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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]

• 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 • Most of the existing calculation methods are outdated and do not fit climate-proof buildings.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] • Building policies must be rooted in a good understanding of the targeted population. • Building performance standards may benefit from creating databases of weather files. • A thermal performance analysis should consider multiple key performance indicators. • Building performance policies should address the thermal resilience of buildings. This paper presents the main challenges faced and lessons learned when developing a new method to assess the thermal performance of residential buildings for the recently updated Brazilian building performance standard, NBR 15575–1:2021. It touches on subjects related to the representation of occupant behavior, climate, and thermal acceptability in building performance simulation, as well as the use of reference models, key performance indicators, and performance levels in policies. NBR 15575 provides a thorough procedure to analyze thermal performance, allowing buildings to be assessed while in passive operation mode and also accounting for energy needs when active operation is necessary. Multiple key performance indicators are introduced to provide a comprehensive evaluation. The main difficulty found was dealing with diversity. Given the vast scale of Brazil's territory, a high variation in culture, climate and construction techniques is expected, thus requiring a compromise between detail and scalability. There are still many opportunities for improvement, especially regarding the representation of occupants, and adjustments of the characteristics of reference models to promote high thermal performance, considering the diverse climates, regional practices, and economic needs. This paper might help researchers and other stakeholders to develop and improve other local standards and protocols, especially for warm climates. [ABSTRACT FROM AUTHOR]

Feature engineering and data-driven classification models are at the forefront of analysis of large temporal sensor data from the built environment. In previous efforts, temporal features were engineered from the whole building hourly electrical meter data from 507 non-residential buildings. These features fall within the three general categories of statistics, model, and pattern-based and can be used to identify various behavior in the structure of the whole building electrical meter data. In this paper, a deeper investigation is made of exactly what types of behavior are most important in the context of two classification scenarios: the primary use of a building and the level of performance the building has when compared to its peers. The highly comparative time-series analysis (hctsa) toolkit is used to analyze the most important temporal features for the classification of various building performance attributes. In the first analysis, a comparison is made to distinguish the behavior between university dormitories (70 buildings) and laboratories (95 buildings) as an example of interpreting the classification of the primary-use-type of a building. In the second analysis, a comparison of buildings with high (165 buildings) versus low (169 buildings) consumption is used to extract and understand the behavior that indicates the level of the energy performance of a building. These two case study examples provide a foundation for further explainable machine learning techniques in both classification and prediction as applied to buildings. This effort is the first example of machine learning with an explicit focus on the interpretability of classification for smart meter data from non-residential buildings. [ABSTRACT FROM AUTHOR]

Highlights • Studies using questionnaire for collecting energy data in buildings are reviewed. • Investigations are classified according to data collection methods and objectives. • Problems about terminology, identity of recipients, and response rate are highlighted. • The review provides suggestions and guidance on the use of questionnaire. Abstract The paper presents a review of the literature on the use of the questionnaire as a tool for collecting energy data in residential buildings. Numerous studies used the questionnaire to gather necessary information for different purposes. However, even using the same tool, the procedures differ in terms of distribution and compilation, contact with the interviewees and type of proposed questions. One hundred thirty-seven studies were considered in the review, including both scientific articles and surveys reports. The available works were analysed and classified according to the geographical origin, period, sample size, sample structure, data collection methods, response rate, data processing, and objectives of the investigation. In the 80% of the selected studies, the questionnaire is used as unique tool for data collection, albeit cases in which the questionnaire is coupled with other survey techniques, such as field measurements and time use surveys, have also been recorded. The in-person interview is the most common completion option in the sample and it is also the method that produces the highest response rate (77.6%). Generally, the collected data are subjected to statistical processing (over 80% of the cases). Regarding the objective of the surveys, the questionnaire is mainly employed for investigations on energy consumption and occupants' behaviour, but also other purposes were identified. Overall, the revised sample and the experiences reported are largely varied and heterogeneous. The lack of a homogeneous methodology appears in the use of an extremely diversified terminology. Therefore, the codification of a reference method and the standardisation of the nomenclature would be desirable. It would be useful to define general guidelines to be followed when designing surveys by using questionnaires. The review provides some suggestions and guidance on the use of questionnaire, highlighting strengths and weaknesses, and represents a source of information for future researches focused on the energy performance of buildings. [ABSTRACT FROM AUTHOR]

Highlights • The weighted average values of thermal energy consumption (oil and natural gas) for space heating, as of 2011, of the complete stock of buildings in Greece used as primary residences (insulated or not, single-dwellings or apartments), is estimated to 60.9 up to 130.1 KWh·m−2·year−1. • The mean actual thermal energy consumption for space heating of residential buildings is much lower than that evaluated based on HDHs or the method of Hellenic Building Energy Performance Regulation (REPB), according to European Directive 31/2010. • The implementation of the Hellenic regulation for building energy performance (REPB) imposed the improvement of thermal protection of the building envelope and the performance of the electrical and mechanical systems. • Applying the REPB minimum requirements on thermal protection reduce the space heating loads of residential buildings in all climate zones by 63% to 70%. The compliance of existing residential buildings to the minimum requirements of the REPB could result to about 24.4 TWh of savings in space heating energy annually. • The benefits of any National Regulation on Building Energy Performance should be examined on the basis of expected lower actual energy consumption. Abstract This paper presents the energy, the technical and the environmental characteristics of residential buildings in Greece, as well as their potential for energy conservation, based on their actual energy consumption data. The technical characteristics of residential buildings related to their energy performance (insulation, type of openings, system for space heating and cooling, etc.), the actual energy use (kWh.m−2.year−1) and the environmental factors (kgCO₂.m−2.year−1) related to energy consumption, are some of the parameters of this survey. The average annual specific energy consumption of residential buildings in Greece was 112 kWh·m−2·year−1 in 2014, the 6th lower consumption among the 28 European member states (EU-28) in which the average residential building energy consumption is of about 158.8 kWh·m−2·year−1. The potential of space heating energy conservation for Greek residential buildings was estimated, based on (i) the 2011 heating energy consumption data and (ii) the percentages of space heating energy conservation, calculated by analysing 144 different types of residential buildings, having various geometric and technical characteristics, such as the A/V ratio (envelope area to volume of building), the heating degree hours (HDHs) and various occupancy profiles. The resulting average actual energy consumption is much lower than that calculated using Heating Degree Hours (HDHs) or the method of Hellenic Building Energy Performance Regulation (REPB). Almost 45% of these buildings were built before 1980, without any thermal insulation or double glazing. The compliance of these buildings to the minimum requirements of the REPB (related to thermal insulation and the efficiency of their electromechanical systems), could result to about 24.4 TWh of savings in space heating energy annually, i.e. to about 32–175 kWh·m−2·year−1, depending on the climate zone that corresponds to 8.5–46.2 kgCO₂·m−2·year−1 reduction. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of building fabric, services and occupant related factors on actual energy use of six case study dwellings, located in three new low energy social housing developments in UK, covering a variety of built forms and construction systems (timber frame, hempcrete, steel-frame). Physical monitoring of indoor environment and window-opening is cross-related with building fabric and systems’ performance, and qualitative data gathered through occupant surveys, review of control interfaces and handover guidance, to understand the causes of the gap between modelled and measured energy use. Actual energy use is found to exceed design expectations by a factor of three, questioning the need for whole-house mechanical ventilation heat recovery (MVHR) systems at measured air permeability rates of 6 m³/(h.m²) against the design target of 3 m³/(h.m²). Lack of proper commissioning of MVHR and heating systems, combined with inadequate user comprehension about their operation and control leads to occupant ‘misuse’ wherein systems are de-activated, thereby negatively affecting indoor air quality. This is confounded by occupant factors related to higher demand temperatures, unexpected opening of windows during winters due to under-performance of MVHR combined with habitual behaviours, and over-use of heating systems to compensate for higher than expected air permeability. [ABSTRACT FROM AUTHOR]

In this study, the objective is to redesign a previous concept for a single-family Zero greenhouse gas Emission Building (ZEB). The concept is redesigned based on comparing greenhouse gas (GHG) emission loads and compensation from different design solutions applied in Norwegian single-family ZEB pilot buildings and selected sensitivity studies. The objective is to see if a previously developed ZEB model (2011) can be redesigned to achieve a life cycle energy and material emission balance (ZEB-OM), which previously was not achieved. Five different design parameters are evaluated: area efficiency, embodied emissions in the envelope, insulation thickness, heating systems and different roof forms with respect to the photovoltaic area. Embodied emissions reductions were possible in the ground foundation, from around 1 kg CO 2 /m 2 to 0.6 kg CO 2 /m 2 per year. Both models are able to compensate for all operational emissions. The new model is in addition able to compensate for 60% of embodied emissions, whereas the previous model only could compensate for 5%. The new model does not reach the life cycle energy and material balance. The paper presents and discusses different approaches for achieving the ZEB-OM balance. Further concept model optimization is needed. [ABSTRACT FROM AUTHOR]

Heating and cooling of residential buildings is accountable for a significant share of the EU's final energy consumption. In order to determine the current condition of the building stock and to implement appropriate measures and requirements to improve energy efficiency of buildings, a detailed analysis of existing buildings is essential. This paper aims at describing characteristics of the building stock of Salzburg by analysing energy performance certificates. Therefore, the building stock is grouped into archetypes based on the construction period, building condition (not-retrofitted and retrofitted) and building type (single-family house and multi-family house) and then analysed regarding energy need for space heating, energy carrier, heat emission system, share and U-values of building elements and window to wall ratio. The analysis of the data demonstrates that the structure and naming conventions within the EPC-database pose hurdles for a correct investigation of the data. A comprehensible and distinct notation as well as versioning is inevitable for the sake of avoiding a loss of information and enabling international comparability. An analysis of energy carriers of the archetypes reveals, that a significant share of buildings still uses fossil fuels like oil and gas for energy supply, although electricity (heat pumps) and district heating are on the rise for buildings constructed in recent periods as well as for retrofitted buildings, with heat pumps being the most important energy carrier for new single-family houses amounting to a share of 65 % and district heating for new multi-family houses amounting to a share of 46 %. A detailed observation of the thermal performance of buildings and building elements reveals high potential and practicability not only for energy efficient new buildings, but also retrofitted buildings throughout all construction periods and for both, single-family houses and multi-family houses (e.g. median U-values for retrofitted ceilings/roofs range from 0.17 to 0.26 W/(m2K) compared to a median of 0.14 W/(m2K) for not-retrofitted ceilings/roofs from the most recent construction period). The conducted analysis provides detailed statistical information on the Salzburg building stock and hence a robust basis for further studies regarding the thermal performance of the building stock and future scenarios by means of urban building energy modelling approaches. Furthermore, based on this information, policies for energy efficient buildings can be improved and adapted according to current circumstances. [ABSTRACT FROM AUTHOR]

This paper models scenarios for energy label based retrofit targets for Switzerland's residential building sector for 2050. It takes into account the magnitude and uncertainty in the energy performance gap (EPG) between labelled and actual energy consumption using actual energy performance data, as previous work highlighted that the EPG is not evenly distributed across different building labels. A building stock retrofit model is developed to estimate the potential energy savings from improving building performance through increasing energy label rating. A Monte Carlo analysis is applied using real EPG distribution data. The uncertainty in total energy savings is calculated for business-as-usual case and for three scenarios based on the different retrofit incentive policies of different Swiss Cantons. This allows to quantify the uncertainties in energy and emission outcomes of different policy targets arising from the variable EPG. The results show that with the business-as-usual approach it is impossible to achieve the objectives set (9.7 Mt CO 2 -eq/y vs 0.4 Mt CO 2 -eq/y by 2050). On the other hand, to reach the targets, a more aggressive policy aiming at renovating all buildings to the highest standards is necessary, that translates into a renovation rate that seems unrealistically high (3.4% per year until 2050 vs the proposed 1.4%). The contribution is to inform stakeholders designing new policies (notably the EU Renovation Wave policies) of the risk related to energy policies. [ABSTRACT FROM AUTHOR]

Reliable building simulation models are key to optimizing building performance and reducing greenhouse gas emissions. Informed decision making requires simulation models to be accurate, extrapolatable, and interpretable, all of which require calibrating model simulations to ground truth. Complicated building dynamics and highly uncertain exogenous disturbances make the model calibration process challenging and expensive; hence, a scalable and efficient calibration approach is needed to enable actual application. Current automatic calibration algorithms do not leverage data collected from multiple sources: for example, data obtained from previous calibration tasks on other buildings. In this paper, we employ probabilistic deep learning to meta-learn a distribution using multi-source data acquired during previous calibration. Subsequently, the meta-learned Bayesian optimizer accelerates calibration of new, unseen tasks. The few-shot (that is, requiring few model simulations) nature of the proposed algorithm is demonstrated on a Modelica library of residential buildings validated by the United States Department of Energy (USDoE). The proposed algorithm is compared against classical Bayesian optimization-based calibration, and it is shown that ANP significantly sped up the calibration procedure: the optimal model parameters are identified with 40–60% less simulations compared to the baseline. [ABSTRACT FROM AUTHOR]

• A systematic literature-approach to classify retrofitting is proposed. • An overview of Spain's previous guidelines on residential retrofits is presented. • A review of financial and subsidies mechanisms in Spain to renovate buildings is introduced. • A literature-based matrix on retrofitting actions is presented. • A classification of energy efficiency strategies for retrofitting is proposed. The building sector is responsible for more than 40% of final energy consumption in Europe; consequently, retrofitting existing buildings can significantly contribute to mitigate greenhouse emissions. Nevertheless, although the European Union has introduced relevant policy instruments, up to now the annual retrofit rates are considerably low with an average of 0.2% at European level. Understanding the past would support the success of the new strategies, such as the recent ones launched through the New Green Deal, which reinforces the importance of renovating existing buildings stock, as the main aim of the renovation wave. As a starting point for assessing the main challenges to allocate the Recovery funds, this paper provides a review of Spain's relevant literature to clearly define the characterization of the existing building stock, which actions have been typically considered under the scope of retrofits, and which strategies have been implemented until now, considering both, private and public initiatives and public financial schemes. The present work has a strong focus on energy-related strategies, although other interrelated actions are mentioned, such as accessibility measures and interior refurbishment of dwellings. Differences and similarities within these approaches are presented through the analysis of 27 relevant references of retrofitting actions and 52 references of financial mechanisms. As in Spain 93% of multifamily buildings were constructed prior to the national transposition of the first Energy Performance Building Directive (EPBD), and therefore are in need of deep energy renovations, the retrofitting of multifamily buildings topic has been widely addressed, even though often in a disjointed manner. The study suggests that although historically there have been several recommended strategies, few are conceived as integral actions, only 15% of the intervention packages refer passive and active energy-related measures and renewable energy incorporation. Furthermore, considering the antiquity of the building stock and the advantage of addressing the topic through clusters, only 63% of the resources directly refer these actions to specific clusters among the six distinctive periods, although in most cases focusing their recommendations on buildings constructed before 1980 where the worst energy performance buildings are concentrated. Concerning public financial and funding instruments, the research illustrates that there has been a substantial increment of programs over the last years promoting energy-related measures, renewable energy and other complementary aspects such as accessibility and interior renovations, mainly for older clusters. Nevertheless, the funds constitute only 8% of the necessary declared investments, which along with the dispersion between the different procedures and the complexity of the processes, have significantly reduced the global impact of these actions without generating robust and oriented market dynamics. Despite the several resources found, both financial instruments and guidelines tend to describe in more detail strategies related to heating demand and consumption and not delve into other relevant actions for warmer climates, fact associated both to the dynamics coming from other countries, and to a vision of the past in which people do not consume refrigeration. This clear focus on heating loads rather than cooling could present limitations for warmer regions in the near climate-change future. [ABSTRACT FROM AUTHOR]

This paper is focused on the optimization of the Passive House concept for single-family houses in the climatic context of the Southern Brazilian region, using two approaches: 1) Analysing the buildings' energy performance through the simulation method presented in the Technical Regulation of Quality for the Level of Energy Efficiency of Residential Buildings (RTQ-R); 2) Analysing the buildings' energy performance according to the Passive House concept approach, with optimization using a multi-objective evolutionary algorithm. Three single-family houses built with basic passive strategies were selected as the case studies for the Bioclimatic Zones BZ1, BZ2 and BZ3 of the Southern Brazilian region. These buildings were geometrically modeled and each profile for usage and occupation were defined. Posteriorly, the thermal and energy performance of the buildings have been performed through the classification of the energy efficiency level of the envelope, according to the RTQ-R standard. Then, the Passive House concept was applied to the three reference buildings and the optimization process has been performed using the multi-objective algorithm to instruct the dynamic simulation software. In the models with the Passive House concept, it has been observed a reduction in energy demand of 83.5%, 56.3% and 55.1%, and a reduction in thermal discomfort, on an annual comfort basis established between 20 and 26 °C, from 83.5%, 73.7% and 86.2% for buildings located in Bioclimatic Zones BZ1, BZ2 and BZ3 respectively. To improve the buildings' thermal and energy performance in the climates corresponding to Bioclimatic Zones BZ2 and BZ3, it was necessary to adopt the windows opening strategy in order to increase the system's air renewal rate through natural ventilation, combined with the MVHR system. It has been concluded that through the use of the Passive House concept optimized to the Southern Brazilian climate region, a significant increase in terms of thermal comfort was attained whilst drastically decreasing the energy demand of buildings. [ABSTRACT FROM AUTHOR]

• Most effective temporal features from smart meter data for building characterization are found. • State-of-the-art feature selection methods and a proposed customized approach are utilized. • Importance-in-prediction based features that improve building classification are determined. • Number of utilized features is substantially reduced while the accuracy is also enhanced. The present paper aims at determining the most influential features to be extracted from smart meter data to facilitate machine learning-based classification of non-residential buildings. Smart meter-driven remote estimation of the chosen characteristics (the buildings' performance class, use type, and operation group) is significantly helpful in buildings' commissioning, benchmarking, and diagnostics applications. As the first step, state-of-the-art feature selection methods and a proposed customized approach are utilized for determining the most influential parameters in the pool of temporal features, proposed in a previous study. Next, importance-in-prediction based features, generated from an hour-ahead load prediction pipeline, that can improve the classification accuracy are proposed and added as additional input parameters. Finally, interpretations about some of the most influential features for different classification targets are provided. The obtained results demonstrate that, while aiming at estimating the buildings' use type, through performing feature selection and adding importance-in-prediction based features, the number of utilized features is reduced from 290 (initial pool of features proposed in a previous study) to 29, while also increasing the accuracy from 71% to 74%. Similarly, number of employed features for estimating the performance class is decreased from 224 to 17 and the achieved accuracy is improved from 56% to 62%. Finally, using only 6 selected features, compared to 287 features in the initial set, the obtained accuracy for the classification of operation group is increased from 98% to 100%. It is thus demonstrated that the proposed methodology, through selecting and utilizing notably fewer features, results in a notable simplification of the feature extraction procedures, improves the achieved accuracy, and facilitates providing interpretations about the reason behind the influence of some of the most important features. [ABSTRACT FROM AUTHOR]

• In-situ monitoring allows for a more reliable estimation of envelope performance of residential buildings. • Policy differences are one of the main causes for the variation in building envelope performance across regions. • Potential global warming impacts ought to be considered when pondering on the future direction of envelope development of residential buildings. • Interactive policy framework underscores the necessity of devising more comprehensive public policies pertaining to energy saving. Climatic conditions can exert significant impacts on energy demand of residential buildings. Therefore, case-based evidence is necessary for aiding local policy making on building energy performance. By designing and carrying out in-situ monitoring campaigns respectively in Cambridge, Hong Kong and Shanghai, we present in this paper a cross-regional analysis of actual building envelope performance in these three climatic regions that operate under different energy efficiency policies. Compared with conventional tabulated data, information gleaned from the method of in-situ monitoring shows lower uncertainty and higher precision, especially when the wall has good thermal properties. By comparing practices in different regions and with accurate post-occupancy thermal data, the analytical results further show that the effectiveness of building-related policies on energy performance varies across regions. This is one of the pioneering studies that make interactive policy recommendations based on the evidence obtained from cross-regional, in-situ monitoring campaigns. [ABSTRACT FROM AUTHOR]

In this paper the findings from a long-term field study of the thermal performance of a circa 1950s dwelling are presented and discussed. The study aimed at evaluating the robustness of the QUB method in the field under UK climatic conditions. A series of 147 QUB tests were performed during the whole heating period (September 2016 – March 2017) in a detached house located in the University Park campus, University of Nottingham considering two distinct conditions: as-built and with increased airtightness. The QUB method was able to provide consistent and robust estimates of the Heat Transfer Coefficient (HTC) of the whole dwelling with approximately 80% of the results within ± 10% from the mean and more than 95% of the results within ± 15%. The need to treat heat losses occurring through the ground when assessing the thermal performance of buildings through experimental diagnostics methods was highlighted, especially in uninsulated concrete slab floors. The method devised to isolate the ground floor heat losses from the whole building losses resulted in reduced dispersion of the adjusted Heat Transfer Coefficient with a coefficient of variation of 5% and 98% of results within ± 10% from the mean. [ABSTRACT FROM AUTHOR]

• Role of corridors in the overheating of multi-residential dwellings was assessed. • Three TM59 compliant corridors/flat scenarios were compared to monitored data. • Propensity of corridors to overheat and exacerbate overheating in flats is nuanced. • Discretisation of flat/corridor boundary conditions may be masking dominant effects. • A new method is proposed for the consistent and replicable modelling of corridors. Prolonged overheating can have serious cumulative effects on human health, resulting in heat exhaustion, heatstroke and even death. The frequency and severity of heatwaves will increase considerably in the future as a result of accelerating climatic changes compounded by increasing urbanisation. A recent overheating risk-assessment methodology, Technical Memorandum (TM)59: 2017 was developed by the Chartered Institution of Building Services Engineers (CIBSE) to address this problem, by providing a consistent framework for the evaluation of overheating risks in new homes. TM59 has for the first time highlighted the importance of including corridor heat transfer effects in the dynamic modelling of multi-residential dwellings. This paper investigates the strengths and limitations of current approaches to the modelling of corridors, based on a case study of three energy-efficient flats located in London. The results of modelling in accordance with TM59 guidance are compared with alternative approaches, using more realistic occupancy and weather information, and compared to empirically measured data. The findings of this study indicate that current practices in Building Performance Simulation (BPS) are likely to under-estimate the actual air temperatures in corridors. This study highlights the need for further research into the way in which corridors, flats and their interconnecting ventilation and heat transfer networks are commonly discretised in BPS models. [ABSTRACT FROM AUTHOR]

• A methodology was represented for calibrating the building energy performance model. • Accurate calibration was achieved on the model even with the short-term measurement. • The calibration process was utilized the MBE- CVRMSE and obtained an enhanced accuracy. • The HDD and CDD was applied in the absence of the real weather data. • The accurate model also provides the opportunity to trail the systems' performance. The calibration process has an excellent advantage, especially for large-scale projects that manage the potentially complex energy performances of various building systems. It also provides great advantages when the annual real-time measurements are not available since the created model can be calibrated with short-term measurements to obtain an accurate annual energy performance. This paper presents a methodology for creating an energy performance model based on a calibration process of a large-scale residential building incorporating heating and cooling energy consumptions. The main purpose is to calibrate the building energy model by utilizing mean bias error (MBE) and coefficient of variation of root-mean-squared error (CVRMSE) indices and obtain the annual building-energy performance with enhanced accuracy. Furthermore, two novel approaches were developed. The first is to provide accurate weather data in the absence of real weather data by taking advantage of available data for heating degree days (HDDs) and cooling degree days (CDDs). The second is to provide accuracy on the collected data of measurements by taking advantage of the predicted data of short term measurements. A methodology is evolved to calibrate the building model by using real-time short-term monitored data from the building. The methodology consists of four main steps and further sub-steps. Modeling, the first step, covers the collection of input data and the development of the model stages. Measurements, the second step, covers the process of data collection for calibration. Improvements for calibration represent the third step, where different versions of the model are developed by changing the input parameters of the model within the defined ranges of variation (ROV). Then, the results of the obtained versions are compared with the real-time measurements, and MBE and CVRMSE values for each version calculated to examine the model's accuracy. Finally, when the model is considered as calibrated, the simulation is run to obtain the annual energy performance of the building for better precision. The results in the model run here show the monthly MBE and CVRMSE values for the initial version to be 15.12% and 17.19%, respectively. After applied strategies, these values are improved according to the calibration criteria defined by ASHRAE to −2.76% and 8.40% respectively, which is considered as calibrated. Overall, it is usually hard and costly to track the real-time energy consumptions of buildings for a long period. Annual building energy consumptions can be obtained accurately by calibrating the building model with the short-term measurements. An accurate model gives the opportunity to trial the performance of each building system. [ABSTRACT FROM AUTHOR]

• Two alternative air tightness test methods are examined for use in high-rise MURBs. • A sequential pressure neutralization test is successfully performed in a MURB suite. • Field test results are used to calibrate a CONTAM air flow model. • The Love and Passmore method exhibited a characterization error of 108%. • The Lstiburek method exhibited a characterization error of 0.2%. Blower door testing is commonly used to characterize exterior façade air leakage in buildings. This characterization is needed to improve the accuracy of energy models and certify building performance. Performing these tests in large buildings requires air flow rates that are sometimes impractical to achieve using available equipment, which necessitates testing in individual zones within those buildings. However, when performing these tests in individual zones, the conventional whole-suite tests are unable to isolate the required envelope flow characteristics and pressure neutralization tests are, in most cases, too logistically difficult to perform, which necessitates an investigation into alternative methods. In this study, two methods developed for use in row housing were adapted to a high-rise multi-unit residential building (MURB) context in which the test suite is surrounded by adjacent suites: The Love and Passmore method, and the Lstiburek method. The efficacy of these adapted techniques was assessed in a single suite located in a high-rise MURB that followed typical North American construction habits. To carry out these assessments, a combination of field data and calibrated CONTAM simulations are used. For the case study building, the Love and Passmore method exhibits exterior boundary characterization errors of 108%, and is inappropriate for this characterization in high-rise MURBs. Alternatively, the Lstiburek method exhibits an exterior boundary characterization error of 0.2%, but additional analysis showed the Lstiburek method exhibits greater sensitivity to measurement noise than the pressure neutralization method. As a result of this increased noise sensitivity, and because of the similar labour and equipment requirements, it is therefore also not recommended as a replacement for the pressure neutralization method. It is important to note that buildings constructed using different details and techniques may exhibit different results, which is a limitation of this study. Details related to these tests, including a discussion of potential shortcomings and strengths, are presented in this paper. [ABSTRACT FROM AUTHOR]

A strong correlation exists between occupant behaviour and space heating energy use. In particular, the occupancy status (e.g., daytime absence) is known to have a significant influence on residential heating load profiles, as well as on cumulative heating energy consumption. In the literature, many occupancy models have been utilised to predict occupancy profiles of individual dwellings as part of the larger residential building stock. However, none of the existing models consider diversity associated with occupancy-integrated archetypes to generate high-temporal resolution heating load profiles. The current paper uses Time Use Survey (TUS) data to develop a high-temporal resolution residential building occupancy model. The key feature of the proposed model, implemented using MATLAB, is the ability to generate stochastic occupancy time-series data for national population subgroups characterised by specific occupancy profiles. It is shown that the results are capable of closely approximating data available from TUS. The developed model can be applied to improve the quality of modelled high-temporal resolution heating load profiles for generic building stock characterised by population subgroups represented by different occupancy-integrated archetypes. A case study is performed on a building stock sample located in London, UK. The developed occupancy model has been implemented in MATLAB and is available for download. [ABSTRACT FROM AUTHOR]