to individual premises. Yet, energy efficiency analyses need to go beyond the single building perspective and incorporate strategic district approaches to optimize the retrofit investment. For this purpose, several aspects should be considered simultaneously, and new methodologies should also be promoted. Therefore, this paper aims to discuss energy retrofit campaigns in building portfolios, drawing an exhaustive and updated review about the challenge of jumping from the single-building perspective to a stock-based analysis. This research discusses the publications available on the topic from five key aspects that are all essential steps in achieving a complete and reliable study of energy efficiency at a portfolio level. They are energy modelling and assessment, energy retrofit design, decision-making criteria assessment, optimal allocation of (financial) resources and risk valuation. This review, therefore, advocates for joint consideration of the problem as a basis on which to structure further disciplinary developments. Research gaps are highlighted, and new directions for future research are suggested. [ABSTRACT FROM AUTHOR]

Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well. [ABSTRACT FROM AUTHOR]

A large amount of the Iranian energy demand is related to the building sector, mainly due to its obsolescence. In this paper, a second-skin system has been implemented as a retrofit action for an office building, evaluating the effect of a tensile material as second-skin in terms of primary energy saving, carbon dioxide equivalent emissions, and simple payback period. The analysis was carried out through numerical simulations across a whole year and for four Iranian cities (Tabriz, Teheran, Yazd, and Bandar Abbas) in four different climates (cold, temperate, hot-dry, and hot-wet), and with the building aligned at either north-south or east-west. Moreover, an economic analysis was carried out suggesting different incentive policies to promote building energy refurbishment. The simulation results highlighted a favorable orientation for buildings in Iran, suggesting a guideline for new constructions. Indeed, the best results were achieved for an east-west orientation of the building (up to a primary energy saving of 13.6% and reduction of carbon dioxide equivalent emissions of 45.5 MgCO2,eq, in Yazd), with a decrease of the annual specific total (cooling and thermal) energy demand of 37.9 kWh/m2/year. The simple payback period values were also lower in the east-west orientation than the north-south one. [ABSTRACT FROM AUTHOR]

Building energy efficiency is strongly linked to the operations and control systems, together with the integrated performance of passive and active systems. In new high quality buildings in particular, where these two latter aspects have been already implemented at the design stage, users' perspective, obtained through post-occupancy assessment, has to be considered to reduce whole energy requirement during service life. This research presents an innovative and low-cost methodology to reduce buildings' energy requirements through post-occupancy assessment and optimization of energy operations using effective users' attitudes and requirements as feedback. As a meaningful example, the proposed method is applied to a multipurpose building located in New York City, NY, USA, where real occupancy conditions are assessed. The effectiveness of the method is tested through dynamic simulations using a numerical model of the case study, calibrated through real monitoring data collected on the building. Results show that, for the chosen case study, the method provides optimized building energy operations which allow a reduction of primary energy requirements for HVAC, lighting, room-electricity, and auxiliary supply by about 21%. This paper shows that the proposed strategy represents an effective way to reduce buildings' energy waste, in particular in those complex and high-efficiency buildings that are not performing as well as expected during the concept-design-commissioning stage, in particular due to the lack of feedback after the building handover. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new HVAC (heating, ventilation, and air conditioning) control strategy as part of the smart energy system that can balance occupant comfort against building energy consumption using ubiquitous sensing and machine learning technology. We have developed ZigBee-based wireless sensor nodes and collected realistic temperature and humidity data during one month from a laboratory environment. With the collected data, we have established a building environment model using machine learning algorithms, which can be used to assess occupant comfort level. We expect the proposed HVAC control strategy will be able to provide occupants with a consistently comfortable working or home environment. [ABSTRACT FROM AUTHOR]

In this paper, we developed a new integrated analysis environment in order to thoroughly analyses urban-building energy patterns, named IUBEA (integrated urban building energy analysis), which focuses on energy modeling and analysis of a city's building stock to support district or city-scale efficiency programs. It is argued that cities and towns account for more than two-thirds of world energy consumption. Thus, this paper explores techniques to integrate a spatial analysis environment in the field of urban building energy assessment in cites to make full use of current spatial data relevant to urban-building energy consumption and energy efficiency policies. We illustrate how multi-scale sampling and analysis for energy consumption and simulate the energy-saving scenarios by taking as an example of Greater London. In the final part, is an application of an agent-based model (ABM) in IUBEA regarding behavioral and economic characteristics of building stocks in the context of building energy efficiency. This paper first describes the basic concept for this integrated spatial analysis environment IUBEA. Then, this paper discusses the main functions for this new environment in detail. The research serves a new paradigm of the multi-scale integrated analysis that can lead to an efficient energy model, which contributes the body of knowledge of energy modeling beyond the single building scale. Findings also proved that ABM is a feasible tool to tackle intellectual challenges in energy modeling. The final adoption example of Greater London demonstrated that the integrated analysis environment as a feasible tool for building energy consumption have unique advantages and wide applicability. [ABSTRACT FROM AUTHOR]

As building systems account for almost half of the total energy consumed by the building sector to provide space heating, cooling, and ventilation, efficiently designing these systems can be the key to energy conservation in buildings. Dual VAV systems with an effective control strategy can substantially reduce the energy consumption in buildings, providing a significant scope of further research on this system configuration. This paper proposes to utilize the warm air duct of the dual VAV system as a dedicated outdoor air (DOA) unit when no heating is required, which allows the cooling load to be effectively distributed between two ducts. A specific control sequence is proposed with different supply air temperature reset strategies to estimate the heating, cooling loads, and fan power energy consumption of the proposed system. A simple two-zone office building is taken as a preliminary case study to simulate the airflow rates and fan power of a single duct VAV and proposed dual VAV systems to illustrate the concept. Finally, a larger multi-zone office building is simulated to measure the annual heating, cooling loads, and fan power energy and compare the energy savings among the systems. The results show significant fan power reduction ranging from 1.7 to 9% and notable heating energy reduction up to 76.5% with a small amount of cooling load reduction varying from 0.76 to 2.56% depending on the different locations for the proposed dual VAV systems. Further energy savings from different supply air temperature reset strategies demonstrate the opportunity of employing them according to climates and case studies. The proposed dual VAV system proves to have the potential to be adapted in buildings for the purpose of sustainability and energy savings. [ABSTRACT FROM AUTHOR]

Cooling energy consumption is a major contributor to various sectors in hot climates with a significant number of warm days throughout the year. Buildings account for 40% of total energy consumption, with approximately ∼30–40% of that used for cooling in geographical areas such as Iran. Energy demand for cooling is an important factor in the overall energy efficiency of electric mobility. Electric vehicles (EVs) consume ∼30–50% of energy for the air conditioning (AC) system. Therefore, the efficient management of the cooling demand is essential in implementing energy-saving strategies. Passive radiative cooling is capable of providing subambient cooling without consuming any energy. This article reviews potential applications of passive radiative cooling in reducing cooling energy for buildings. It also provides a rough estimate of the amount of energy saved when applying a radiative cool roof to a model building. It is shown that by using radiative cool materials on roofs, the share of electricity usage for cooling can be reduced to 10%, leading to a reduction in cooling load by 90%. Additionally, the potential use of radiative cool coats of various types for different EV components, such as shell/body, windows, and fabrics, is introduced. Although the prospects of the design and engineering of radiative cooling products appear promising for both buildings and EVs, further investigations are necessary to evaluate scalability, durability, and performance based on factors such as geography and meteorology. [ABSTRACT FROM AUTHOR]

The development of high-performance insulation materials that facilitate the reduction in building energy consumption is of paramount significance. In this study, magnesium–aluminum-layered hydroxide (LDH) was prepared by the classical hydrothermal reaction. By implementing methyl trimethoxy siloxane (MTS), two different MTS-functionalized LDHs were prepared via a one-step in situ hydrothermal synthesis method and a two-step method. Furthermore, using techniques, such as X-ray diffraction, infrared spectroscopy, particle size analysis, and scanning electron microscopy, we evaluated and analyzed the composition, structure, and morphology of the various LDH samples. These LDHs were then employed as inorganic fillers in waterborne coatings, and their thermal-insulation capabilities were tested and compared. It was found that MTS-modified LDH via a one-step in situ hydrothermal synthesis method (M-LDH-2) exhibited the best thermal insulating properties by displaying a thermal-insulation-temperature difference (ΔT) of 25 °C compared with the blank panel. In contrast, the panels coated with unmodified LDH and the MTS-modified LDH via the two-step method exhibited thermal-insulation-temperature difference values of 13.5 °C and 9.5 °C, respectively. Our investigation involved a comprehensive characterization of LDH materials and coating films, unveiling the underlying mechanism of thermal insulation and establishing the correlation between LDH structure and the corresponding insulation performance of the coating. Our findings reveal that the particle size and distribution of LDHs are critical factors in dictating their thermal-insulation capabilities in the coatings. Specifically, we observed that the MTS-modified LDH, prepared via a one-step in situ hydrothermal approach, possessed a larger particle size and wider particle size distribution, resulting in superior thermal-insulation effectiveness. In contrast, the MTS-modified LDH via the two-step method exhibited a smaller particle size and narrow particle size distribution, causing a moderate thermal-insulation effect. This study has significant implications for opening up the potential for LDH-based thermal-insulation coatings. We believe the findings can promote the development of new products and help upgrade industries, while contributing to local economic growth. [ABSTRACT FROM AUTHOR]

An increasing number of U.S. cities require commercial/office properties to publicly disclose their energy performance due to the adoption of energy benchmarking and disclosure policies. This level of transparency provides an additional in-depth assessment of a building's performance beyond a sustainability certification (e.g., Energy Star, LEED) and may lead less energy-efficient buildings to invest in energy retrofits, therefore improving their marketability. However, the research is scarce on assessing the impact of such policies on office building marketability. This study tries to fill this gap by investigating the impact of energy benchmarking policies on the performance of office buildings in four major U.S. cities (New York; Washington, D.C.; San Francisco; and Chicago). We use interrupted time series analysis (ITSA), while accounting for sustainability certification, public policy adoption, and property real estate performance. The results revealed that in some cities, energy-efficient buildings generally perform better than less energy-efficient buildings after the policy implementation, especially if they are Class A. The real estate performances of energy-efficient buildings also exhibited continuously increasing trends after the policy implementation. However, due to potentially confounding factors, further analysis is required to conclude the policy impacts on energy-efficient buildings are more positive than those on less energy-efficient buildings. [ABSTRACT FROM AUTHOR]

Highlights: What are the main findings? What is the implication of the main findings? Proposal of a BIM-based framework for lifecycle carbon prediction and optimisation. Proposal of a standard method with generic formulations to calculate the embodied carbon. Exploration of BIM-enabled parametric modelling for optimising low-carbon alternative design. Exploration of the interoperability between BIM and energy simulation for lifecycle energy analysis. Investigation of low-carbon materials and designs in the lifecycle carbon of residential buildings. Residential building construction is resource-intensive and significantly impacts the environment by embodied and operational carbon emissions. This study has adopted a parametric building information modelling (BIM)-based approach for a residential building to analyse its lifecycle carbon performance and to evaluate the optimisation potential through alternative material use and design. The study looks at a residential development project, applying an automatic calculation and analysis tool of upfront embodied carbon and BIM-based lifecycle energy simulation to predict carbon emissions from operating the built spaces. A parametric BIM model has been established to aid energy simulation and operational carbon assessment across a 50-year building lifetime, considering 1.5 °C Net-Zero World and 3 °C Hot House World climate scenarios. Various improvement opportunities for future residential development projects, from material selection to operational efficiencies, are explored. This includes quantitative analysis on architectural-structure design, low-carbon construction materials (e.g., cement substitutes, steel scraps, and green hydrogen steel), and novel design for construction approaches (such as modular integrated construction), with discussion around their impacts on optimising the building lifecycle carbon performance. This study provides a deeper understanding and insights into the lifecycle performance of residential buildings to facilitate further exploration of achieving a more sustainable and low-carbon built environment. [ABSTRACT FROM AUTHOR]

An earth-to-air heat exchanger (EAHE) system utilizes the low-grade thermal energy of underground soil to warm up and cool down the flowing air within an underground buried pipe. Integrating the EAHE system with building ventilation can reduce the energy demand for conditioning ventilation air. The main purposes of this paper are to estimate the year-round energy-saving potential of the EAHE-assisted building ventilation system and provide its design guidelines in a hot-summer and cold-winter climate. A steady-state heat transfer model was proposed to calculate the outlet air temperature of an EAHE and further identify its ability to preheat and precool ventilation air. Influences of depth, length, and diameter of a buried pipe on the year-round thermal performance of the EAHE system were evaluated. The results show that considering the compromise between thermal performance and construction costs of the EAHE system, a depth of 5 m and a length of 80 m are recommended. The EAHE system can provide a mean daily cooling and heating capacity of 19.6 kWh and 19.3 kWh, respectively. Moreover, the utilization of the EAHE system can reduce by 16.0% and 50.1% the energy demand for cooling and heating ventilation air throughout the whole year. [ABSTRACT FROM AUTHOR]

The energy issue has given rise to a prolific research field, which branches into several strands. One of these strands focuses on the role played by building energy features in shaping property prices. Indeed, market players are expected to show a higher willingness to pay for building units characterized by higher energy performance. The study of the so-called price premium for building energy efficiency has flourished in the last decade or so; plenty of evidence is now available concerning its occurrence, although its magnitude is still debated. The literature relies on the methodological frameworks of statistical modeling and multiple regression, primarily employing hedonic price models. Lately, spatial autoregressive models have also been adopted. Here, we propose to deal with estimation of the price premium by adopting an innovative perspective. In particular, we use a methodological framework in which regression models are complemented with a multi-criteria optimization approach. Using a spatial autoregressive model first, and with D as the reference energy rating band, we find the following price premiums: 55% for A4, 42% for A3 to A, 20% for B or C, −14% for F, and −29% for G. The multi-criteria optimization approach proves efficient in estimating the price premium. The estimates above are essentially confirmed: the results converge for all the energy rating bands except for G. [ABSTRACT FROM AUTHOR]

Passive houses have strong thermal insulation and airtightness of doors and windows, and they are generally used in cold climates. This case study aims to evaluate the energy-saving potential of this technology in the hot-summer and cold-winter areas (Cf in Köppen climate classification) of China. The results show that after enhancing the thermal insulation and airtightness, the energy consumption in winter significantly decreased by 62% overall. However, the energy consumption of cooling in the transition season and summer increased, which is caused by overheating. Hybrid ventilative cooling and shading can solve this problem. In particular, when the indoor temperature range is set to the adaptive thermal comfort of natural ventilation, the energy consumption from air conditioner cooling can be greatly reduced by 81% overall. Passive houses combined with ventilative cooling has significant application value in this climate zone. [ABSTRACT FROM AUTHOR]

Building energy optimization (BEO) is a promising technique to achieve energy efficient designs. The efficacy of optimization algorithms is imperative for the BEO technique and is significantly dependent on the algorithm hyperparameters. Currently, studies focusing on algorithm hyperparameters are scarce, and common agreement on how to set their values, especially for BEO problems, is still lacking. This study proposes a metamodel-based methodology for hyperparameter optimization of optimization algorithms applied in BEO. The aim is to maximize the algorithmic efficacy and avoid the failure of the BEO technique because of improper algorithm hyperparameter settings. The method consists of three consecutive steps: constructing the specific BEO problem, developing an ANN-trained metamodel of the problem, and optimizing algorithm hyperparameters with nondominated sorting genetic algorithm II (NSGA-II). To verify the validity, 15 benchmark BEO problems with different properties, i.e., five building models and three design variable categories, were constructed for numerical experiments. For each problem, the hyperparameters of four commonly used algorithms, i.e., the genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, simulated annealing (SA), and the multi-objective genetic algorithm (MOGA), were optimized. Results demonstrated that the MOGA benefited the most from hyperparameter optimization in terms of the quality of the obtained optimum, while PSO benefited the most in terms of the computing time. [ABSTRACT FROM AUTHOR]

Globally, the residential sector consumes a significant amount of energy. Therefore, bioclimatic architectural systems which consider passive solutions should be studied, analyzed, and implemented to reduce energy consumption. This review aims to promote thermal comfort in African countries by using passive solar systems. It begins with the keyword thermal comfort and then reviews articles published over the last ten years that consider bioclimatic architecture and construction strategies in Africa, the main trends in scientific research in this field, and the possibilities for each climate zone in achieving the highest degree of climate comfort. Following an extensive review, certain bioclimatic architectural strategies adopted in specific countries can be applied in countries with similar climates and this can contribute to significant energy savings through effective functional solar and ventilation design strategies. Several countries have been identified as having the most significant publications on thermal regulations in buildings, and the associated regulations and projects are discussed. Several studies have also examined static and adaptive models of thermal comfort. [ABSTRACT FROM AUTHOR]

Climate is a key element in building design. The determination of adequate climate zoning is crucial for achieving building energy efficiency and reduced carbon emissions. In this study, a cluster analysis method was applied to develop new thermal climate zones for building envelope thermal design in China. In total, three different cluster analysis methods, including k-means, average-linkage, and Ward's clustering, were considered. The analysis indicated that the average-linkage clustering was more appropriate for this study, and the elbow method could not accurately determine the best number of categories of average-linkage clustering. Further analysis showed that the unsupervised cluster processes may generate an unavoidable redundancy category and, to obtain precise results, supervision may be necessary in some contexts. Finally, China was classified into 10 climate zones. The North China plain and Qinghai–Tibet plateau are classified into two independent climate zones, and Turpan and Bayanbulak were classified into two newly defined climate zones different from their surrounding area in the new definition. Quantitative analysis indicated that the new zones were more precise when compared to the current ones, which can provide more precise climate information and contribute to formulating more precise standards and policies related to the thermal design of building envelopes in the future. [ABSTRACT FROM AUTHOR]

In order to accurately analyze the building energy consumption and identify the problem of building energy consumption in advance, this study carries out the energy consumption analysis based on BIM (Building Information Modeling). The research object is a four-story college student dormitory in Beijing, and this set of BIM-based energy consumption simulation data was obtained using standard operating procedures (SOP). This operating procedure can start energy consumption analysis in the conceptual design stage, and developers can participate in real-time through the use of a three-dimensional information model, without additional design required. Then, comparing this study with the traditional energy consumption analysis, we see that the SOP of this research result has the following advantages: SOP function analysis is more professional, and the visual display method is more popular and intuitive; due to the flexible file format of the SOP, when data exchange is required between different software, the SOP can realize more convenient operation, and users can identify problems in the early stage of design through the SOP, correcting the scheme according to the simulation results, which is conducive to the development of the construction process. Finally, this study puts forward the analysis and estimation of energy consumption in different stages of the building life cycle, so as to provide researchers with ideas for improvement. [ABSTRACT FROM AUTHOR]

It is estimated that almost 40% of the world's energy is consumed by buildings' heating, ventilation, and air conditioning systems. This consumption increases by 3% every year and will reach 70% by 2050 due to rapid urbanisation and population growth. In Darwin, building energy consumption is even higher and accounts for up to 55% due to the hot and humid weather conditions. Singapore has the same weather conditions but less energy consumption, with only 38% compared to Darwin. Solar radiation can be defined as electromagnetic radiation emitted by the Sun and the Darwin area receives a large amount of solar radiation; building energy consumption can be reduced hugely if this radiation is blocked effectively by analysing appropriate shading devices. This study investigated the influence of different types of shading devices on the cooling load of a town hall building located in Darwin, Australia, and proposed the optimal shading device. The results showed that the horizontal fins led to a 5% reduction in the cooling load of the building. In contrast, adding a variation to the device angles and length increased the savings to 8%. The results demonstrated that the overhangs were more efficient than the fins, contributing 9.2% energy savings, and the cooling reduction savings were increased to 15.5% with design and length variations. [ABSTRACT FROM AUTHOR]

Recently, Korea has become increasingly interested in unused, but possibly useful energy resources, due to the world-wide controversy over nuclear power and limitations in renewable energy production. Among these unused resources, the water that is produced in our surroundings is available as a potential energy source for heating, cooling and domestic hot water. This water is relatively stable on the supply side, available as a high-efficiency source in all seasons, and is continuously replenished without polluting the environment. This paper analyses the energy savings generated based on the actual use of a sustainable heating and cooling system that operates using the water escaping from a nearby building. The results indicate the value of protecting the environment as well as reducing energy consumption and associated costs. [ABSTRACT FROM AUTHOR]

Tourism represents an important economic driver in Italy, being responsible for approximately 13.2% of the total GDP (a value higher than the reference European average) and for nearly 10% of the regional GDP. Among the touristic sectors, the agritourist ones show a persistent growth, experiencing in 2019 a 6.7 point percentage improvement compared to the 2017 figures. Given this situation, the transition towards a low-carbon path, affecting the building sector for some time, should also involve agritourist buildings, through the release of EU directives, member state laws, and technical rules. On the other hand, agritourism sites could be awarded the Community EU Ecolabel. Unfortunately, awarding the EU environmental excellence brand implies the availability of several data on building energy behavior that should then be managed by complex evaluation tools. To overcome this issue, the use of the simplified ARERA (Italian Regulatory Authority for Energy Networks and Environment) technical datasheets, issued to assess environmental improvements consequent to energy efficiency interventions in the urban residential building stock, is proposed. The application of this tool totally avoids using building computer-based simulation models, thus facilitating the preparation of the EU Ecolabel request documentation by agritourism owners. Being awarded the Community EU Ecolabel also implies approaching a net zero energy condition because of a lower energy consumption and a minor recourse to fossil fuels. For this purpose, an application of an easy graphical method, previously developed for residential and commercial buildings, which visually represents improvements achievable by a given agritourism when implementing energy efficiency measures, is presented. [ABSTRACT FROM AUTHOR]

Active building envelopes that act as energy converters—gathering on-site available renewable energy and converting it to thermal energy or electricity—is a promising technological design niche to reduce energy consumption in the building sector, cut greenhouse gas emissions, and thus tackle climate change challenges. This research adds scientific knowledge in the field of composite building envelope structures containing phase-change materials for thermal energy storage. In this study, the focus lies on the cooling phase of the diurnal gain and release of solar energy. The experimental setup imitates day and night environment. Six alterations of small-scale solar facade modules are tested in two different configurations—with and without the adjustable insulation layer on their outer surface during the discharging phase. Modules explore combinations of aerogel, air gap, and Fresnel lenses for solar energy concentration. The results allow us to compare the impact of the application of an additional insulation layer at "night" for different designs of solar facade modules. The results show that modules with an air gap provide higher heat gains but do not take full advantage of the latent heat capacity of phase-change materials. [ABSTRACT FROM AUTHOR]

The building sector is responsible for 50% of worldwide energy consumption and 40% of CO2 emissions. Consequently, a lot of research on Building Energy Efficiency has been carried out over recent years, covering the most varied topics. While many of these themes are no longer of interest to the scientific community, others flourish. Thus, reading trends within a field of knowledge is wise since it allows resources to be directed towards the most promising topics. However, there is a paucity of research on trend analysis in this field. Therefore, this article aims to analyse the evolution of the Building Energy Efficiency field of knowledge, identifying the recurrent themes and pointing out their trends, supported by statistical methods. Such an analysis relied on more than 9000 authors' keywords collected from 2000 articles from the Scopus database and classified into 30 topics/themes. A frequency distribution of these themes enabled us to distinguish those most published as well as those whose academic interest has cooled down. This field of knowledge has evolved over three distinct phases, throughout which, eight themes presented an upward trend. These findings can assist researchers in optimising time and resources, investigating the topics with growing interest, and possibilities for new contributions. [ABSTRACT FROM AUTHOR]

Owing to movement in the spatial environment and changes in activity levels, students' thermal perception is time varying in classrooms throughout different periods of the day. However, previous studies have rarely considered the time-varying thermal perception in different periods of the day, which may cause discomfort for students and lead to energy wastage. Therefore, a study was conducted to investigate the time-varying thermal perception of students and its influencing factors in different classes of the day. In addition, the differences in students' adaptive behaviors in different periods were also explored. A total of 578 university students were surveyed using questionnaire surveys during the heating season in Xi'an, China. The following results can be obtained: (1) The thermal sensation vote and thermal preference vote values in the afternoon were significantly higher than those in the morning. At the start of the first class in the morning/afternoon, the thermal sensation of the students had the highest sensitivity to outdoor temperature changes. (2) The students' thermal perception was greatly affected by the preclass activity state at the start of the first class in the morning/afternoon. However, in other periods, the above phenomenon was not obvious. (3) In the afternoon, the frequency of clothing adjustment was greater than that in the morning, and this behavior would significantly affect the students' thermal sensation. (4) Compared with the current classroom heating strategy, the heating strategy of dynamically adjusting the indoor set temperature according to the time-varying characteristics of the students can theoretically achieve energy savings of 25.6%. [ABSTRACT FROM AUTHOR]

Increasing energy demand in buildings with a 40% global share and 30% greenhouse gas emissions has accounted for climate change and a consequent crisis encouraging improvement of building energy efficiency to achieve the combined benefit of energy, economy, and environment. For an efficient system, the optimization of different design control strategies such as building space load, occupancy, lighting, and HVAC becomes inevitable. Therefore, interdisciplinary teamwork of developers, designers, architects, and consumers to deliver a high-performance building becomes essential. This review aims to endorse the importance of Building Performance Simulation in the pre-design phase along with the challenges faced during its adaptation to implementation. A morphology chart is structured to showcase the improvement in Building Energy Efficiency by implementing Building Performance Simulation for different building energy systems and by implementing various energy efficiency strategies to achieve the 3E benefit. As a developing nation, India still lacks mass application of Building Performance Simulation tools for improving Building Energy Efficiency due to improper channelizing or implementation; thus, this framework will enable the designers, architects, researchers to contemplate variable building energy optimization scenarios. [ABSTRACT FROM AUTHOR]

The high concentration of pollutant sources, complex topography, and regional meteorology are all factors that may contribute to air episodes in dense urban areas. Energy use in buildings is a significant source of pollution in the Greater Athens Area (GAA), Greece, where over 90% of the existing building stock has been classified below energy class B. The present study focuses on the potential effects that a realistic level of building energy efficiency upgrades will have on the air quality over the GAA. Results are expected to be relevant to similar urban areas. Furthermore, the study of primary pollutants' dispersion is applied at a 1.2 × 1.2 km spatial resolution, providing significant local (neighborhood) level information. Numerical simulations were performed using EPA's CALPUFF modeling system with wind field input from an independent numerical weather prediction using NCAR's Weather Research and Forecasting (WRF) model. In order to calculate emission rates from major roads, highways, shipping ports, residential heating installations, and major industrial facilities, data were taken from National and European statistics, demographics, and local topography. After validation, the modeling system was used to examine three building energy efficiency upgrade scenarios, implemented on 20% of the buildings. Ground level concentrations of SO2, NOx, CO, and PM10 were calculated and reductions of up to 9% were found for GAA maximum values but up to 18% for local values that were also close to or above the European safety thresholds. [ABSTRACT FROM AUTHOR]