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The aim of this paper is to evaluate and illustrate the energy saving potential of the façade addition on existing and low energy performing block buildings in different climatic contexts. To achieve this purpose, the paper illustrates some outstanding case studies on deep renovation through façade and volumetric additions, as reference possible solutions towards energy renovation. To further assess the energy potential of these transformations, the same solutions have been applied to a reference building in Bologna. In particular, a selected apartment of typical building block has been investigated and simulated in detail, to identify the buildings’ energy requirement and propose different retrofitting hypotheses towards nearly Zero Energy Buildings (nZEBs). Simulations of these different hypotheses resulted in corresponding diverse energy performances, from the very low grade of performance in “as built” scenario, up to nearly zero energy demand, for selected technological solutions applied in specific climatic contexts. To further estimate the energy impact the same apartment has been “extracted” from its original climatic context and energy simulations have been also carried out in two different climatic zones. Obtained results prove that façade additions are a very powerful solution towards the aim of zero energy in existing buildings. [ABSTRACT FROM AUTHOR]

Building energy consumption forecasting is crucial for energy managers and policymakers. However, acutely predicting the energy consumption of any building is more important in energy efficiency benchmarking of buildings. Energy benchmarking is a precise technique for measuring, tracking, and reducing end-use energy usage of buildings by employing comparative scenarios. Bottom-Up energy consumption assessment has been used in several studies to evaluate a collection of buildings' energy performance to a standard. Traditionally, researchers have used a single approach to predict the energy use of buildings and to conduct benchmarking. However, it has been found that doing so frequently compromises the accuracy of the predicted energy use of buildings. It also has an adverse effect on the buildings' energy benchmarking framework results. This paper will provide an energy benchmarking framework for residential buildings based on the blending techniques of multiple approaches. Over 3000 datasets were gathered from the Indian city of Jaipur. In order to analyse the trends in energy consumption, the data were divided into categories based on economic levels. The data is then subjected to some fundamental statistical analysis, along with several approaches are blended to forecast the energy consumption of the buildings with the highest accuracy. These benchmark levels set guidelines for assessing and recognising strong performance while also identifying underperforming buildings and giving them more priority for energy efficiency improvement. The technique may be used for different metropolitan levels and climatic conditions. [ABSTRACT FROM AUTHOR]

Abstract Dwellings with no heating, ventilation and air conditioning (HVAC) systems are commonly found in many countries. The long-term thermal performance of these buildings can be assessed based on hourly data of occupant thermal discomfort integrated over the required timespan (e.g. total degree hours of discomfort per year). This approach can be easily applied when simulation is adopted in the assessment, but field studies using this approach are rare as they would require complex, costly and long measurement/survey campaigns. This paper addresses the challenges on conducting field studies on long-term thermal performance of dwellings with no HVAC system by introducing a novel performance indicator: the Seasonal Thermal Sensation Vote (S-TSV). S-TSV adopts the standard 7-point thermal sensation scale and is based on the perceived overall thermal sensation recalled by the user of the building for specific seasons and times of day. The new performance indicator is not intended to replace existing ones, but to complement them in the understanding of the complex thermal performance processes taking place in buildings with no HVAC. S-TSV was applied in a field study targeting a small sample of dwellings in Brazil. Results demonstrate the capabilities of S-TSV to describe trends in buildings performance in this sample. S-TSV also assisted on the identification of relationships between such performance and some independent variables addressed in this field study (e.g. windows operation, footwear and income), considering a threshold of p -values <0.05 on the chi-square statistic test. [ABSTRACT FROM AUTHOR]

The cost-optimal analysis represents a useful tool to stimulate the refurbishment of existing buildings, highlighting the minimal global cost that private or public users have to sustain in order to attain appreciable energy savings in the building life span. The identification of precise interventions on the building-plant system could steer legislators to the emanation of appropriate financial incentives in order to make the refurbishment of existing edifices more attractive. However, the cost-optimal solutions cannot be generalized as they are strongly influenced by the initial conditions and by the climatic context. In this paper, a traditional social housing unit, realized in Italy during the 1970s, largely widespread and strongly energy-consuming, was analysed in two different climatic zones belonging to the Italian territory. Suitable interventions were identified for the reduction of energy requirements for heating, cooling and domestic hot water production. These analyses were carried out by using the same simulation tool for energy and economic performances, highlighting the deviances among the cost-optimal solutions, the n-ZEB target and the minimal interventions for the containment of energy consumptions imposed by the current Italian legislation for buildings subjected to refurbishment. [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]

The selection of a thermal comfort model for establishing indoor optimal hygrothermal conditions during the hot period has a major impact on energy consumption of Net Zero Energy Buildings in hot climates. The objective of this paper is to compare the influence of using different thermal comfort models for zero energy buildings in hot climates. The paper compares the impact of applying Fanger's model, Givoni's model, the ASHRAE 55 adaptive comfort model and the EN 15251 adaptive comfort model on energy consumption and comfort performance. Using both the building performance simulation tools ZEBO and EnergyPlus for energy simulation, an existing prototype of a residential apartment module is used to evaluate energy performance and thermal comfort in two parametric series. The first one is the result of coupling natural ventilation and mechanical cooling and the second one is guided coupling natural ventilation, mechanical cooling and ceiling fans. This study shows that the percentage of energy consumption difference meeting the comfort criteria according to ISO 7730 in comparison to EN 15251, ASHRAE 55 or Givoni's model varied up to 16%, 21% and 24.7%, respectively for the presented case study. More energy savings can be expected for buildings in hot climates with greater cooling demands. [ABSTRACT FROM AUTHOR]

• Provided a platform to test various residential building control systems. • Used probability of occupancy to determine setback temperature when unoccupied. • Integrated optimizer with adaptive and occupancy control. • Generated dynamic electricity tariff based on wholesale electricity pricing. • Evaluated the peak load shaving potential with dynamic pricing and optimization. Energy consumption in buildings continues to rise with increased deployment of energy-consuming equipment such as Heating, Ventilation, and Air Conditioning (HVAC) amid a growing world economy. Renewable energy is projected to comprise a majority of the future electricity supply, but the intermittent nature of renewables means that consumption must respond to dynamic supply for optimal utilization. This paper proposes a novel HVAC control strategy for residential buildings using the adaptive comfort model, considering occupancy through probability and real-time information, and optimizing the HVAC schedule to reduce cost, maintain thermal comfort, and respond to the dynamic availability of renewable energy while being generalizable to different situations. To validate this approach, the Universal CPS Environment for Federation (UCEF) co-simulation platform is used to connect advanced building controls with the building energy simulation software EnergyPlus. Simulations are performed for a residential building in Sacramento, CA during a typical summer week. Economic impacts, energy consumption, and thermal comfort are analyzed for traditional, adaptive, and occupancy-based control strategies under demand-based, tiered, and fixed electric tariff systems. Simulation results show that occupancy consideration, adaptive thermal comfort, and optimization can reduce cost by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 % compared to traditional fixed setpoints. The ability of the proposed HVAC control strategy to shift energy consumption away from peak times under a demand-based tariff system is qualitatively analyzed and findings suggest that maximum load-shifting on a grid-scale is attained using occupancy consideration with optimized control and demand-based pricing. For individual residential buildings, similar economic benefits can be gained using the less-complex adaptive HVAC control strategy with existing tiered or simple electric tariff systems. [ABSTRACT FROM AUTHOR]

The application of large area of glass is still the main utilized strategy to count for the deep-rooted preference for the full external view as well as daylight penetration in residential buildings. However, for the successful renovation of old residential buildings, the application of full-height glass window should be made a major priority. This paper presents a sustainable approach on the current set-up of the multi-apartment renovation process in terms of sustainable lighting. Among the conducted investigations, the paper includes the case study analysis for the experimental applications of a double skin facade aimed at finding out the optimal configurations that could utilize daylighting demands. Also, currently applied mechanisms in the identification and evaluation of daylighting efficiency, data analysis for the measuring of light energy efficiency as well as the processes involved in the determination of daylighting feasibility control for the renovation process utilizing the developed glazed wall are presented in this paper. This paper gives an insight into recommendations and research findings that could be used to further improve this process. [ABSTRACT FROM AUTHOR]

Over the last years there have been frequent changes to buildings’ thermal legislation, to cope with increasing environmental restrictions and a wider consumer awareness. This work has a twofold objective: 1 – provide an overall methodology to evaluate changes in buildings’ thermal regulations; 2 – to assess the economic merit of these regulatory changes, which have a profound economic impact especially on homeowners, tenants and the global urban real estate market, but also on the society through wider environmental impacts. The literature has provided several contributions at the scale of buildings, but few at the scale of cities (or even regions). This paper uses the city of Lisbon (Portugal) as a case study to test the methodology and determine the economic impact of the changes made in the thermal legislation by the Government. The economic assessment was made at 3 levels: financial analysis, economic analysis and social-economic analysis. It was found that the new regulation brings not only environmental benefits but also economic benefits in long term at both individual and social level. It was furthermore concluded that the impact of those benefits are geographically uneven, and old areas of the city with worse energy ratings have better economic indicators. [ABSTRACT FROM AUTHOR]

In light of current climate change projections in recent years, there has been an increasing interest in the assessment of indoor overheating in domestic environments in previously heating-dominated climates. This paper presents a monitoring study of overheating in 122 London dwellings during the summers of 2009 and 2010. Dry Bulb Temperature and Relative Humidity in the main living and sleeping area were monitored at 10 min intervals. The ASHRAE Standard 55 adaptive thermal comfort method was applied, which uses outdoor temperature to derive the optimum indoor comfort temperature. It was found that 29% of all living rooms and 31% of all bedrooms monitored during 2009 had more than 1% of summertime occupied hours outside the comfort zone recommended by the standard to achieve 90% acceptability. In 2010, 37% of monitored living rooms and 49% of monitored bedrooms had more than 1% of summertime occupied hours outside this comfort zone. The findings of this study indicate that London dwellings face a significant risk of overheating under the current climate. Occupant exposure to excess indoor temperatures is likely to be exacerbated in the future if climate change adaptation strategies are not incorporated in Building Regulations, building design and retrofit. [ABSTRACT FROM AUTHOR]

Abstract: The increase of peak and energy demand during the cooling season is becoming a crucial issue, as well as the intensification of the urban heat island effect. This trend is observed at several latitudes, including areas where overheating was unknown at building and urban levels. This phenomenon involves different issues: reduction of greenhouse gases, quality and comfort in outdoor and indoor environment, security of energy supply, public health. The building sector is directly involved in this change and adequate solutions can provide great benefit at energy and environmental levels. Roofs in particular are envelope components for which advanced solutions can provide significant energy savings in cooled buildings or improve indoor thermal conditions in not cooled buildings. Cool materials keep the roof cool under the sun by reflecting the incident solar radiation away from the building and radiating the heat away at night. Roofs covered with vegetation take benefits of the additional thermal insulation provided by the soil and of the evapo-transpiration to keep the roof cool under the sun. These two technologies are different in: structural requirements, initial and lifetime maintenance costs, impact on the overall energy performance of buildings. This paper presents a numerical comparative analysis between these solutions, taking into account the several parameters that affect the final energy performances. By means of dynamic simulations, the paper depicts how cool and green roofs can improve the energy performance of residential buildings in different localities at Mediterranean latitudes. [Copyright &y& Elsevier]

One of the challenges of utilizing solar PV in residential buildings is the management of load in accordance to the intermittent nature of solar resource. In this paper, Mixed Integer Linear Programming (MILP) is proposed to effectively plan and allocate load for consumption in such a way that the user defined priority of loads are conserved. In this way, the loads are made to follow the battery state of charge in accordance to the intermittent nature of solar resource without adversely affecting the quality of life of the user. In doing this, energy audit of a typical 4-bedroom residential building belonging to a medium-income family is carried out and classified into controllable and non-controllable loads. The energy audit is also used to size the PV system and the battery bank taking into consideration the financial status of the user (i.e. adequately sized and under-sized PV system based on financial status of the user). A load manager based on MILP with solar resource load following capability is thereafter developed and implemented in a computational program to manage the load based on user’s priority. Six scenarios are created to gain insights into the effectiveness of the proposed load manager. The results reveal that the proposed technique is effective in allocating loads based on the available solar resource in such a way that the user priority is maintained. [ABSTRACT FROM AUTHOR]

Building Archetypes (BAs) are often used in modeling urban-scale building energy consumption profiles to represent the energy consumption behavior of typical buildings within the modeled urban environment. One current approach to the development of BAs involves the creation of Building Energy Models (BEMs) using surveyed data coupled with codes, standards, or engineering experience. Another approach is the modification of existing standardized BEMs using available data to produce a suitable BA for the representation of the building stock. The adoption of either of these methods has been treated as an axiom or a step that did not need much consideration. However, the results produced by BEMs created according to different methodologies present several differences. The discrepancy in the produced results is shown not only in the results of the BEMs developed according to different methodologies but also in the degree to which these results vary when changing input values. Limited studies analyzed the sensitivity of these models to uncertain inputs, even though it is essential for the development of BA libraries. This paper comparatively investigates the Region-Specific (RS) and Department of Energy (DOE)-based BEM creation methods for BA library development. The models are developed by following the two methodologies, and their predictions are compared to the metered data from a high-rise residential building in the Marina district of Lusail City, Qatar. A Global Sensitivity Analysis (GSA) method is used to identify the most influential parameters contributing to the energy consumption variation of these models. Further, a parametric simulation campaign is conducted by varying the inputs determined earlier to quantify the BEMs' output variability. According to the results, the baseline RS BEM and DOE BEM yield an Energy Use Intensity (EUI) of 211.03 kWh/m2 and 137.9 kWh/m2, respectively. The deviation of these values from the metered EUI of 185,37 kWh/m2 indicates that the RS BEM development methodology is preferable to the DOE BEM for the BA development. Based on the GSA results, regardless of the BEM development methodology used, the most important parameters contributing to output variation are the Cooling Setpoint, the Outdoor Air Requirements, the Equipment Power Density, and the Lighting Power Density. Further, the RS BEM's parametric simulations produce a mean cooling EUI of 324.83 kWh/m2, closer to the literature benchmarks than the mean cooling EUI of DOE BEM, 341.62 kWh/m2. The results obtained from the baseline model and the uncertainty analysis support the conclusion that a Region-Specific Model developed from the ground up serves to better represent high-rise residential buildings in regions with extreme climate conditions. The impact this work achieves is providing decision-making support for urban scale building energy modelers for future building stock representation efforts in such areas while also providing an expected uncertainty range for the developed high-rise residential archetypes. [ABSTRACT FROM AUTHOR]

In this paper, a value-engineering based integrated design approach is presented to improve energy efficiency of residential buildings. The design approach is based on reducing construction costs from oversizing structural systems of the building to allow investing in energy efficiency measures. The integrated design utilizes optimized selection procedure to identify set of measures that can minimize life-cycle costs while maximizing energy consumption for the buildings without exceeding budget thresholds defined by the value engineering analysis. The integrated design approach is demonstrated and applied to design a prototypical villa in Kuwait considering both homeowner and government perspectives to optimize the selection of energy efficiency measures. The results indicate that significant reductions in construction costs can be achieved due to commonly practiced oversizing of the villa's structural systems. These cost reductions are more than sufficient to cover the incremental costs of implementing optimally identified energy efficiency measures with the benefits of lowering annual energy demand by 70% compared to the current design practices in Kuwait. [ABSTRACT FROM AUTHOR]

• A conceptual framework of in-situ monitoring activities is proposed. • Meta-analysis and synthesis are conducted with 68 selected monitoring activities. • Previous papers have to some extent insufficient documentation of monitoring activities. • An empirical rule is proposed on setting of time interval and monitoring duration. • Research opportunities rest on high-rise buildings in hot humid zone. Occupant behavior has a significant impact on building energy consumption and sustainable development of the community. In-situ monitoring of occupant behavior is one of the most effective and widely used research methods. It collects data of occupant behavior using smart sensors in the natural environment and, if appropriately designed and applied, can effectively avoid bias in the results. However, previous studies have rarely discussed how to design and apply in-situ monitoring activities in residential buildings. This paper, through a comprehensive and critical literature review, aims to close the knowledge gap on in-situ monitoring of occupant behavior in residential buildings. Multiple review techniques were used. First, a conceptual framework of monitoring activities was proposed based on a narrative appraisal of related publications. Second, the body of literature was established through an exhaustive search of papers by Web of Science and Scopus, two popular search engines. In total, 68 monitoring activities from 74 journal papers were selected according to the inclusion criteria. Third, meta-analysis and meta-synthesis were applied to this body of literature under the conceptual framework to reflect the achievements of previous studies and to explore the challenges facing future research. Results show that previous studies had limited consideration of sampling methods, setting of time interval and monitoring duration, installation of sensors, and the impact of microclimate. Ignoring these issues would reduce the productivity of data collected from in-situ monitoring activities and thus bring bias into the results. To address such limitations, recommendations are given for the design procedure of in-situ monitoring activities. In addition, an empirical rule is proposed with regard to setting the time interval and monitoring duration. Possible areas of future research are also discussed, e.g. occupant behavior in high-rise residential buildings in hot humid zone. The findings of this paper should facilitate the application of in-situ monitoring in building energy research and familiarize future studies with regard to occupant behavior in residential buildings. [ABSTRACT FROM AUTHOR]

• End-use of electricity consumption in residential buildings in Gulf Cooperation Council countries was presented. • Discrepancies in certain indicators have been observed by the end-use of electricity consumption. • Improving the efficiency of air conditioners and thermal insulation of the walls are the best measures to conserve electricity in residential buildings. • The results can be used in areas with a similar climate, living standard, buildings types, and the inhabitants' behavior. Energy conservation and improvement in energy efficiency yield multiple technical, economic, environmental, and social benefits and realize comfort and sustainability of residential buildings (RBs). This review paper presents the end-use of electricity consumption in RBs and the results of economic analysis. In addition, a description and discussion of studies on energy conservation measures, Net Zero Energy Building, and renewable energy in RBs are discussed. The percentage of end-used energy consumption for different purposes obtained in many studies are often not consistent. Moreover, discrepancies in certain indicators have been observed, necessitating the need to clarify the factors in the consumption of electricity in RBs. Further, a few studies used the term energy consumption in buildings (total or electrical); however, specifying the type of buildings to identify and use the necessary indicators of energy consumption in each type of building are desirable. Furthermore, most studies emphasized improving the efficiency of air conditioners and thermal insulation of the walls as these are the best measures to conserve electricity. [ABSTRACT FROM AUTHOR]

Abstract: Manual ventilation of dwellings in winter consumes excess heating energy, as cold outdoor air replaces warm indoor air. The German government promotes ‘shock-ventilation’ (Stoßlüften), where all windows are opened simultaneously, fully and briefly, to minimise energy wastage. However, the predominant design of windows in Germany''s housing stock mitigates against this strategy, as these windows open inwards while their indoor ledges provide ideal storage for pot-plants and other objects, blocking normal opening. An alternative window setting, long periods of trickle-ventilation, can consume up to 20 times as much energy as shock-ventilation. This paper reports a pilot study of household ventilation capabilities and practices in the German municipality of Aachen. A statistical analysis indicates 29% of dwellings have sufficiently unimpeded windows to facilitate shock-ventilation, while householder interviews reveal reasons for reliance on trickle-ventilation, including convenience and underestimation of its energy consumption. Analysis of results using ‘social practice theory’ suggests three possible policy interventions to improve energy-efficiency of ventilation. The results suggest the need for a nationwide study to quantify energy wastage through mismanaged ventilation, not least because of its possible cost to the country, of several billion Euros annually, and the millions of tonnes of CO2 emissions it most likely causes. [Copyright &y& Elsevier]

Abstract: The paper presents life cycle energy (LCE) analysis of different types of residential buildings (one storey, two storey, and duplex and multi storey) in Indian context. A total of 10 houses’ designs were examined with energy saving features, e.g. thermal insulation on wall and roof, double pane glass for windows. One of these buildings was further examined to assess LCE performance with on-site power generation. Dynamic energy simulation tools DesignBuilder, e-Quest and EnergyPlus were used to assess energy performance of the buildings. LCE of the buildings is varying from 240 to 380kWh/m2 year depending on the type (envelope) of the building and climatic conditions. LCE savings of about 5–30% are observed with thermal insulation on wall and roof along with double pane glass for windows. It is found that net zero operating energy building can be achieved by on-site power generation from PV and wind turbine. LCE of the building for net zero operating energy is evaluated to be 71.24kWh/m2 year. [Copyright &y& Elsevier]

Abstract: In recent years, calibrated energy modeling of residential and commercial buildings has gained importance in a retrofit-dominated market. Accurate weather data play an important role in this calibration process and projected energy savings. It would be ideal to measure weather data at the building location to capture relevant microclimate variation but this is generally considered cost-prohibitive. There are data sources publicly available with high temporal sampling rates but at relatively poor geospatial sampling locations. To overcome this limitation, there are a growing number of service providers that claim to provide real time and historical weather data necessary for building modeling at 15–40km2 grid across the globe; common variables such as temperature and precipitation have been constructed on ∼1km2 grids . Unfortunately, there is limited documentation from 3rd-party sources attesting to the accuracy of this data. This paper compares provided weather characteristics with data collected from a weather station inaccessible to the service providers. Monthly average dry bulb temperature; relative humidity; direct normal, diffuse and global solar radiation; wind speed and wind direction are statistically compared. Moreover, we ascertain the relative contribution of each weather variable and its impact on building loads. Annual simulations are performed for three different building types, including a closely monitored and automated energy efficient research building. The comparison shows that the difference for an individual variable can be as high as 90%. In addition, annual building energy consumption can vary by ±7% while monthly building loads can vary by ±40% as a function of the provided location''s weather data. [Copyright &y& Elsevier]

[Display omitted] • The communal areas can have different levels of energy performance in the 15 types of public residential buildings under study. • Spatial design features can evidently affect the energy consumption in the communal areas. • The ability to harvest daylight serves as a key determinant of energy efficiency. • Both econometric and machine learning techniques are proved to be effective to generate reliable findings. In this paper, we construct a unique database for 1228 residential buildings in Hong Kong to investigate how the spatial features of these residential buildings affect the electricity consumption in the communal area. We choose Hong Kong for this analysis as the city owns a large number of standard-type residential buildings managed by the public institution, which could be affected strongly by environmental policies. Both the machine learning method, based on the Least Absolute Shrinkage and Selection Operator (LASSO), and econometric regressions are adopted to analyse the data. We first utilize the machine learning LASSO technique to identify the most relevant factors for the subsequent econometric analysis. Our results show that the electricity demand for relatively low consumption building types, such as Twin Tower, is 6% lower than that of the high consumption building types. Newly constructed buildings usually belong to the medium consumption types, with the estimated monthly electricity consumption per apartment in communal areas to be around 50.2 kWh on average in 2020. These findings shed light on the nexus between spatial features and energy use for complex buildings, potentially contributing to the better crafting of energy-saving policy and the improvement of residential building programmes. [ABSTRACT FROM AUTHOR]

• Temporal and seasonal variations of window opening in residences are explored. • Cross-sectional survey, photography and longitudinal monitoring are combined. • Window operation habits of residents are driven by natural ventilation and fresh air. • Logistic models for window opening are developed and differentiated by seasons. • Outcomes provides evidence for window operation strategies and accurate building simulation. Window operation behavior has been recognized as one of the pivotal factors affecting building energy efficiency and indoor environments. Such behavior could vary from one region to another. A holistic understanding of the temporal and seasonal variations in the operation of residential windows in the Yangtze River region remains insufficiently explored. This paper presents a multi-scale approach by combining cross-sectional surveys, photographic image observations, and longitudinal onsite measurements to investigate the window opening characteristics of residents. The advantage is being able to perform qualitative and quantitative analyses systematically upon the completion of each step. The methodology has been applied to a case study in Chongqing, China. A year-long study revealed the window operation habits of residents in this region who rely greatly on windows for natural ventilation in transient seasons and for fresh air in summer/winter, especially when heating and cooling systems are in operation. Logistic models were developed and differentiated by seasons: transient, winter, summer with natural ventilation, and summer with air conditioning. The models quantified the driving factors and their corresponding variations affecting window opening probabilities in different periods of a year. It can be integrated into building simulations with realistic profiles for more accurate prediction of energy consumption in buildings. The proposed research methodology is applicable to other regions. The gained knowledge of residents' window operation characteristics in this region provides evidence for window operations and building designs/retrofit strategies. [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]

• Effects of multi-zone heating systems in residential buildings are assessed. • Data obtained from 336 scenarios in Mediterranean climates are evaluated. • Results are evaluated under economic and energy criteria. This paper explores the effects of multi-zone heating systems in residential buildings in different Mediterranean climates. The aim is to evaluate their potential in residential sectors to provide a general basis from the results (from the energy and economic point of view). In addition, if feasible, a further detailed evaluation of this management strategy for optimising the energy use in residential buildings would also be carried out. To do so, the effects of two different zoning controls in different types of apartment, occupancy patterns, building characteristics and locations in Spain, have been assessed. Different combinations of these parameters have resulted in 336 different scenarios that have been dynamically simulated using Design Builder software. The obtained energy results have been analysed in detail. Moreover, an economic analysis of these results has also been carried out to evaluate the economic feasibility of these systems in residential buildings located in temperate climates. This has been calculated by evaluating the maximum investment that can be assumed in each scenario to achieve different payback periods (namely 10 and 20 years). The results obtained show that these systems could be a cost-effective strategy aimed at reducing the energy consumption in residential buildings, not only in cold climates, such as is shown in the literature (the majority of the studies found are located in the UK and northern countries), but also in more temperate climates, such as that of Spain. Savings of around 20% were obtained in the most usual scenarios in Spain (coherent with results obtained in previous studies in the UK found in the literature), showing that in several cases, the initial investment in zone-controlled systems could be paid off in less than ten years, especially in large apartments and the coldest weather conditions. [ABSTRACT FROM AUTHOR]

Thermal comfort evaluations in the built environment are essential to occupant's satisfaction and also building energy consumption. Traditionally, thermal comfort has been assessed by Fanger's PMV model that was developed based on extensive laboratory tests. However, it's been found that PMV predictions are not good in field studies, especially in buildings with natural ventilation. In this paper, machine learning (ML) algorithms were used to predicted occupants' thermal comfort votes (TCV) and thermal sensation votes (TSV), using 5512 sets of thermal comfort data collected in naturally ventilated residential buildings in fourteen cities in China. Environmental parameters, personal parameters, climatic types, and adaptive control measures were considered and used as input parameters for the ML model. It was found that environmental parameters (both outdoors and indoors), personal parameters (metabolic rate and clothing insulation), and climatic types all significant affect both TCV and TSV, while adaptive control measures only affect TSV but not TCV. Comparing with established models (PMV, ePMV and aPMV), the ML models had smaller errors in predicting TSV and TCV. Based on these results, we suggest that the ML, especially ANNs model was reliable in predicting occupants' TCV and TSV in naturally ventilated residential buildings, and performed better than traditional thermal balance based models. Moreover, using the new model, we found that acceptable temperature ranges in naturally ventilated buildings were far wider than the ASHRAE adaptive comfort zone, suggesting that appropriate models should be established based on local data. [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]