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• Affordable and adaptable VIP based internal and external retrofitting solutions. • Implementation of VIP based integral retrofitting solutions in two tertiary buildings. • Space heating energy saving analysis before and after VIP based retrofit. • Envelope heat loss coefficient reduction analysis before and after retrofitting. Vacuum insulation panels (VIPs) represent a huge opportunity to achieve nearly zero energy buildings, especially in the retrofitting of existing buildings. VIPs can be applied in conjunction with façade cladding elements, considerably reducing the heat losses or gains from the building by means of very slim wall construction systems or retrofit solutions. However, the fact that VIPs cannot be cut on-site, can be easily damaged during their handling, installation and use and have an envelope that can cause thermal bridging in the junction between panels or when combined with other materials, has hindered their penetration in the construction market. This paper presents two innovative façade retrofitting solutions, a rear ventilated façade and a stud mounted internal solution, that have tackled all these issues and provide thermal transmittances of 0.28 and 0.14 W/m2 K in relatively slim insulation systems of 10 cm widths. Solutions have been installed on the entire façade of two existing buildings located in Bilbao (Spain) and Malmö (Sweden) subjected to an integral rehabilitation process, covering 2100 m2. Buildings energy use have been monitored before and after the renovation, showing energy cuts of around 35% from pre-intervention status. This paper presents the lessons learnt during the design and installation process of the vacuum insulation integrating solutions in the façade of two existing buildings and the thermal performance results achieved after their retrofitting. [ABSTRACT FROM AUTHOR]

Abstract Recently developed generation of high-performance skins greatly leads to the emersion of innovative manufactures integrating real-time environmental response, enhanced materials, dynamic automation with built in microprocessors, wireless sensors and actuators, and design-for-manufacture techniques. This application has basically alter the thinking way of architects in the early design stages of the building with a shifting in importance from form to performance, from structure to envelope. In the field of high-performance buildings, the envelope begins to be the setting of research and development. The aim of the paper is to discuss the design of three strategies used in constructing adaptive building envelopes of multistory buildings, integrating improved energy performance and architectural innovation, in order to Control the physical environmental factors (heat, light, sounds), as well as improving occupants' comfort. Finally, three case studies are analyzed to unveil the implementation of these strategies on constructing structures and study their effects on the building energy savings. Scope and objective The objective of this paper is to illustrate and discuss new conceptual ways of designing adaptive building envelopes of multistory structures that respond to environmental changes in the surrounding climate of different places in the world, and how the usage of such adaptive envelopes can help reduce the energy consumption of the building. Methodology The literature survey will first discuss the characteristics and properties of high performance facades. After that, the paper present and analyze existing examples and ideas of adaptive envelopes, gaining an overall understanding of the concept of three adaptive building envelopes. In addition, at the same time develop knowledge of the materials commonly used and how they perform. Finally, three case studies are presented to analyze the implementation of the three adaptive envelopes strategies and observe their effects on the building energy savings. [ABSTRACT FROM AUTHOR]

This paper analyzes electricity use in buildings and explores key research questions related to assessing, rating, labeling, and benchmarking building energy use. The analysis reviews annual Energy Use Intensity (EUI) data from 3060 fully electric-powered buildings across six categories: residential, educational, offices, hospitals, hotels and restaurants, and wholesale and retail trade services. One-fifth of the analyzed buildings is derived from an energy dataset that offers a higher time-scale resolution, providing more detailed insights into energy usage patterns. The analysis employs various factors, including the seasonal variation factor (SVF), daily variation factor (DVF), monthly factor (M f), and hourly factor (H f), to gain a detailed understanding of actual energy usage at different time scales. The findings indicate that electricity use is less sensitive to seasonal variations than other energy carriers that provide heating and cooling. The paper provides hourly and monthly peak load percentages (PPL), which can indirectly assist in assessing hourly schedules for building energy performance simulations. The monthly energy use pattern varies between building categories, with high-energy months alternating between winter and summer. For non-residential buildings, high-energy hours correspond directly to the daytime, while for residential buildings, there is a shift towards the evening, and the daily amplitude is lower. Furthermore, the analysis of daily and monthly variability of heating energy carriers, even if non-electric, sheds light on the implications of electrification for these loads. • The study evaluates annual electricity data from 3060 fully electric-powered buildings. • Median EUIs are meaningful energy performance benchmarks by building category. • Residential and educational buildings exhibit EUIs of 90-120 kW h/m2. • Offices and hospitals demonstrate EUIs of 160-170 kW h/m2. • Monthly and hourly factors establish energy benchmarks for finer time resolution. [ABSTRACT FROM AUTHOR]

Building performance simulation is a powerful tool applied both in research and for building design including heating, ventilation, and air-conditioning systems. Several research studies have used this tool to investigate the potential of energy savings measures for swimming facilities. However, in these facilities the technical complexity is a considerable challenge in modelling since many complex phenomena occur in the various sub-systems. The building industry traditionally plans and design these complex buildings by heuristic rules of thumb, and these empirical design rules may lead to significant differences between real and predicted performance. Therefore, it's important to develop simplified models with acceptable accuracy for simulation-based design of swimming facilities. The scientific literature introduces different simplifications for the air handling unit modelling, but the impact of these simplifications is hardly analyzed. Therefore, the paper investigates the model complexity of the air handling unit in a Norwegian swimming facility by comparing a novel simplified model and a detailed model which serves as a digital replica of a real unit. The simplified decoupled model is found to have an acceptable accuracy for early-stage design, bearing in mind the overall uncertainty at this design stage. However, when carrying out a detailed investigation of a swimming facility, the detailed model should be applied, since this complex heuristic rule-based model, is taking into account phenomena like thermal-coupling effects between the swimming pool and the air handling unit and the control errors of the real internal controller. In conclusion, the paper derives useful guidelines for building performance simulation design of air handling unit, which is the main energy-intensive component in indoor swimming pool facilities. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

[Display omitted] • A split-degree days index is proposed for building energy use/climate classification. • Split-degree days index is shown to better estimate solar radiation and humidity data. • The estimation of building energy end-uses is improved using the split-degree days. • Split-degree days also showed improved results for high thermal mass and 24-hr models. • Split-degree days index maintains a high accuracy for varying base temperatures. Degree days have been widely used in different applications in buildings, such as estimating building energy use and climate classification for building energy standards. However, there are limitations with the use of conventional degree days that result in inaccuracies in estimating building energy consumption using degree day-based methods. This paper proposes a new method, the split-degree day method, that shows substantially improved results in the accuracy of the building energy use estimation compared to the conventional degree day methods. The analysis in 801 locations in the U.S. using regression models showed that the new, proposed split-degree day method in this paper, compared to the conventional degree day method, better accounts for the weather parameters and more accurately estimates end-uses. The split-degree days showed an improvement of over 5% in the accuracy of the total annual energy use prediction, 8% for predicting the heating energy use, 0.3% for predicting the cooling energy use, and 33% for predicting the fan energy use. Additionally, the analysis showed improved results for the model with higher thermal mass and the model with a 24-hour operating schedule. These improvements were due to the fact that the split-degree day method includes more information related to the weather characteristics of a location, which is missing in a conventional degree day calculation procedure that relies on aggregated data at daily intervals. Furthermore, as opposed to the conventional degree days, the accuracy of the estimations using the split-degree days are shown to maintain their high accuracy when the base temperature deviates from the optimal base temperature. The proposed method can be used as a more accurate alternative to the conventional degree days in different applications, including but not limited to building climate classification, building energy estimation, and weather normalization for building energy savings calculation. [ABSTRACT FROM AUTHOR]

[Display omitted] • 33 worldwide open datasets of city-level building energy consumption are summarized. • Representative applications of 198 papers using the collected datasets are analyzed and compared. • Policy implications are presented for using the open datasets to support policymaking. • Useful non-energy datasets about weather, building features, urban forms, and occupant-related factors are recommended. • Solutions to privacy issues are explored, including anonymizing methods and proper data aggregation. Data related to building energy use fuels the research and applications on building energy efficiency, which is an essential measure to address global energy and environmental challenges. However, in most cities, there is a lack of comprehensive and publicly accessible building energy use datasets with necessary temporal and spatial granularities to support urban building energy modeling, regional energy planning, city-level building performance benchmarking, and policymaking on building energy efficiency. Data owners and governments are facing challenges in determining which and how building energy use data should be disclosed at the city level and how to protect data privacy. This review paper provides insights to answer these questions based on a comprehensive and critical review of worldwide open datasets and their applications in the built environment context. Detailed information about the collected 33 building energy datasets is summarized and categorized. Studies identified into 11 subdomains using these open datasets are critically analyzed and compared. Potential policy implications based on the studies are also proposed. Moreover, non-energy datasets that are frequently used in research relevant to urban building energy use are also introduced. Solutions to privacy issues are discussed to address concerns from data publishers. Finally, significant conclusions are made to support the proper disclosure of city-level building energy data. This review study is valuable to urban building energy data disclosure, urban building energy modeling, and data-driven energy policymaking. [ABSTRACT FROM AUTHOR]

• A data-informed building energy management (DiBEM) framework was proposed. • It was demonstrated in an office/laboratory building with two-years' experimental data. • The impacts of energy efficient interventions were quantified through data-driven models. • The energy use intensity was reduced from 54.1 kWh/m2 to 42.8 kWh/m2. To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy-efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations. [ABSTRACT FROM AUTHOR]

Inequities in the built environment have long persisted in communities around the world. Prior studies have exposed that energy retrofit programs invest inequitably in residential buildings, leaving racial minorities with disproportionately less energy inefficient homes, regardless of income level. This inequity in energy performance and retrofit investments has yet to be studied for commercial and institutional buildings. Further research has shown that tree canopy coverage and vegetation is less dense in historically disadvantaged communities, contributing to a greater urban heat island effect and corresponding higher energy consumption for cooling compared to historically advantaged communities. Moreover, there is limited albeit emerging research that utilizes granular socioeconomic data with fine temporal scale energy consumption data to help identify energy inequalities among race and income groups. This paper examines the differential impact of energy efficiency retrofit installation on energy performance between advantaged vs. disadvantaged groups using data from U.S. public school buildings. Additionally, it studies how the effect of retrofits is compounded by the presence of vegetation surrounding the building. Utilizing hourly interval smart meter data from primary and secondary school buildings in California, the impact of retrofits are quantified using three energy metrics. Then the disparities in retrofit impact for advantaged vs. disadvantaged groups (as defined by three equity metrics) are evaluated using school-level demographic data. Lastly, regression on the percent change in monthly energy consumption from the pre-retrofit to post-retrofit period is used to quantify the incremental benefits of retrofits compounded by vegetation. Findings show that energy efficiency retrofits can improve energy performance and reduce energy inequities. Specifically, retrofits significantly increase energy efficiency and reduce the energy efficiency equity gap by up to 198%. Evidence shows that vegetation surrounding a building has a synergistic effect with mechanical retrofits for reducing energy consumption in respect to reduced cooling loads, even in cases where mechanical retrofits alone resulted in significant increases in energy consumption. Dense vegetation provides around 6% energy savings, similar in magnitude to savings from mechanical retrofit installation. This validates the effectiveness of retrofits for reducing energy consumption and improving energy equity, and demonstrates the ability of vegetation to provide additional energy savings beyond mechanical interventions. [ABSTRACT FROM AUTHOR]

Climate change and its consequences are of great concern. Buildings can be affected by climate change in different ways, such as changes in energy needs and thermal comfort. However, the challenge is to quantify and assess the uncertainties involved in future climate data as well as the relevant adoption strategies. The aim of this paper is to demonstrate potential energy consumption changes in high performance building construction systems in a changing climate. In this paper, current and future weather data of three time slices of 2020, 2050 and 2080 were used to simulate the performance of a simple building in Manchester and London using DesignBuilder software which employs Energy Plus as its calculation engine. Five of the most commonly used and high performance construction systems were examined in terms of energy consumption in this model and results are given. In general, this paper provides a useful methodology for simplification in design decision-making for current and future UK housing. It is observed that future climate scenarios do not have major effects in qualitative comparisons of construction systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • nZEBs in Eastern Europe lack carbon neutrality metrics and targets. • Performance requirements for nZEBs in Eastern Europe are presented. • Eastern Europe needs strategy and local governance for nZEB market penetration. • EPCs require major reform, and effective monitoring of nZEB performance is needed. • The cost-optimality calculation method must be adopted to ensure cost-effective market uptake. The European Unions' ambition for the construction sector is to be carbon neutral by 2030 for new construction. Since 2021, all new buildings in the EU should have been constructed as nearly zero-energy buildings (nZEB). However, Eastern European countries struggle to implement the 2018 Energy Performance of Building Directive recast requirements. Next to the economic challenges, equally essential factors hinder renovating the existing residential building stock and adding newly constructed high-performance buildings sourced primarily from renewable energy sources. Therefore, this study provides a cross-study to identify the barriers to nZEB implementation in ten Eastern European countries, including Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia. The study was conducted between 2019 and 2021 and provides an overview of prospects for nZEB in Eastern Europe. The study examines the challenges of nZEB plans faced in those countries and provides constructive recommendations. The regulations and definitions regarding nZEB energy performance, cooling and heating energy demand, thermal comfort, onsite renewables, and construction quality were analyzed. Results show that most Eastern European countries are unprepared to comply with the EPBD guidelines and cost-optimality approach. The paper ranks each country and recommends specific measures to refine the nZEB definitions. The paper provides a thorough comparative assessment and benchmarking of select EU geography that can help shift the identified gaps into opportunities for the future development of climate-neutral high-performance buildings. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports the use of an internationally recognized validation and diagnostics procedure to test the fidelity of a simplified calculation method. The case study is the simplified model for calculation of energy performance of building envelopes, introduced by the Brazilian regulation for energy efficiency in commercial buildings. The first step of the assessment consisted on evaluating the simplified model results using the BESTEST. This paper presents a straightforward approach to apply the BESTEST in other climates than the original one (Denver, USA). The second step of the assessment consisted on applying the simplified model to evaluate four building typologies, and compare the results with those obtained using a state of the art building energy simulation (BES) program. For some BESTEST cases, the simplified model presented results inside of a confidence interval calculated by the authors. However, the simplified model was found to yield significant difference in the four building typologies analysed. Moreover, in all four building typologies analysed, the simplified model led to a lower energy efficiency label when compared to the label obtained using BES. The paper concludes that the simplified model may require improvements to properly indicate the actual energy performance of commercial building envelopes. [Copyright &y& Elsevier]

The energy consumption necessary to maintain thermal comfort in buildings remains a significant and partially unjustified part, accounting for about 30–40% of the total energy consumption. Despite the increasingly pressing regulations in the energy sector (EPBD recast), the quality of the internal environment remains one of the critical parameters on which to pay more attention in view of a consistent evaluation of the Nzeb building. The windowed components are often designed with thermal insulation performances higher than the minimum requirements but still they lack in design of the incident solar radiation control, which is a particularly delicate topic for indoor comfort and more generally for a higher energy efficiency in buildings. If we think of the numerous variables of influence (typology, orientation, geographical location, etc.), the possibilities to associate energy saving, lighting control and users' comfort are inevitably entrusted to dynamic systems integrated into the glass. In this paper authors present the results related to the experimental characterization of two identical test rooms with different typologies of windows. One room is furnished with a traditional high thermal performance glass and the other, with an electrochromic glass suitably controlled by remote. The operative temperature measured in both test rooms have been utilized to verify the simulation model developed to assess the energy saving achievable in a Mediterranean climate, taking properly into account the hourly variations of the climate and the actions on the shading regulation systems. [ABSTRACT FROM AUTHOR]

The global construction industry is expected to experience an average growth of 3.6% annually in construction outputs throughout 2018 to 2022. The surge of new building developments will create substantial demand for energy and therefore run the risk of higher carbon emissions. With the rising concern over climate change, it is imperative for buildings to have energy-saving strategies in place. Many research has discussed the use of energy efficient technologies as a solution, but overlook the role of energy-saving behaviour during the post-occupancy stage. Occupants' energy-saving behaviour is important in ensuring the optimisation of building technologies. A large part of human behaviour is characterised by habit, which is learned sequences of an act that have become automatic responses to specific ques and are functional in meeting certain needs. The study aims to establish the link between the behaviour of building occupants and their underlying habits. Adopting the Habit Theory as a premise, the study formulates a framework on strategies for behaviour change interventions that captures the underlying motivations to exhibiting energy-saving behaviour. The Effective Theory-Building design process was applied, which engages an axiomatic system to purposefully generate theory, evaluate its utility, and provide an effective representation of the observed phenomena. The theoretical framework addresses how energy-saving behaviour is cultivated through conditions of habits. This shows that the building occupant's behaviour is important for enabling energy efficiency and that it can be construed and explained by repetitive habitual actions of energy-saving practices. To have the greatest effect on a building's energy performance, building managers must examine the nuanced ways that habitual actions may shape the occupants' energy-saving behaviour and consider intervention strategies for changing habits. The paper provides a deeper understanding of building occupants' energy-saving behaviour from a sociotechnical perspective and creates a paradigm for future studies of building energy management. [ABSTRACT FROM AUTHOR]

Abstract The use of energy efficiency procedures is a typical practice in building construction process that creates a huge amount of data regarding the building. This is particularly valid in structures which include complex collaborations, for example, ventilation, sunlight-based increases, inner additions, and warm mass. This paper proposes a new approach for automating building construction when improving their energy efficiency, aiming to foresee comfort levels based on Heating, Ventilating, Air Conditioning (HVAC), constructive systems performance, environmental conditions, and occupant behavior. More specifically, it presents a research work about thermal performance of prefabricated construction systems developed by an Argentine enterprise called Astori, using two Knowledge Discovery in Databases (KDD) processes to extract knowledge. In this context, Building Information Modeling (BIM) will give data to support the calculation to outline goal levels of a sustainable building performance concerning classification systems. The data were collected from a project in Uruguay referring to the construction systems and the energy efficiency of the building. The data mining tool SPMF was used to test the performance of classification and its use in prediction. Particularly, FP-Growth Algorithm and Clustering methodologies were used to analyze a combination of ambient conditions, in order to compare them using Revit© software. The results generated by these methods can be generalized for a set of buildings, according to the objective to be achieved concerning the thermal building performance. Highlights • Knowledge Discovery in Databases of complex collaborations in building construction. • Methodology used for knowledge related to metrics and key performance indicators. • Preprocessing for organization/setting of model parameters for building performance. • Execution of Data Mining with significant algorithms to increase project quality. • Analysis and representation of the results with prefabricated construction systems. [ABSTRACT FROM AUTHOR]

• Electrical-thermal modeling of power converter as part of a BIPV library in Modelica. • Power converter integration in BIPV module frame in a 'plug and play' configuration. • Experimental validation using a converter prototype tested in a climate chamber. • Improved accuracy compared to TRNSYS power conditioner across all KPIs. • Converter placement inside the frame strongly a?ects the components temperature. European legislation on building performance and energy efficiency pushes the shift towards minimizing the environmental footprint of buildings. Building-integrated photovoltaics (BIPV) is a promising technology that can accelerate the transition to energy-neutral buildings. Quantifying the potential of BIPV is crucial and one means of obtaining those results is through simulation. The state-of-the-art tools offer either thermal or electrical specialization; in particular, balance of system components (BOS) such as power converters have not been studied in detail within the building simulations BIPV domain. In this paper, a multi-physics model of a BIPV integrated DC/DC converter is developed in the Modelica language, taking into account the thermal and electrical couplings inherent to power electronic systems. The model has been validated using representative outdoor BIPV measurements and a DC/DC converter prototype. It has been found that the proposed model provides reasonable accuracy and outperforms an equivalent power conditioning model in TRNSYS. To demonstrate the model's functionality, two case studies are performed. First, the temperature-dependence of the converter's efficiency and losses is quantified and analyzed and, second, the prominent contributors to the converter losses are identified and discussed. [ABSTRACT FROM AUTHOR]

Highlights • The U-value impact on the thermal performance of residential buildings was analyzed. • 192000 buildings were randomly generated and evaluated using dynamic simulation. • Six geometry-based indexes were correlated with the buildings performance. • Higher U-values can decrease energy consumption in lower latitudes. • Higher and wider U-value intervals increase the geometric freedom for lower latitudes. Abstract Contrarily to what happens in northern European countries, buildings in the Mediterranean region are prone to overheating. Consequently, it is important to better understand the role that the thermal transmittance of the building envelope elements has on air-conditioning consumptions. This paper analyzes the effect of different U -values on building design in the Mediterranean area. 192 000 residential buildings were randomly generated for sixteen distinct locations and the energy consumption was assessed for each. It was found that in northern Mediterranean locations, as U -values decreased, energy consumption also decreased. However, in warmer climates, low thermal transmittances tended to significantly increase energy consumption. Hence, the lower the latitude, the higher the U -values should be, in order to prevent increasing the cooling demands. Additionally, geometry-based indexes were correlated with the building's energy performance. For high U -values, it was found that bigger buildings worsen the energy performance and larger windows tended to improve it. For low U -values, bigger north-facing windows were beneficial. There is an adequate interval of values for which the geometry has a lower impact, which is wider and higher for lower latitudes, thus meaning that not only does the building performance improve but architects are also freer to explore alternative designs. [ABSTRACT FROM AUTHOR]

Abstract Convenience stores are known to have higher Energy Use Intensities (EUIs) than most other commercial building types. However, convenience store energy performance analyses have not been systematically investigated. Moreover, current national convenience store benchmarks are inconsistent from one data base to another due to lack of relevant energy data. This paper assesses the energy performance of more than five hundred convenience stores in the same fleet in Eastern United States. The investigation aims to establish benchmarks for convenience stores with and without gasoline pumping stations. The main factors influencing the actual convenience store building energy use were determined. Multiple regression models were developed to find relationships between annual energy consumption per unit area and gross floor area, customer transaction count, building operating year, etc. The statistically characterized results are meant to serve as a reference data set in comparing the whole-building energy performance index for buildings of similar functionality. The statistical correlation analyses can strengthen the robust prediction of energy performance in convenience stores, enabling proper assessment of energy conservation measurements (ECMs) for convenience store operations, as well as guiding additional such energy performance studies. [ABSTRACT FROM AUTHOR]

Abstract: The success of modeling the sustainable performance of the residential building envelope will be to a great extent associated to the sustainable energy performance indicators used. The sustainable energy performance indicators that these building assessment models are developed around should be chosen by taking into account the targeted objectives. However, it is very common to find building performance assessment models that do not take into account these considerations and therefore have a limited capability and scope. This leads to inadequate aggregate indicators for the actual assessment of the sustainable performance of the building envelope for a sustainable energy efficient building. The focus of this paper is to investigate the principal sustainable energy performance indicators for modeling the sustainable performance of the residential building envelope and develop an approach for determining the most appropriate sustainable energy performance indicators. In doing that, this paper provides an overview of previous research on sustainable energy performance indicators and discusses conceptual framework for developing sustainable energy performance indicators. In order to identify these indicators that influence the capability of building performance assessment models, a comprehensive survey of construction industry professionals was conducted using questionnaire survey technique while the data was analyzed using correlation analysis techniques. [Copyright &y& Elsevier]

Abstract: Building designers are often limited in their ability to reduce the environmental impact of buildings, due to a lack of information on the environmental performance of building components as well as inconsistencies in the way in which this information is derived. Whilst numerous tools exist to help facilitate the low-energy building design process, these typically require large investments of time and money that are often beyond those available within any particular project. This paper describes an approach for streamlining the design process to reduce building life cycle energy consumption. Building assemblies are ranked based on an assessment of the life cycle energy requirements associated with their use within a building. This facilitates early stage assessment, negating the need for a resolved design before the relative energy requirements of alternate design solutions are known. Previous work assessed the initial and recurring embodied energy as well as the operational energy requirements for heating and cooling associated with the use of a range of building assemblies, using a simplified house model. This paper presents a sensitivity analysis of variations to the floor area, shape and orientation of this model, to test the reliability and applicability of the ranking approach across a broad range of circumstances. It was found that these variations did not influence the ranked order of the assemblies in terms of their life cycle energy requirements. Thus, the ranking of assemblies appears to provide an appropriate approach for streamlining the selection of construction elements during the building design process. [Copyright &y& Elsevier]

Abstract: This paper aims to study the various parameters that affect the energy performance of commercial buildings in Singapore. The parameters are diverse, ranging from characteristics of construction of the walls and windows, to the various system settings and types within the building. Building energy performance is measured via two key indexes, namely, the Envelope Thermal Transfer Value (ETTV) and the annual cooling energy requirement (E c). Parameters related to these two indexes are identified. An additional parameter, the solar absorptance of the wall, is further incorporated to calibrate the ETTV equation. A relative ranking on the functional parameters of ETTV has been performed to evaluate their effectiveness in lowering the ETTV of buildings. In addition, the impact of using cladding on ETTV is also studied. A correlation for E c, expressed in the form of a simple linear equation, has been developed. This correlation accounts for the internal building loads, envelope loads, operating schedules and efficiency of the cooling equipment. Finally, ETTV and E c have been employed to study the effects of chiller over-sizing and ventilation rates on building cooling energy. In the pursuit for better energy-efficient buildings, the approach presented in this paper contributes to the construct of sustainable energy-efficient built-environment. [Copyright &y& Elsevier]

• Bottom-up archetype model for space heating demand of Swiss office building stock. • Archetypes characteristics derived from energy certificates database. • Estimation of current thermal performance and energy retrofit's potential. • Calculation of national heating demand and distribution among archetypes. • Influence of design characteristics and buildings properties on heating demand. Energy efficiency in buildings is a key objective of the European energy strategy. To address the limited knowledge of the thermal performance of the non-domestic building stocks, this paper presents a bottom-up, physics-based, archetypal model derived from a large building stock database and physical characteristics from 2170 building energy performance certificates in Switzerland. The model was validated by measured energy consumption data and national statistics. Results highlight the potential for energy retrofit: most of the stock is still heated with fossil fuels (67% of the total heated area) and 40% of the total envelope surface has a poor thermal performance associated with the period before 1980. We estimate national final energy demand for heating of the office building stock (11.3 PJ/year) and present detailed breakdown of energy by thermal loss element. Significant differences were found between archetypes related to urban settings (specific demand 50% higher in rural than in urban contexts) and age of the buildings (56% of the total demand is due to buildings constructed before 1970). The physical model highlights the impact of architectural design characteristics such as building compactness and glazed surface ratios on thermal performance. The model represents an important step for studies on optimal thermal retrofit pathways. [ABSTRACT FROM AUTHOR]

• BIM-DB can effectively simulate building performance parameters. • The PSO-RF-NSGA-III hybrid method can be used to predict and optimize building performance. • NSGA can simultaneously optimize energy consumption, carbon emissions and thermal comfort. • The optimal building parameters are different in different regions. Near-zero-energy-consumption buildings (NZEBs) are of great significance for sustainable development, and their design and research have attracted increasing academic attention. To drive and realize the energy saving design and achieve carbon emission and thermal comfort optimization of NZEBs, in this paper, an intelligent optimization method integrating the BIM-DB and PSO-RF-NSGA-III method is established. Multiobjective optimization problems involving NZEBs in four typical climate regions in China are explored. With a typical office building as an example, first, simulation calculations regarding the energy consumption, carbon emissions and indoor thermal comfort in the four climatic regions are performed based on orthogonal tests and BIM-DB. Second, the nonlinear mapping relationships between building design parameters and prediction targets are constructed with the PSO-RF model, which is trained with sample data. The obtained nonlinear mapping relations are used to establish the objective function of NSGA-III, and the multiobjective Pareto-optimal solution set is obtained with the developed PSO-RF-NSGA-III algorithm. Finally, the only optimal solution is determined by using the ideal point method, and reference near-zero-energy-consumption office building parameters are calculated for different climate regions. The conclusions are as follows. (1) The PSO-RF algorithm can efficiently predict building energy consumption, carbon emissions and thermal comfort. In the four regions, the goodness of fit of the three targets is greater than 0.94. (2) Multiobjective optimization can be performed with the proposed RF-NSGA-III intelligent optimization method. After optimizing multiple groups of optimization schemes and adopting energy saving measures, the energy consumption levels in the four climate regions are reduced by 39.72 %, 32.22 %, 26.94 % and 35.37 %, and the other goals are optimized. (3) Index calculations indicate that the optimized building design parameters meet the specified standards for NZEBs, and the main influencing factors and corresponding measures vary from region to region. [ABSTRACT FROM AUTHOR]

• Investigated climate change impacts on office building performance in Brussels. • Applied a long-term climate change sensitive system sizing and design approach. • Time-integrated discomfort analysis showed a major surge in overheating by 2100. • Long-term climate change resistivity is ensured in reference building until 2100. • Primary energy use and GHG emission findings are useful in mixed humid climates. As climate change continues, it is expected that the risk of overheating will rise in both new and existing buildings in mixed humid climate zones in Europe. This study introduced a novel climate change sensitive sizing and design approach for cooling and heating systems in nearly zero-energy office buildings in Brussels, Belgium, for different weather scenarios. This approach considered the long-term effects of climate change on building performance. The climate change effects were assessed using current and future climate data from the regional atmospheric model, MAR. To demonstrate the approach, a case study of a nearly zero-energy office building in Brussels was conducted. The reference building model was first calibrated using monthly energy use data from the year 2019 using ASHRAE Guideline 14. Then, the building was evaluated with different HVAC strategies and their performances were quantified. The results indicated an increase in overheating as high as 1.2 °C and cooling energy use as high as 13.5 kWh/m2 and a decrease in overcooling as low as 0.3 °C and heating energy use as low as 10.9 kWh/m2 in the reference building by the end of the century. In addition, due to climate change sensitive sizing and design approach coupled with optimal sizing, the reference building was climate change resistant towards the worst-case scenario by end of the century with up to 3.7 for climate change overheating resistivity and 20.2 for climate change overcooling resistivity. Finally, the paper provided recommendations for future practice and research based on the study findings. [ABSTRACT FROM AUTHOR]

• Building performance simulation is powerful but computationally expensive. • Machine Learning (ML) surrogate models can reduce simulation times significantly. • Building energy and peak loads are predicted under different operational settings. • Extreme gradient boosting outperformed other methods. • Linear regression showed the lowest training time with competitive predictive power. Building Performance Simulation (BPS) is a powerful and widely used technique to evaluate building design and operation strategies prior to construction or retrofitting. However, BPS models often have high computational costs, which is particularly limiting for applications that require a significantly large number of simulations, such as building design optimization or uncertainty analyses. To overcome this gap, researchers have turned to surrogate modeling, where a mathematical model, such as a machine learning algorithm, is trained to mimic the performance of a BPS, allowing to test numerous building design/operation configurations at low computational costs. Past studies have applied surrogate BPS modeling to predict the impact of building design parameters on energy performance. However, few have considered building operational parameters, such as occupancy, equipment and lighting usage, and thermostat setpoints, which significantly impact energy consumption and peak loads, especially in harsh climate conditions. This paper presents a unique evaluation and comparison of machine learning algorithms as surrogates to BPS predictions of building performance (energy consumption and peak loads) under different operational settings. Results indicate that Extreme Gradient Boosting outperformed all other methods in predictive accuracy, with R2 values reaching as high as 0.99 for some models. In contrast, linear regression models were the fastest to train and easiest to interpret while still achieving competitive prediction accuracies (R2 values > 0.9). This work provides direct evidence of the machine learning surrogate models' ability to accurately predict building performance under different operational settings. It also offers unique insights into the strengths and weaknesses of white-box and black-box predictive modeling approaches and the effect of dataset size on the results. [ABSTRACT FROM AUTHOR]

Mosques are external load dominated buildings that are characterized by their intermittent and varying occupancy schedules. Most mosques employ some form of mechanical heating/cooling system in order to maintain suitable thermal comfort conditions for the users during prayer times. Due to the unique spatial characteristics and occupancy patterns of mosques, these systems are often found to be energy-intensive which impacts the overall energy efficiency of the building. The inefficiency in mosque energy usage has been typically attributed to the poor thermal performance of the buildings along with unsuitable operational strategies for the occupancy schedule of mosques. This paper reviews contemporary literature on mosque energy usage with an aim of identifying the factors that influence the energy efficiency of mosque buildings. Findings from the literature have been categorized according to different parameters of the building design as well as design and operational strategies of the heating/cooling systems. Discussion on the common practice and best practice has also been done with respect to thermal comfort standards and requirements. In addition to that, this paper compares and critically evaluates the studies that have aimed at reducing energy consumption and improving energy efficiency in mosques. Findings from multiple research suggest that as much as half of the energy usage can be reduced with the optimization of building design and operational strategies of mosques. The review of contemporary literature provides valuable insights into mosque energy usage patterns and identifies the important aspects to be considered in reducing energy consumption in mosque buildings. Through this literature review, numerous research gaps have been identified that may be pivotal in designing energy efficient mosques. Based on those, future potential research prospects have also been suggested. Image 1 • A comprehensive review on energy performance of mosque buildings is presented. • Factors influencing mosque energy efficiency are identified. • Impact of mosque design and operational parameters on energy usage are addressed. • Critical analysis of energy optimization studies is presented. • Numerous research gaps and scopes are identified for further research. [ABSTRACT FROM AUTHOR]

The buildings sector contributes 20% of global greenhouse gas emissions, and building energy use is anticipated to double by 2050. Building performance research has typically focused on the operational phase, with life-cycle impacts increasingly studied, but often in isolation. This paper presents a novel framework integrating building energy modelling with life-cycle analysis and life-cycle costing. This is applied to four façade glazing materials in a 15-story case study office building in Queensland, Australia – a sub-tropical and commercial example rare in literature but important for future building development. Results demonstrate that double-glazed low-emissivity material (Type 4) was the most energy and financially efficient despite higher embodied energy and carbon than alternatives. It yielded operational energy and greenhouse gas emission savings of 13% against the baseline, and 2% lifetime financial savings. Clear double-glazing (Type 3) had the poorest overall performance, attributed to its low U-value trapping heat within the building and increasing net energy and emissions. This was new evidence that clear double-glazing should be carefully considered in sub-tropical climates. The integrated approach identified a material with improved overall performance. If only embodied impacts (production, transport, disposal) were assessed, GT1 would appear the best option as it takes less energy and carbon to manufacture and transport yet has very poor operational performance. This paper extends existing knowledge on façade materials and will aid future work on sustainable, low-emission building design in other climates, economies, designs and industries. • Integrated modelling of building façade operational energy, carbon, and cost. • Double-glazed low emissivity option reduced energy 13% in operational phase. • Rare commercial study in sub-tropical climate shows glazing selection influence. • One glazing type performed poorly in winter due to overnight 'heat trapping. • Framework will aid analysis for other climates, economies, designs and industries. [ABSTRACT FROM AUTHOR]

Automatic warehouses need to balance speed, cost, flexibility, and energy consumption to support the responsiveness, efficiency, and sustainability of modern supply chains. This paper explores environmentally friendly velocity and acceleration configurations of the Shuttle-Based Storage and Retrieval Systems (SBS/RS) under throughput requirement. This study develops an energy consumption model for the SBS/RS with cross shuttles operating on a dual-command-cycle basis and estimates the maximum throughput, travel time and energy consumption. Numerical experiments explore the optimal velocity profiles with the least energy consumption under different throughput requirements. The results show that the lift velocity and acceleration are the leading factors influencing energy consumption. Increasing the accelerations of aisle and cross shuttles can moderately reduce travel times and improve storage efficiency, without hurting energy consumption. Besides, this paper also identifies the relationship between throughput capacity and energy consumption. Overall, this study provides insights on the SBS/RS configurations under given throughput requirements and environmental performance and builds a green decision-making basis for automatic warehouse designers and managers. [ABSTRACT FROM AUTHOR]

• An uncertainty propagation method was developed which captures climate uncertainties. • The method is applicable to cases where few future weather files can be developed. • The method can reduce computation requirements following a probabilistic approach. • The impact of equipment modernization using updated design day files is investigated. In the United States, buildings consume a significant portion of total energy use and contribute to carbon emissions. Therefore, evaluating their performance for sustainable design is critical. While building standards are updated frequently to improve building efficiency, the climate is changing and classical (deterministic) approaches to quantifying building energy use may not be accurate. Significant uncertainties exist in current models of future building performance. Probabilistic approaches to evaluate whole building performance and account for climate uncertainties require large input data of climate projections with detailed spatial and temporal resolution and considerable computational resources. This paper offers a four-step process to propagate climate uncertainties from future climate projections into building energy performance. The climate uncertainty propagation method consists of a combination of regression, distribution fitting and random sampling. It has the potential to capture climate uncertainties in building simulation tools and is applicable to cases where limited future weather files can be produced. In addition, we include the use of updated design day files in future building performance analysis. Design days drive equipment modernization impacting whole building energy use under climate change. The Department of Energy office reference buildings for Philadelphia climate conditions are used as the case study. The aim of this research is to generate a probabilistic model that captures future building energy performance trends where can be applicable to regions that have limited future hourly weather files to be incorporated into building simulation tools. The results of this paper are intended to promote a probabilistic approach to account for climate uncertainties and to provide guidance in analyzing buildings projected energy consumption under climate change. [ABSTRACT FROM AUTHOR]

Lighting energy savings, as well as visual and non-visual user benefits have been widely attributed to daylighting. This paper explores daylight design strategy, visual appraisal, Daylight Factor (DF), lighting energy usage and discomfort glare using two green building offices in Malaysia, which have incorporated daylighting into both façade and interior design. Visual appraisal surveys were collected from 39 and 145 subjects in the open plan working space of the Energy Commission Building (ECB) and Public Works Department Block G (PWD), respectively. The survey focused on task brightness, colour appearance, uniformity and lighting preference. Discomfort glare assessed via occupant point-of-view luminance maps was juxtaposed here from a glare study involving the same buildings. Illuminance loggers were used to monitor artificial lighting usage as well as the DF on a selected floor of each building. There were no significant differences in occupant responses to the visual appraisal survey for both office spaces. Using MS1525:2014 and Green Building Index (GBI NRNC) tool as baselines, the DF performance of both offices differs significantly: PWD had a 45.5% daylit area, with ECB a 14.8% daylit area for DF >1%. However, lighting energy usage results show substantial savings of 53% and 41% occurred from daylighting. These findings of visual appraisal, DF, lighting energy savings and discomfort glare show a discrepancy in using only the DF to justify the daylight performance of an office space in a tropical climate such as Malaysia. The findings suggest that equivalent consideration should be given to interior design to facilitate daylighting, which is often beyond the control of designer, but in the hands of office end users. [ABSTRACT FROM AUTHOR]

Due to the strengthening of regulations and codes on building energy performance, as well as with the application of national legislations regarding energy management and efficiency, existing industrial facilities are using thermal refurbishment and renovation as impetus for increasing their overall energy efficiency. This paper analyzes a building envelope refurbishment for a case study of an existing historical industrial facility. Critical parameters affecting energy performance of industrial buildings were identified by reviewing relevant literate. Two retrofit scenarios were developed and dynamic thermal simulation using EnergyPlus was implemented to evaluate the potential for improvement. Thereby the impact of interior loads was considered, determined by measurements conducted on factory machines, occupancy and lighting operation patterns. However, information regarding constructions of the existing facility and installed technical building services is limited. There is also uncertainty in the quantification of natural ventilation air change rate for such buildings. To overcome these limitations a study of various material databases was carried out, in order to assess data for building envelope composition. Input values for missing data were provided based on literature, allowing a fair comparison between refurbishment alternatives. Simulation results showed that the heating demand of the facility could be reduced up to 52%, indicating a significant potential for energy savings. Beyond that, thermal performance against summer overheating also depicted considerable improvements as regards to hours exceeding thermal comfort levels. [ABSTRACT FROM AUTHOR]

Sustainable building performance requires the integration of various metrics such as energy consumption, thermal comfort levels, occupants’ wellbeing, and productivity. Despite their interdependence, these metrics have been mostly evaluated independently, overlooking potential tradeoffs that can occur between them (e.g., energy conservation efforts and thermal comfort). In addition, human-related factors such as occupants’ energy consumption behaviors, schedules, and movements between buildings cannot be captured using current commercial building modeling tools. Consequently, simulating the performance of a group of buildings such as in a campus, neighborhood, or city remains very challenging. In this paper, a comprehensive agent-based modeling (ABM) framework is developed to: (1) model an urban area with several buildings along with the movements and actions of people within the environment; (2) calculate key performance metrics such as indoor/outdoor thermal comfort and energy consumption levels; and (3) test and propose strategies to optimize sustainable building operation. This study illustrates the multidisciplinary approach needed to capture various dimensions of sustainable building performance. The framework is then applied to a green campus environment, identifying an energy management strategy that can reduce energy consumption by 19% without compromising occupants’ comfort and wellbeing. [ABSTRACT FROM AUTHOR]

• EU policy efforts on energy efficiency in buildings stared in the 1970s in response to the oil crisis. • The first comprehensive EU policy was the SAVE directive in 1992, introducing policy actions still relevant today. • A major step forward was the Energy Performance of Buildings Directive in 2002 and its subsequent amendments. • Mandatory energy performance standards are progressively converging towards near zero energy buildings. • Additional policies and financing are needed for the full decarbonisation of the building stock. The reduction of energy demand in buildings through the adoption of energy efficiency policy is a key pillar of the European Union (EU) climate and energy strategy. Energy efficiency first emerged in the EU energy policy agenda in the 1970s and was progressively transformed with shifting global and EU energy and climate policies and priorities. The paper offers a review of EU energy policies spanning over the last half century with a focus on policy instruments to encourage measures on energy efficiency in new and existing buildings. Starting from early policies set by the EU in response to the Oil Embargo in the 1973, the paper discusses the impact of EU policies in stimulating energy efficiency improvements in the building sector ranging from the SAVE Directive to the recently 2018 updated Energy Performance of Buildings Directive and Energy Efficiency Directive. The review explores the progress made over the last 50 years in addressing energy efficiency in buildings and highlights successes as well as remaining challenges. It discusses the impact of political priorities in reshaping how energy efficiency is addressed by EU policymakers, leading to a holistic approach to buildings, and provides insights and suggestions on how to further exploit the EU potential to save energy from buildings. [ABSTRACT FROM AUTHOR]

• A review of simulation-aided occupant-centric building design studies is presented. • Covered themes include occupant-centric metrics, models and design practices. • Most studies focus on energy-related metrics with a lack of implementation. • Metrics related to occupant comfort, wellbeing and space planning are understudied. • Improved data collection, modeling and communication methods are recommended. Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process. [ABSTRACT FROM AUTHOR]

• An overall panorama of the school buildings in Brazil was presented. • Energy billed data and survey evidence were used to build a statistical stock model. • The Weibull distribution was the most adequate to represent the continuous variables. • kWh/student·year was more suitable than kWh/m2·year to model Brazilian school buildings stock. • Thermal performance is an issue to be greatly improved in schools in Brazil. Understanding the actual conditions in school buildings regarding energy usage and environmental satisfaction gives way to the development of consistent building stock modelling. In the Brazilian context, a deep-rooted inefficient structure of energy management implies a lack of mapping the actual conditions of the public schools. Therefore, this paper aimed to assess the actual energy performance of school buildings in Brazil. This paper innovates by integrating questionnaire responses and billed energy data to allow the construction of an evidence-based stock model through a statistical approach, which was never performed for the Brazilian building stock. Moreover, the association of energy use intensity (EUI) with the core aspects of building characteristics, occupancy, environmental satisfaction and necessary improvements mapped the relevance of such aspects in energy usage patterns. Additionally, a discussion of the EUI indicators was addressed. Results showed an unprecedented broad panorama of the school building stock in Brazil and its main features. In terms of statistical analysis, the Weibull distribution was appropriate for representing the continuous variables of the stock. The EUI as a function of the number of students was more suitable than the floor-plan area to achieve a reliable energy performance analysis. Several tests were performed to assess if the energy management, environmental satisfaction and maintenance practices impacted the EUI or not. Finally, the main conclusion was that the stock model obtained was simple and fit the energy management structure in the Brazilian scenario. [ABSTRACT FROM AUTHOR]

• This method integrates uncertainty analysis and cluster analysis methods. • Proposed novel zoning indicators are statistically significant. • Moves from traditional weather-based approaches to a performance-based approach. • Robust tool to tackle complex relation between climate and building energy efficiency. • Provide evidence for the rationality of decision making in energy policy. Climatic zoning is an important tool in building energy policy and regulations, smaller and more homogeneous climate zones could help enhance the rationality of energy policymaking. In most countries, climate zoning is based on simplified climate models, and it is difficult to accurately represent the energy demand characteristics of buildings. Therefore, this paper proposes a novel climate subdivision method that tackles the complex relations between climate and building energy-efficient, which move from traditional weather-based approaches to a performance-based approach. Integrate the uncertainty analysis method and the building dynamic performance simulation to extract a novel statistically significant index as the basis for classification. The K -means clustering method and discriminant analysis method are used to obtain and verify the clustering results, respectively. Furthermore, the comparison with clustering results based on degree days confirms the superiority of the new method proposed in this paper in identifying building energy demand. The method is applied to the cold climate zone of China as a showcase. The results show significant differences in building energy demand and the order of key features affecting building performance between each region in the climatic zones. The zone can be further sub-divided into four groups considering the climate factor and building feature uncertainty, and clustering results have been verified by several evaluation indicators. [ABSTRACT FROM AUTHOR]

• Multi-objective optimisation of energy performance associated with window design. • Simultaneous and conflicting objectives are considered helping simpler comparisons. • A framework for numerical assessment of view in office environments is proposed. • View, energy performance and daylighting are considered as optimisation objectives. • The best model found has highest view and daylight, and medium energy consumption. This paper presents a new, multi-objective method of analysing and optimising the energy processes associated with window system design in office buildings. The simultaneous consideration of multiple and conflicting design objectives can make the architectural design process more complicated. This study is based on the fundamental recognition that optimising parameters on the building energy loads via window system design can reduce the quality of the view to outside and the received daylight – both qualities highly valued by building occupants. This paper proposes an approach for quantifying Quality of View in office buildings in balance with energy performance and daylighting, thus enabling an optimisation framework for office window design. The study builds on previous research by developing a multi-objective method of assessment of a reference room which is parametrically modelled using actual climate data. A method of Pareto Frontier and a weighting sum is applied for multi-objective optimisation to determine best outcomes that balance design requirements. The Results reveal the maximum possible window to wall ratio for the reference room. The optimisation model indicates that the room geometry should be altered to achieve the lighting and view requirements set out in building performance standards. The research results emphasise the need for window system configuration to be considered in the early design stages. This exploratory approach to a methodology and framework considers both building parameters and the local climate condition. It has the potential to be adopted and further refined by other researchers and designers to support complex, multi-factorial design decision-making. [ABSTRACT FROM AUTHOR]

• New building development projects underperform often. • Underperformance leads to increased energy consumption and CO 2 emissions in building operation. • The paper links building project development and building operational performance. • Two simulation methods are combined in a multi methodology framework in the paper. • The paper explores the implications of project partner collaboration for operational building performance in the case of a recent building project. The "performance gap" in the United Kingdom construction industry is a persistent problem as new building development projects underperform more often than not. The "performance gap" is partially attributed to the number of stages involved in building project development and the coordination difficulties of partners with different incentives. The project outcome is important for energy consumption, carbon emissions and occupant well-being. Thus, it is important to study the project management process in terms of the standard time, cost and quality parameters, but also in terms of project partner incentives and coordination, and the subsequent energy performance and resultant indoor environmental conditions. A system dynamics model of project management processes is developed to explore the implications of partner coordination for building quality. The system dynamics model is coupled to a building performance simulation model to explore building energy consumption and Indoor Environmental Quality, and apply this on a recent building project case study. Results show that greater project partner alignment can reduce annual energy consumption up to 12% and CO 2 emissions up to 37%, with greater emphasis in the design stage of the project subject to resource availability. The trade-offs involved on value appropriation are considered and discussion of results points to possible ways for improvement. [ABSTRACT FROM AUTHOR]

Inter-building effect (IBE), which refers to the shading effect from surrounding buildings, plays an important role in building energy use in high-density cities. However, it is customary to neglect the IBE during energy simulation. Four issues are observed on previous research: 1) it has been controversial whether the IBE significantly affects energy consumption, 2) most studies used low-rise or medium-rise residential buildings as references, 3) most studies were conducted with hypothesised buildings, 4) most studies did not consider window blinds effect on IBE. These issues inhibit the theoretical understanding of high-rise building energy performance in cities and jeopardise the achievement of accurate simulation. This paper thus aims to investigate the IBE on the energy use of high-rise office buildings in Hong Kong as a typical high-density city. The IBE of ten selected real-life office buildings in their real-life communities was analysed. Four scenarios were compared, namely, simulation of building with both IBE and window blinds (base case), simulation of building with IBE but no window blinds, simulation of isolated building with window blinds, and simulation of isolated building without window blinds. The results show that the IBE influences the total energy use by up to 13.1%. Compared with the base case, heating, ventilation, air-conditioning (HVAC) and the lighting consumption deviation with different scenarios fluctuated largely, ranging from −11.8% to 18.8% in HVAC consumption, and from 0.1% to −27.6% in lighting consumption. An offset effect was found between the decreased lighting consumption and the increased HVAC consumption. From the floor-level analysis, with real communities, lighting energy use decreased with height among all the buildings generally. A multi-variant regression model was established to evaluate the relationship between IBE variables and building energy deviation caused by IBE. In addition, the results conclude that shading blinds cannot be overlooked when examining IBE on building energy use. These findings reveal the importance of considering IBE on building energy consumption in high-density contexts on a case-by-case basis. [ABSTRACT FROM AUTHOR]

[Display omitted] • The strengths and weaknesses of existing data collection methods are analyzed. • The main correlated factors for different building types are summarized. • Existing methods to characterize behavioral diversity are classified and compared. • The adaptability of various prediction models is discussed. • The mutual validity of model evaluation indicators is examined. Opening windows is by far the simplest means of ventilation. It is also crucial for energy efficiency and for creating a comfortable indoor environment. During the last decade, researchers have made great strides in investigating occupants' window operation patterns. However, the different research methods used to capture, recognize, and model behavior across the literature make it difficult to compare the results between studies. This has greatly impeded the application of window opening behavior models to building energy performance simulation software. Therefore, this paper aims to provide a comprehensive review of occupants' window opening behavior in relation to four aspects. The first aspect is data collection methods, whereby different data collection methods are analyzed, and the limitations of the existing monitoring devices are pointed out. The second aspect is the factor analysis, whereby the main correlated factors for different building types are summarized. In particular, it is assessed whether indoor temperature and indoor CO 2 concentration are drivers of the window opening behavior. The third aspect is the characterization of behavioral diversity, whereby the existing methods to characterize behavioral diversity are classified and compared. The final aspect is prediction models, whereby the adaptability of various prediction models and the mutual validity of model evaluation indicators are discussed. In the future, scholars will need to make efforts to expand the test sample size, quantify window opening angles, consider the diversity of behavior and unify model evaluation metrics. This would help the application of predictive models in supporting building design and the evaluation of the effectiveness of energy efficiency technologies. [ABSTRACT FROM AUTHOR]

• POE was carried out to compare the design target and operational effect after use. • A Large Irregular Green Commercial Building was chosen for in-depth analysis. • We recommend the building energy saving and carbon emission reduction strategy. Commercial buildings, especially large irregular commercial buildings with complex space and dense occupation, have high energy consumption and carbon emissions. Moreover, the actual operating performance differs significantly from its design, in terms of energy conservation and carbon emissions. This study selected an irregular large-scale green commercial building in Dalian, a coastal city in the cold zone of China. The running energy consumption and indoor physical environment were investigated and analyzed, and a satisfaction survey was conducted using the Post-occupancy evaluation (POE) methods. The promotion strategies of holistic design were proposed by comparing the operational building performance with the design target. The research shows that the energy consumption of the building was 68.02 kWh/m2, which failed to meet the standard requirements. The carbon emission was 74.76 kgCO 2 /m2. Less than 10 % of humidity in summer fell in the expected range, and the lowest value of PM 2.5 concentration in winter was 28.3 %. The score of indoor environmental quality and service satisfaction was low. This paper identifies the problems and analyzes the differences between the operation stage and design phase. It provides recommendations and guidelines for optimizing the carbon emission and indoor environment based on the performance improvement of building operational conditions. [ABSTRACT FROM AUTHOR]

Typically the effect of thermal bridges on the energy performance of buildings is taken into account by implementing an average U-value in 1D whole building energy simulation program, which is referred to as the equivalent U-value method. This treatment accounts for the effect of thermal bridges on the overall thermal transmittance of envelope details, while their thermal inertia effect is ignored. In this paper, the dynamic effect of balcony slab as thermal bridges on the energy performance of a high-rise residential building is investigated by comparing the annual space conditioning loads obtained by the equivalent U-value method to that obtained from 3D dynamic modeling of the balcony junctions implemented in WUFI Plus program. The simulation results show that the equivalent U-value method underestimates the annual heating loads by 2.8–4.4% for the building as-designed. With the increase of balcony portion and better insulated walls, the difference in annual space heating loads modeled using these two methods is increased to 8.6–15.2%. With the implementation of balcony thermal break the annual heating loads are reduced by 8.8–25.7% and the difference between these two modeling methods is also reduced to 1.9–11.5% for the cases investigated. [ABSTRACT FROM AUTHOR]

• A top-down analysis of the non-residential building stock in Brazil is proposed. • The share of each building typology in the country energy consumption was assessed. • A statistical analysis showed variation of EUI according to type of building and region. • Reference values for the commercial building stock in Brazil is provided. This paper provides a pioneering, top-down analysis of the non-residential building stock in Brazil. A country-wide dataset was used, comprising 10,000 buildings divided into 12 typologies. Key indicators include floor area, energy use intensity, and operation patterns. In addition, predominant wall constructions, lighting systems, equipment, water heating, and HVAC systems for each typology were identified, including average density power for the systems. Data from the Brazilian Energy Balance report was correlated with the sample of buildings to determine the proportion of each building typology in the total energy consumption of the country, considering different energy sources. This study provides an innovative and up-to-date status of the characteristics of non-residential buildings in Brazil. A complementary statistical analysis addressed the correlation between energy use intensity and the building characteristics including an ANOVA test and a regression analysis in order to investigate the influence of the energy usage indicators (Lighting Power Density, Equipment Power Density, Cooling capacity) on the energy use intensity of each building typology in Brazil. This study is intended to serve as a reference for building characteristics and building energy performance in Brazil, and hence support diverse research regarding country-level building stock modeling, energy benchmarking, climate change impacts, and energy-efficiency related studies. [ABSTRACT FROM AUTHOR]

• Meter-level anomaly detection and diagnosis is performed through CMP algorithm. • CMP parameters are automatically set using supervised and unsupervised methods. • A severity score, based on 4 statistical methods, is used to recognize anomalies. • 55 anomalous energy consumption patterns are discovered in a one-year timeseries. • Anomalies at meter-level are diagnosed by exploiting information at sub-load level. Recently, the spread of IoT technologies has led to an unprecedented acquisition of energy-related data providing accessible knowledge on the actual performance of buildings during their operation. A proper analysis of such data supports energy and facility managers in spotting valuable energy saving opportunities. In this context, anomaly detection and diagnosis (ADD) tools allow a prompt and automatic recognition of abnormal and non-optimal energy performance patterns enabling a better decision-making to reduce energy wastes and system inefficiencies. To this aim, this paper introduces a novel meter-level ADD process capable to identify energy consumption anomalies at meter-level and perform diagnosis by exploiting information at sub-load level. The process leverages supervised and unsupervised analytics techniques coupled with the distance-based contextual matrix profile (CMP) algorithm to discover infrequent subsequences in energy consumption timeseries considering specific boundary conditions. The proposed process has self-tuning capabilities and can rank anomalies at both meter and sub-load level by means of robust severity score. The methodology is tested on one-year energy consumption timeseries of a medium/low voltage transformation cabin of the university campus of Politecnico di Torino leading to the detection of 55 anomalous subsequences that are diagnosed by analysing a group of 8 different sub-loads. [ABSTRACT FROM AUTHOR]

• Implementation of a model predictive control scheme for HVAC systems is presented. • The hardware/software solution is generalisable to most building management systems. • Cloud solutions can offer low-cost, scalable control in commercial buildings. • Economic MPC reduced energy usage by 1.7% compared to baseline control. • Building thermal performance strongly affects viability of MPC schemes. Many businesses are looking for ways to improve the energy and carbon usage of their buildings, particularly through enhanced data collection and control schemes. In this context, this paper presents a case study of a food-retail building in the UK, detailing the design, installation and cost of a generalisable model predictive control (MPC) framework for its Heating, Ventilation and Air Conditioning (HVAC) system. The hardware/software solution to collect relevant data, as well as the formulation of the MPC scheme, is presented. By utilising cloud-based microservices, this approach can be applied to all modern building management systems with little upfront capital, and an ongoing monthly cost as low as $6.39/month. The MPC scheme calculates the optimal temperature setpoint required for each Air-Handling Unit (AHU) to minimise its overall cost or carbon usage, while ensuring thermal comfort of occupants. Its performance is then compared to the existing legacy controller using a simulation of the building's thermal behaviour. When simulated across two months the MPC approach performed better and achieved the same thermal comfort for a lower overall cost. The economic optimisation resulted in an energy saving of 650 kWh, with an associated cost savings of $240 (an improvement of 1.7% compared to the baseline), while the carbon optimisation gave negligible CO 2 savings due to the inability of the building to shift heating to low-carbon periods. Findings from this study indicate the potential for improving building performance via MPC strategies, however the level of impact will depend on specific building attributes. [ABSTRACT FROM AUTHOR]

• The optimal energy benefits of switchable insulation systems (SIS) are evaluated for office buildings. • When combined with precooling, optimally operated SISs can provide significant energy and cost reductions. • Optimal and hybrid controls are developed to operate SIS-integrated roofs and precooling strategies. • Optimized controls for SIS and precooling can reduce by over 20% energy use and 30% peak demand. In this paper, optimized controls to enhance the energy efficiency and demand response benefits of roof-integrated switchable insulation system combined with precooling strategies are evaluated for office buildings. A wide range of optimal cost functions are investigated to evaluate the total building energy saving as well as electrical peak demand shedding and shifting potentials. The results indicate that roof-integrated switchable insulation systems provide modest reductions even when optimally controlled of up to 5% and 4% savings in total building's energy use and electrical peak demand during a peak day. However, when precooling strategies are integrated with roof switchable insulation systems, optimal controls can enhance the performance of office buildings by reducing total energy use by up to 19% and electrical peak demand by up to 34%. Moreover, the analysis presented in this study demonstrated that roof-integrated SIS combined with precooling strategies offer significant potential to shape the energy demand profiles for grid-interactive efficient building (GEB) applications when optimized controls are deployed. [ABSTRACT FROM AUTHOR]

A great number of low carbon technologies have been developed in the last decades. The use of such technologies promises good indoor environment for the building's occupants, lower energy consumption and carbon emissions. However, there are uncertainties related to payback periods and usability constraints of low carbon technologies. In addition, past and current research has shown differences between the expected and the actual performance of buildings, both in terms of energy consumption and indoor comfort. For a better understanding of differences between expected and actual performance of buildings, it is necessary to investigate the energy consumption, the behaviour of the occupants and their interaction with new technologies, and the resulting indoor comfort. Monitoring building performance can help to reduce the uncertainties related to the building performance of buildings. This paper presents an overview and classification of data collection methods to monitor the energy consumption, thermal comfort of occupants and the operation of buildings in use. Data collection methods and techniques are categorised and linked to specific methods to evaluate building performance and recommendations are made to set up building monitoring research. By identifying the most effective methods to monitor buildings, this research aims at embedding performance monitoring in standard practice. [ABSTRACT FROM AUTHOR]

Moisture-related issues in buildings can accelerate the decay of building materials and increase occurrence of mould, resulting in significant economic and health implications. Transient hygrothermal risks assessment proved to be the most reliable approach, yet its application at early design stages is impeded by the high number of assumptions, input and skills required to be robustly applied. Climate-based indicators can assist in determining effective prevention design strategies based on the magnitude of the potential hygrothermal risks. However, in Australia, the National Construction Code relies on a climate zoning originally developed for thermal and energy efficiency provisions, clustering locations that present different moisture profiles. This paper investigates the suitability of the existing climate zones for hygrothermal risk indications by calculating the moisture index for several representative cites across Australia. Results reveal the current climate mapping to be unsuitable and too coarse to reliably provide robust indications for moisture management. Further, a new characterization of Australian climates for hygrothermal assessment purposes is proposed as a first step towards a better representation of moisture risks within the building code. [ABSTRACT FROM AUTHOR]

[Display omitted] • A research topic relatively new but with an increase interest in the last five years. • The largest scientific contribution from China, Australia and Italy. • The main journals in the field Building and Environment and Energy and Buildings. • Three main direction of research: thermal energy performance of buildings, ecological benefits and reducing the urban heat. • The main limitation of using green walls is the high cost of installing and maintenance. The continuous state of development of the human society imply a big effort and demand to generate and use more and more energy to power our lifestyle. The impact of human activity has negative effects on the environment and thus solutions to maintain or increase our development rate but in the same time to decrease the pressure on the environment must be developed. In this context, the purpose of this paper is to investigate if the use of green walls systems can be a solution to decrease the energy demands in buildings. The investigation include a bibliometric literature research, a scientometric analysis and an in-depth discussion. The data used for the research were obtained by interrogating the ISI Web of Science and Scopus databases, were selected using the guidelines of the PRISMA method and processed with the help of VOSviewer and Bibliometrix software. The research results indicate an increase interest in this topic in the last five years and that the use of vegetation in the constructed grey areas can bring a lot of benefits especially from environmental point of view. Green walls can be a solution to decrease the temperature on the wall surface in hot summer days and to prevent heat loses in the winter time, and thus have beneficial effects on the amount of energy required to maintain a proper interior temperature. The main limitation of using green walls is given by higher costs of installing and maintain the vegetation on walls, thus, finding new more economical, systems of green walls must be developed in the future. Considering all of this it can be state that green wall systems have the potential to become good solutions not just to improve the energy efficiency of buildings but also to create more sustainable urban areas. [ABSTRACT FROM AUTHOR]

Building energy use benchmarking is the process of measuring the energy performance of buildings relative to their peer group for creating awareness and identifying energy-saving opportunities. In this paper, we present the design and implementation of BEEM , a data-driven energy use benchmarking system for buildings in Singapore. The peer groups for comparison are established using a public energy disclosure data set. We use an ensemble tree algorithm for accurately modeling building energy use and for identifying the most influential factors. Our models reduce the prediction error from 24.39% to 6.04%, on average, when compared to the baseline linear regression models, which were used in the previous energy efficiency labeling program in Singapore, and outperforms ten other recent models. Using the prototype implementation of BEEM, we benchmarked three building types, office (290), hotel (203), and retail (125), and compared their rating. The code repository and the accompanying data set are released as an open-source project for community use. [ABSTRACT FROM AUTHOR]