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[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]

While IEA EBC Annexes usually are focused on R&D about single energy technologies, their broad scale use in practice is of even higher importance to contribute to global energy goals. This practical application of low-carbon technologies on community scale has been the subject of Annex 51, carried out from 2010 to 2013. In this Annex, evaluating 25 community energy case studies of the 10 participating countries, a ‘Guidebook on Successful Urban Energy Planning’ has been extracted from these evaluations to directly address practical urban/energy planners and municipal decision makers. The main content of the Guidebook with respect to planning approaches is summarized in this paper, distinguishing between the different planning fields of ‘urban energy planning’, which is addressing whole cities and communities, and ‘local energy planning’, oriented to neighbourhoods or building clusters. The necessary link between both is emphasized, considering a city as an interconnected energy system requiring a holistic approach rather than a compartmented consideration. As a side effect, a general method to calculate the primary energy performance of buildings and neighbourhoods employing different energy systems, including energy efficiency or energy conservation technologies, was derived. Using appropriate system characteristics, such as seasonal performances, this approach can be applied for every energy system, and for every building or neighbourhood. It is presented in this paper supplying an example from one of the case studies. [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]

Among the various factors that affect building performance, occupant behavior (OB) has received more and more attention and has become a research hotspot in building design and operation in recent years. However, due to the remarkable randomness and diversity of OB in buildings, it is difficult to accurately describe its characteristics using a fixed schedule, which is a normal approach of most energy simulation tools. DeST, a whole building energy simulation tool offers the function of stochastic OB simulation so that the simulation results can be more in line with the actual situation. In the newly released DeST 3.0, the OB modules are developed based on the actual observed OB data and are divided into two parts: occupancy and occupant action modules. The occupancy module is based on the Markov chain, which simulates the occupant movements among the spaces inside and outside the buildings. The occupant action modules are proposed with an environment and event-driven stochastic infrastructure based on a three-parameter Weibull distribution, such as occupant shading, window, and air-conditioning (AC)/heating control behavior modules. This paper presents the OB modules development for coupled simulation in DeST 3.0 and discusses the effects of integrated simulation of occupant behavior on building energy consumption. Firstly, an overview of the current modelling efforts of OB is given, from the trend to the existing foundation. Secondly, the development of OB modules for coupled simulation in DeST 3.0 is introduced in-depth, including co-simulation of AC/heating control behavior, window behavior and shading behavior. Lastly, two case studies that realize coupled simulation using the developed modules are shown, one is the comparison between existing occupancy schedules from GB standards and the developed occupancy simulation, and the other is the comparison between the result of simulating with or without using AC/heating control behavior modules in two bedrooms of the residential building. [ABSTRACT FROM AUTHOR]

Research has shown the large effect that occupants have on buildings' performance. Uncertainties related to the actual energy consumption of buildings increase the risks for the investments in low carbon technologies. Monitoring building occupancy can potentially decrease these uncertainties by providing more information about the occupants and their behaviour. The objective of the investigation is to establish an approach to inform the design process (e.g. building simulation) by addressing the complexity of occupants behaviour. The approach integrates information on occupants' behaviour and attitudes regarding energy use and indoor conditions to determine the requirements for building simulation and energy calculations. This paper presents the results of two monitoring campaigns in which the approach was employed. The monitoring campaigns focused on two owner-inhabited apartments in Spain and three social rental dwellings in The Netherlands. The results have given first insights of the power of the methodology to obtain detailed and understandable data on the occupancy patterns. This investigation highlighted the importance socio-economical status and attitudes towards energy conservation on occupants' behaviour in residential buildings. The methods described in this paper can be readily used to develop occupancy and heating profiles for monitored households to be used in building simulation programs. [ABSTRACT FROM AUTHOR]

Highlights • The aim of this research is to investigate the thermal performance of the prototype building to assess overheating in the summer, particularly the long-term heatwave period in the UK. • To understand the impact of energy efficient technologies on occupants' wellbeing and health in order to identify occupants' thermal comfort level in these types of dwellings. • The study adopts a quantitative research design based on indoor monitoring, in-situ measurements and dynamic simulation modelling. • This clearly indicates that due to this prototype house's structural construction material behaviour in a heatwave and its location (southwest facing orientation), it is susceptible to very high overheating risk. • The results found from the monitoring during a long-term heatwave in the summer of 2018 provided strong evidence for overheating and thereby thermal discomfort in many occupied spaces, particularly on the first floor followed by several spaces on the ground floor. Meanwhile, all the occupied spaces appeared to be well above the acceptable thermal comfort benchmark throughout the data collection period. • To calibrate the building performance, as well as the building materials and components adopted in the model, the measured indoor environment data were scrutinised in conjunction with the IES simulation results. Abstract There is growing evidence that terraced houses—thermally lightweight, well insulated, naturally ventilated with three exposed wall surfaces—are at risk of overheating, especially in south-eastern England. The aim of this study is to evaluate the building performance and develop a reliable building simulation, which will be employed in the second phase of the study: developing affordable and feasible passive design strategies to support the energy-efficient building systems of the construction industry. This paper reports on the results from the first phase of the study where a quantitative methodology, including indoor and outdoor environmental monitoring, in-situ measurements and building simulation modelling, was adopted. The performance of a case study was modelled and simulated via employing Integrated Environmental Solutions (IES) software suite. The results from the base-case were analysed according to the adaptive thermal comfort of Chartered Institution of Building Services Engineers (CIBSE) Technical Memorandum 52 guidelines: The Limits of Thermal Comfort—Avoiding Overheating in European Buildings. The spaces studied within the case study house were observed to exceed the acceptable limits of thermal comfort; particularly, the large bedroom within this zone exceeded the upper limit for overheating up to 11 h daily. Furthermore, the results from the monitoring study indicate a high risk of summertime overheating across all the case study settings, especially during short-term peaks in outdoor temperatures. The main reasons for the problematic thermal performance were identified as well-insulated and fully air-tight building fabric, the lack of sufficient ventilation through the living spaces and excessive heat gains through the composite cladding material. [ABSTRACT FROM AUTHOR]

Highlights • A methodology is introduced to rank a set of buildings based on energetic performance of occupants. • Ranking is done in two levels, each one gives specific information about occupants of a single building. • The underlying factors that create the ranks are examined to give occupants clues on how to improve their rank and reduce energy consumption. Abstract Identifying the impacts of occupants on building energy consumption has become an important issue in recent years. This is due to the interrelationship of influencing factors such as urban climate, building characteristics, occupant behavior, and building services and operation, which makes it challenging to identify the role of occupants in energy consumption. The research problem in this study lies in the fact that the occupants of a building may not be cautious regarding energy savings, and there exists no ground to assess their energy consumption behavior. One solution is the development of a systematic comparison procedure between similar buildings. This paper introduces a new procedure for comparison between occupants of several buildings to show the rank of each building among others and suggest occupants on reducing their energy consumption and improving their rank. The proposed framework is developed based on multiple data-mining methods, including clustering, association rules mining, and neural networks. The proposed methodology is composed of two levels. The first considers the amount of energy usage by occupants after filtering effects unrelated to the occupant behavior. The second ranks the buildings in terms of achieved and potential savings during the time under investigation. To demonstrate the application, the methodology was applied on a set of monitored residential buildings in Japan. Results suggest that the proposed method enhances the evaluation of buildings' energy-saving potential by revealing the occupants' contribution. It also provides diverse and prioritized strategies to help occupants manage their energy consumption by revealing the building energy end-use patterns. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

Highlights • This study presents a detailed review on IRT for the investigation of building envelope defects. • The literature survey is conducted regarding existing IRT methodologies for building envelopes. • The previous studies with measurement methods, analysis schemes and analysis types are categorized in the literature matrix. • Recent advances and future trends on IRT methods are presented. Abstract Thermal radiation generated by limited resources is emitted from the surfaces and interpreted as temperature. On the other hand, the limited resources necessitate prevention of energy leakages causing noticeable temperature differences on surfaces. Providing sensitive information on temperature contrast, infrared thermography (IRT) is a prominent tool for detecting infrared energy on the surfaces of the objects. IRT is also very promising method for detecting thermal irregularities, air leakages and even moisture abnormalities on building envelopes. Since the concept of nearly zero energy buildings is to be the main target of energy policies in European Union published by European Commission, improving thermal performance of buildings becomes crucial in the last decade. Therefore, implementation of IRT for visualizing and analyzing concealed defects on building envelopes is very promising for improving the energy efficiency of buildings. Given recent regulations and benefits of emerging thermogram technologies mentioned above, a detailed review of the previous studies investigating the abnormalities of building envelopes by IRT is presented in this paper. Furthermore, the applications with measurement methods, analysis schemes and analysis types are classified to highlight the potential of IRT in inspection of building envelopes for providing energy efficient solutions. Finally, recent advances and practical future opportunities are presented for additional contribution of the IRT methods previously employed. [ABSTRACT FROM AUTHOR]

Abstract The actual thermal behaviour of façades is important to identify suitable energy-saving measures and increase the energy performance of existing buildings. However, the accuracy of in situ measurements of façades’ U-values varies widely, mostly due to inadequate test durations. The aim of this paper was to evaluate the minimum duration of in situ experimental campaigns to measure the thermal transmittance of existing buildings’ façades using the heat flow meter method, and to analyse the thermal performance of the façade during the test. Minimum test duration was determined according to data quality criteria, variability of results criteria, and standardized criteria for different ranges of theoretical thermal transmittance and for the same range of average temperature difference. Then, the minimum test duration results were compared. The findings show that ISO criteria are more sensitive and provide more accurate results, requiring a longer test duration. However, when certification is not required, the duration of the test could be reduced by applying data quality and variability of results criteria. The minimum duration of experimental campaigns depends on the theoretical thermal transmittance and the stability of climatic conditions. Moreover, results are more accurate when the dynamic method is used. [ABSTRACT FROM AUTHOR]

Buildings consume a significant amount of energy worldwide in maintaining comfort for occupants. Building energy management systems (BEMS) are employed to ensure that the energy consumed is used efficiently. However these systems often do not adequately perform in minimising energy use. This is due to a number of reasons, including poor configuration or a lack of information such as being able to anticipate changes in weather conditions. We are now at the stage that building behaviour can be simulated, whereby computer programs can be used to predict building conditions, and therefore enable buildings to use energy more efficiently, when integrated with BEMS (i.e. simulation assisted control [1]). In this paper we demonstrate a low cost BEMS that uses building simulation to predict optimised electrical heating startup control points. Those that use electricity for heating in Scotland, where this study was based, tend to be fuel-poor, hence there is a strong case for optimisation, particularly when electricity costs nearly three times as much as the equivalent unit of gas for heating applications. The proposed system demonstrated a 50% energy saving in the reduced heating time compared to scheduling when retrospectively evaluated. [ABSTRACT FROM AUTHOR]

A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance at a range of levels, without burdensome manual intervention such as is the case with traditional solutions. A test implementation on a large university building highlights the potential of this solution. [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]

This study investigates an energy-inefficient council housing tower block in London, due for retrofit, by exploring the correlations between occupancy and energy consumption patterns, thermal comfort and building energy performance in the winter. The aim of this study is to evaluate the building performance and develop a reliable building simulation model to be employed in the second phase of the study for developing an energy-efficient and cost-effective retrofit strategy to support the council's plans. The research seeks to demonstrate the significance of using dominant occupancy and energy use profiles as opposed to relying on standardised profiles when calculating building energy consumption using building simulation software. The paper reports on the results from the first phase of the study where a quantitative methodology; including a questionnaire, structured interviews, indoor monitoring, and building simulation modelling was adopted. The results provide evidence that occupants’ socio-demographic characteristics have a considerable impact on household energy consumption and fuel bills. The results also show that indoor environmental issues experienced in many flats are partly attributed to the thermally inefficient building envelope and partly due to occupants’ patterns of operating their homes with evidence of excessive heating energy use in attempts to alleviate the indoor issues experienced. [ABSTRACT FROM AUTHOR]

Occupants account for a significant impact on building performance through their interactions with zone level building components. Empirically-derived occupant models, despite their potential to represent occupants’ impact in building performance simulation (BPS), have minimal penetration in design and code compliance processes. Instead, occupants are represented with static schedules or simple deterministic triggers. The objective of this paper is to better understand the influence of assumptions made in representing occupant interactions with building components over a BPS model's energy use and comfort predictions, as well as their ability to promote better design decisions. To this end, the energy and daylight performance of a generic perimeter office space in Ottawa, Canada were evaluated using a set of comprehensive performance metrics. Results indicate that representing dynamic occupant–building interactions lead to different energy predictions from the static schedules. The maximum difference in the total electricity use was for window-to-wall area ratios (WWR) of 20%, which was about 30% higher with the stochastic cases than the blind-open static cases. WWR 60% and 40% generally yielded the lowest lighting electricity use with the static and stochastic cases, respectively. This paper emphasizes the importance of incorporating empirically-derived dynamic occupant models for simulation-aided design and code compliance. [ABSTRACT FROM AUTHOR]

In a hybrid cooling system, an indirect evaporative cooling (IEC) unit is installed before an air handling unit to pre-cool the incoming fresh air, in order to reduce the energy consumption of the air-conditioning system. When the system is applied in humid regions, as the dew point temperature of the fresh air is higher, condensation will probably occur in the dry channels of IEC unit. However, the model of IEC unit considering condensation had been seldom studied, which would become an obstacle in predicting the performance of the hybrid system. In order to evaluate its energy saving potential precisely, the paper aims to establish a short-cut model for predicting the annual performance of the hybrid cooling system considering condensation in IEC unit. This paper firstly presents the analytical models for IEC under non-condensation, totally condensation and partially condensation states and proposed a method for judging the three states as well. The models were validated by the published data from literatures. The validated model was then incorporated with TRNSYS for predicting the performance of an IEC hybrid cooling system in a wet market in Hong Kong and the annual simulation results were validated by a field measurement with good agreement. [ABSTRACT FROM AUTHOR]

The increase in global environmental concerns as well as the advancement of computational tools and methods have had significant impacts on the way in which buildings are being designed. Building professionals are increasingly expected to improve energy performance of their design. To achieve a high level of energy performance, multidisciplinary simulation-based optimization can be utilized to help designers in exploring more design alternatives and making informed decisions. Because of the high complexity in setting up a building model for multi-objective design optimization, there is a great demand of utilizing and integrating the advanced modeling and simulation technologies, including BIM, parametric modeling, cloud-based simulation, and optimization algorithms, as well as a new user interface that facilitates the setup of building parameters (decision variables) and performance fitness functions (design objectives) for automatically generating, evaluating, and optimizing multiple design options. This paper presents an integrated framework for building information modeling (BIM)-based performance optimization, BPOpt. This framework enables designers to explore design alternatives using an open-source, visual programming user interface on the top of a widely used BIM platform, to generate models of building design options, assess the environmental performance of the models through cloud-based simulation, and search for the most appropriate design alternatives. This paper details the process of the development of BPOpt and also provides a case study to show its application. The case study demonstrates the use of BPOpt in minimizing the energy consumption while maximizing the appropriate daylighting level for a residential building. Finally, strengths, limitations, current adoption by academia and industry, and future improvements of BPOpt for high-performance building design are discussed. [ABSTRACT FROM AUTHOR]

As the scope of building design and construction increases and building systems become more integrated, the use of building energy models has become increasingly widespread in evaluating and predicting building performance. Despite the growing sophistication of building modeling tools, errors can arise from approximations that are made by a practitioner during model creation. This paper examines the process of model zoning, i.e., how the volume of a building is divided into regions where properties are assumed to be uniform. Zoning is performed during model creation to decrease model complexity. However, accuracy reduces when dissimilar regions of a building are defined by a single zone. In this paper, a systematic approach to creating zoning approximations is introduced. Utilizing the Koopman operator, the time-series output produced by a building simulation can be decomposed into spatial modes which capture the thermal behavior of a building at different time-scales. Identification of spatial structures within these modes forms a framework for the creation of simplified models of varying levels of granularity. In this paper, a detailed model is analyzed, and model accuracy is studied as coarser building representations are created using the introduced method. [ABSTRACT FROM AUTHOR]

An investigation of building performance through a comfort and operational quality standpoint is not too often discussed for Net-Zero Energy Buildings (NZEB). It would seem important that predications and claims for reducing energy-use in buildings and the move towards NZEB does not compromise comfort in buildings. A high school in Essendon, Victoria (near Melbourne) Australia undertook a retrofitting process to improve its existing library from a functional as well as an environmental standpoint. In the process, several pre- and post-measurements were made of building performance. An advanced packaged unit mechanical system applies a demand control ventilation system with a specialised control that promises uniform air temperature throughout the volume of the conditioned space. This system utilises staged compressors with variable speed drive fans and results in minimal background noise. For the mechanical system to deliver as promised, the building envelope was air pressure sealed to an international standard and double glazed (from single glass) and zoned according to orientation and spatial function. Efficient LED lighting was also applied to a dimming control responsive to occupancy and daylight. This level of building improvement requires before and after measurement procedures to assure and prove a quality performance for a near NZEB. Various measurements of pressurisation, air exchange rates through tracer gas, air temperature stratification, IAQ, as well as a continuous and localised comfort survey measurement all contribute to a pre and post assessment of building performance. This paper discusses several measurement processes considered useful to characterize the performance of an HVAC system in a retrofitted library space. As a result of the building envelope quality, subsequent monitoring of the mechanical conditioning system showed that it could have been reduced to half its specified size. Furthermore, sub-metering of the space indicates that the attention given to the lighting and conditioning systems has reduced their impact, so that plug loads are beginning to dominate and require attention if net zero energy building is to be targeted. [ABSTRACT FROM AUTHOR]

More than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle. [ABSTRACT FROM AUTHOR]

Buildings accounted for half of global electricity consumption in recent years. Accurate occupancy information could improve the energy efficiency and reduce the energy consumption in built environment. Although prior studies have explored various sensing techniques for occupancy sensing, these solutions still suffer from serious drawbacks, e.g. their estimated occupancy information is coarse, extra infrastructure is required, and the privacy of occupants is exposed. In this paper, we present the design and implementation of a novel and practical occupancy sensing system, WinOSS, which is able to provide fine-grained occupancy information thoroughly by leveraging existing commodity WiFi infrastructure along with the WiFi-enabled mobile devices carried by occupants. We have implemented WinOSS in a 1500 m 2 built environment for four weeks to validate its performance. Extensive experimental results demonstrate that WinOSS outperforms existing occupancy sensing techniques, and provides comprehensive fine-grained occupancy information (including occupancy detection, counting and tracking) in an accurate, reliable, cost-effective and non-intrusive manner. [ABSTRACT FROM AUTHOR]

Energy demand reduction from buildings is widely recognised as a key component of greenhouse gas abatement strategies. As governments shift towards large-scale sectoral interventions, a far more robust research and evidence base is needed to support the development, implementation, and on-going evaluation of energy demand policy. The shift to a low carbon built environment will require both a step change in the energy performance of buildings alongside more efficient provision of energy services, and an aggressive decarbonisation of the energy used. Yet the prerequisite data of building stocks needed to support this essential shift in energy performance of buildings are not necessarily available or are inaccessible or incomplete. As more information on building energy use is collected through high frequency sensors and building form analytics become more sophisticated, the analysis methods applied to the myriad and diverse sub-sectors of the building stock ‘population’ need to be commensurate with the heterogeneity of the building stock. This paper describes and illustrates the basis of the IEA EBC Annex 70: Building Energy Epidemiology, which draws on the health sciences to posit ‘energy epidemiology’ as a whole-system approach for empirical research that provides a methodological framework for building physicists, engineers, social scientists, and economists to engage in cross-disciplinary studies. It makes the case that the development and application of an epidemiological approach to investigating energy demand can advance understanding of the inter-related factors for policy guidance and evaluation and provide insights on the mechanisms that influence energy demand. The aim of the IEA EBC Annex 70 is to work in an international collaboration to identify user needs around energy demand in buildings and to establish best practice methods and harmonized formats for data collection, analysis and modelling. To illustrate this process, we present an example from the UK on the application of energy epidemiological methods to building energy performance in the residential sector. The case study investigates the potential effectiveness of the policy and technical measures proposed by the UK Government. Policy implementation for broad, deep, and urgent reductions in energy demand from the building sector requires a far better understanding of the underlying relationships between people, energy use, buildings and the environment. [ABSTRACT FROM AUTHOR]

According to the Directive (2010/31/EU), the main goal in the energy performance of buildings, especially for achieving longer-term objectives in the energy saving, is achieving Nearly Zero-Energy Buildings (NZEBs). Thus, this plan can be achieved by refurbishing of existing or by constructing new buildings to satisfy NZEB requirements. Nowadays, refurbishment of existing buildings to satisfy NZEB requirements becomes one of the major aim in construction. In solving this refurbishment problem, Multi-Attribute Decision Making (MADM) methods help here to evaluate existing state of buildings and to compare them with optimal alternative, which equals to NZEB. This comparison allows selecting optimal refurbishment methods to achieve NZEB requirements. However, existing MADM methods do not applied to compare existing alternatives (i.e. buildings) with the optimal alternative (i.e. NZEB), which is based on standards and laws. Usually existing researches present comparison of selected alternatives among each other or with the best alternative from compared, like in the TOPSIS or ARAS methods. Therefore, in this paper, we analyse the concept of a Passive house and NZEB and its applicability in Lithuanian standards and, respectively, define the optimal alternative (i.e. an optimal building). Second, we analyse possibility of extending existing MADM methods to be MADM optimal (MADM-opt). Moreover, we present several modifications how to transform WASPAS, ARAS and TOPSIS by adding optimal alternative. The modified methods were applied for evaluation of 13 apartments. The results show that MADM-opt is useful for the assessment of alternatives and their evaluation according to the optimal alternative. Moreover, it allows determining difference between the assessed alternatives and the optimal alternative. [ABSTRACT FROM AUTHOR]

Integration of CCHP systems into large buildings provides considerable advantages, as far as the economy, energy consumption and environment related issues are concerned. In this paper, the integration of a hybrid CCHP system into a commercial building is studied. The hybrid CCHP system consists of a renewable and a non-renewable CHP component, photovoltaic/thermal (PV/T) panels and internal combustion engine (ICE). Three objective functions are considered based on cost saving, energy saving and emission reduction goals where are determined as annual operating cost ratio (AOCR), primary energy saving ratio (PESR) and carbon emission reduction ratio (CERR). Considering each objective function, the GA optimization is applied in three different approaches as a single objective optimization problem to find the best size of the system components. Then, using Analytic Hierarchy Process (AHP), which is one of the most used Multi-Criteria Decision Making (MCDM) procedures, the most profitable answer is determined from the three answers achieved in the optimization process. The results showed a good performance of the system. In PESR optimization, which is selected as the best system size, values of 32.96%, 17.25% and 14.79% was achieved for AOCR, PESR and CERR, respectively. [ABSTRACT FROM AUTHOR]

The hollow block ventilated wall is a new kind of ventilated wall, the exhaust air of HVAC system is used as the supply air to flow through the cavity of this wall in this paper. The heat or cool storage in the wall is reduced by using the heat recovery technology; the temperature of internal surface is lowered in summer and increased in winter, and the human thermal comfort is enhanced. A semi-dynamic heat transfer model of the ventilated wall is presented for thermal performance prediction. The dynamic optimized resistance-capacitance (ORC) model and the number of transfer units (NTU) model are joined together to develop the semi-dynamic heat transfer model of this ventilated wall. The experimental study is carried out for validating the semi-dynamic heat transfer model. The maximum relative error is 4.3% for mean internal and external surface temperatures, and it is 2.6% for the outlet air temperature of the cavity. The heat transfer model established for hollow block ventilated wall is fairly reasonable and possesses high accuracy. This model can be used to predict the surface temperature of the hollow block ventilated wall and the heat flux removed by the airflow in the cavity for performance evaluation. [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]

This paper reports on the building performance monitoring and annual energy demand of two homes built side-by-side over an occupancy period of three years. The study compares the results from on-site monitoring against the assumed parameters and calculations from compliance modelling at design stage. It focuses on the differences and impact of occupancy behaviour, weather conditions, quality of construction and operation which contribute to an increase in energy consumption creating a gap in performance between design and actual. The results from the study show disparities in the fabric performance reflecting on the overall consumption of energy. This longitudinal analysis highlights how building performance needs to be evaluated over longer periods in order to fully understand how homes and their occupants operate and consume energy. The impact of the real performance of homes in Scotland over longer periods needs to become standardised, and a mechanism for feedback into regulatory mechanisms and construction practices applied, if carbon emission targets are to be met. [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]

[Display omitted] • The proposed method can be applied to all window types and does not require the manual adjustment of threshold values according to different weather conditions. • The prediction accuracy of the proposed method in the case study reaches 97.79%. • The features of window opening behavior for a teaching building in severe cold regions are explored. • Occupants of teaching buildings in severe cold regions in the transition season prefer a large opening angle (45°∼180°). The building industry plays an important role in the effort to achieve carbon neutrality, and window opening behavior is a major contributor to building energy consumption. In severe cold regions, opening windows during the heating period causes energy waste. If the window opening behavior can be monitored in real time, then the occupants' energy use behavior can be guided to reduce energy waste. This paper proposes a window opening behavior monitoring method using a deep learning-based image recognition model that can identify the window state based on real-time video and was validated in a case study based on outdoor thermal and wind data. A teaching building with casement windows was used as a case study. The results showed that the occupants preferred a large window opening angle (45°∼180°), which is a choice that significantly affects the building energy consumption. The prediction accuracy of the proposed method can reach 97.79%, which also serves to avoid the difficulty of manually calibrating the pixel threshold and realize real-time feedback. This method has a wide range of application scenarios that enable us to obtain window opening behavior to improve the building performance simulation accuracy and guide occupants' energy consumption behavior. [ABSTRACT FROM AUTHOR]

This paper introduces a Human and Building Interaction Toolkit (HABIT) for simulating the thermally adaptive behaviors and comfort of office occupants alongside building energy consumption. The toolkit uses the Building Controls Virtual Test Bed (BCVTB) to co-simulate a field-tested, agent-based behavior model with an EnergyPlus medium office model. The usefulness of the toolkit is demonstrated through a series of zone and building-level case study simulations that examine the wisdom of pairing local heating and cooling options with strategic thermostat set point offsets, judging from the energy, Indoor Environmental Quality (IEQ), and cost perspectives. Results generally suggest that trading efficient local heating/cooling options for whole space conditioning has both energy and comfort benefits, saving up to 28% of monthly HVAC energy while improving the acceptability of thermal conditions in a Philadelphia climate. Nevertheless, cost analysis shows that the fuel source of conserved energy must be considered – particularly in the case of personal heater use, which adds to electric plug loads and associated utility and CO 2 emissions cost penalties. Moreover, costs from even small changes in simulated occupant productivity tend to overwhelm energy costs, suggesting the need to improve the accuracy and precision of available productivity models across multiple seasons and climates. [ABSTRACT FROM AUTHOR]

The use of cool materials for heat island mitigation has gained a lot of interest during the past few years. Cool materials are characterized by high solar reflectance and infrared emittance values. To maximize cooling energy savings, high albedo roof coatings should maintain the above properties for the service life of the coating. The aim of the present paper is to analyze the weatherisation of the cool roofs in two buildings in Athens Greece. The optical properties of the aged and new cool roofs are measured and compared. The impact of ageing in the two buildings’ energy performance is estimated. A mineralogical analysis is performed in order to quantify the deposition of pollutants on the cool roofs’ surface. In addition, a series of microbiological tests are implemented to reveal the impact of ageing and weatherisation in health. In both school roofs the surface temperature has a significant decrease between the part of the existing cool coating and the application of the new part with a temperature difference reached reaching 7–12 K. [ABSTRACT FROM AUTHOR]

Since some years, dense cities and compact buildings are promoted as sustainable and energy efficient designs. Nevertheless, urban planning strategies should take into account the interactions between buildings and the microclimate because the Urban Heat Island (UHI) phenomenon can increase the cooling load of buildings and is strongly influenced by urban morphology, urban landscaping and the thermal properties of buildings and soil. The modification of these parameters, such as building density, can mitigate UHI, with direct and indirect improvement of building energy performances. The case study presented in this paper concerns a new district in La Rochelle (France) named Atlantech. Currently at the design stage, the goal is to transform this old military camp into a zero carbon district. This study was performed in parallel with urban planning using EnviBatE and SOLENE-Microclimate simulation. Two building densities are compared through the impacts on solar irradiance, wind airflows, building indoor temperatures and energy demand. Analysis of reference and densified district highlights various impacts such as the wind velocity decrease, up to 80%, and the effect on an existing nearby building solar irradiation, reduced by 7%. These results underline the potential usefulness of these simulation tools for urban planners at the design stage. [ABSTRACT FROM AUTHOR]

As a popular data driven method, artificial neural networks (ANNs) have been widely applied in building energy prediction field for decades. To improve the short term prediction accuracy, this paper presents a kind of optimized ANN model for hourly prediction of building electricity consumption. An improved Particle Swarm Optimization algorithm (iPSO) is applied to adjust ANN structure's weights and threshold values. The principal component analysis (PCA) is used to select the significant modeling inputs and simplify the model structure. The investigation utilizes two different historical data sets in hourly interval, which are collected from the Energy Prediction Shootout contest I and a campus building located in East China. For performance comparison, another two prediction models, ANN model and hybrid Genetic Algorithm-ANN (GA-ANN) model are also constructed in this study. The comparison results reveal that both iPSO-ANN and GA-ANN models have better accuracy than that of ANN ones. From the perspective of time consuming, the iPSO-ANN model has shorter modeling time than GA-ANN method. The proposed prediction model can be thought as an alternative technique for online prediction tasks of building electricity consumption. [ABSTRACT FROM AUTHOR]

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs. [ABSTRACT FROM AUTHOR]

• Energy performance certificate (EPC) to c contribute in defining a energy poverty index. • Mapping building energy poverty risks to support policy actions for tackling energy poverty. • Merging GIS tool and EPC database to obtain city energy poverty maps at city (Bologna) level. Energy poverty is defined as the condition in which low-income people is no more able to face the costs of energy bills and consequently accept to live in cold and uncomfortable houses. In recent years the scientific literature about this specific issue has registered a significant growth, despite the problem is mainly approached from an econometric point of view to which instead medical, social and energy aspects have to be coupled. Recent EU policies like the Clean Energy Package and the Energy Building Performance Directive Recast III encourage to increase the efforts to tackle and eradicate the energy poverty. The paper approaches the problem focusing on one of its complementary causes: the building energy performance. The adopted methodology includes the calculation of the energy costs for each household, the definition of the energy poverty threshold, the calculation of the related building energy performance limit, otherwise leading to the energy poverty condition. These data, associated with the energy performance certificates, are used to create a GIS based mapping of the buildings potentially affected by energy poverty. Maps can be used to support decision making process in addressing appropriate strategies at urban level to tackle the energy poverty risk. The paper includes a case study in the city of Bologna where the proposed methodology is tested. [ABSTRACT FROM AUTHOR]

This paper discusses the performance of CO 2 adsorption device and its utilization to save energy in buildings. This new device adsorbs CO 2 and a small amount of moisture in the CO 2 capture process, and it evaporates pure CO 2 by thermal energy in the desorption process. This study shows the possibility of implementing a CO 2 capture device in the operation of an air ventilation system for high performance air cooling and heating of buildings. This innovative strategy provides a means to recirculate indoor air to save energy for a certain period of time and the potential for an energy-efficient operation of buildings. This study presents the analysis of CO 2 adsorption performance measurements and evaluates the application of the device by numerical calculations. The results of simulations for the tropical summer and Central European winter season show that 30–60% of air ventilation energy for cooling and heating can be saved competed to conventional systems. Based on these results, this study describes the possibility of using this system to recirculate indoor air using the CO 2 capture device to save energy and minimize air cooling and heating loads. This novel strategy introduces a new paradigm of air ventilation and can replace conventional air ventilation systems for certain period of time. [ABSTRACT FROM AUTHOR]

Building energy assessment methods, used in a regulatory context, impose a calculation procedure under restricted and predefined conditions to check preset energy performance levels. Standardized boundary conditions and input data are implemented allowing for objective evaluation of various building designs. Focusing on school buildings in particular, these specific boundary conditions are however often inaccurate or even unavailable. Therefore, throughout this paper, typical school characteristics and their uncertainty are studied. The impact on the energy demand calculations is then demonstrated in an uncertainty analysis using the Monte Carlo analysis method combined with the Latin Hypercube sampling technique. A sensitivity analysis, using the elementary effect method of Morris, reveals the set point temperature, load and users’ profiles of lighting and equipment in class rooms as the most dominant input parameters on which additional surveys and questioning are focused to determine possible inaccuracies and to define, where necessary, new, more realistic boundary conditions. As a final result, a list of representative boundary conditions for Flemish schools is determined which can be used directly or can be converted into averaged input data for simplified calculation methods. [ABSTRACT FROM AUTHOR]

The need for energy efficient building design has stimulated the integrating buildings with energy systems. In this paper, a novel solar thermal curtain wall (STCW), which is the solar collector installed as a building envelope or integrated to normal facades, is developed. A stand-alone house with the STCW was constructed and thermal performance of the STCW was tested and theoretically analyzed. The results showed that the STCW combined energy production for hot water supply with other functional features of architectural, structural and aesthetic as a new kind of building component. In typical summer day and winter day, the efficiency of the STCW system were 56.8% and 41.0%, respectively. The heat transfer coefficient of the STCW varied monthly, with the maximum value recorded being 1.99 W m −2 K −1 in August and the minimum value recorded being 0.86 W m −2 K −1 in January. A sensitivity analysis was made to investigate variations on the heat transmission load of the solar curtain wall. The results show that the transmission heating load can be reduced by about 39% when the insulation is increased from 25 mm to 50 mm. A comparison between the solar collector integrated with traditional wall and solar curtain wall only was made. Integrated solar collector to wall provides more damping of load fluctuation and smaller peak load, compared with traditional walls, the heating load of façade-integrated walls are less and the walls even contribute heating for the building. Though the cooling load was increased, the comprehensive performance for the façade-integrate walls are superior to the traditional walls. [ABSTRACT FROM AUTHOR]

Embodied energy on building materials is a concept that allows the measurement of environmental impact, considering energy expenditure associated to the extraction, transport, processing, on-site assembly and performance of materials, during their expected life cycle. Longer service life periods of given materials and derived assemblies correspond to more sustainable practices, as they reduce the impact of energy and resource consumption and the corresponding level of emissions. In this paper, an assessment is made of the cost/benefit ratio associated to two different strategies for intervention on a 40 year old detached single house in Portugal: total demolition vs. refurbishment. Since the building cost of both strategies of intervention was estimated to be similar, environmental impact was considered as a decision criteria. Therefore, an analysis was made of the initial embodied energy, new materials and materials sent to landfill, for two different scenarios: (a) integral substitution of the existing structure by a new house, and (b) partial demolition and refurbishment of existing house. The original house was characterized to provide a benchmark for the comparison of both intervention strategies. In the end, data related to energy and mass were used to sustain a decision regarding the recommended type of intervention. [ABSTRACT FROM AUTHOR]

High performance simulation of low energy building requires ever more accurate descriptions of the systems under study to improve the building's performance. This paper describes a numerical model to simulate a single room, using a three-dimensional description of heat conduction in the envelope with environmental conditions that vary over short time-steps are described. The simulation considers the projection of solar radiation through a window onto interior walls. The indoor air temperature is assumed to be uniform. The temperature of the inner and outer surface of the walls are calculated at each time step using a variable-step solver. Validation of the model was carried out using experimental data from a low energy cell operating in a natural climate. A set of well-calibrated temperature sensors and an infrared camera have been used to accurately measure the cell's thermal behavior. Comparison between experimental data and numerical results for free varying conditions shows good agreement and the reliability of the model is proven. These validated results were found for a highly insulated cell. Future studies for different thermal mass cells, with new materials, will be realized to show the contribution of this model. Thermal comfort will also be studied. [ABSTRACT FROM AUTHOR]

The paper proposes a hybrid numerical-neural-network model developed based on the simulation of unheated and uncooled indoor temperature and humidity for buildings. This model is initiated with a numerical simulation and the output is then passed to a neural network for calibration. This approach utilizes both numerical and neural network models and it can analyze the influences of specific parameters on building performances without sacrificing accuracy and generalizability. An experimental study was conducted using a simulation of unheated and uncooled indoor temperature in a sports hall with a non-operating hour ventilation rate that is about half that of the operating hour rate. Several cases were examined. The indoor temperatures simulated by the hybrid model were more accurate than predictions by the numerical model alone for all cases. Particularly, results indicate that the hybrid model can generalize about a building parameter having only a constant value in training data, which a conventional neural network model cannot do that. More importantly, the hybrid model is adaptable for other building simulations, which is the main value of this model. [ABSTRACT FROM AUTHOR]

As one form of passive cooling, night ventilation (NV) has been proven effective to improve the building energy performance. In previous studies, however, fixed NV operating strategies were usually pre-defined, ignoring the weather condition variations over the whole operation process, the influence of outdoor humidity on NV's efficiency, and NV's integrated performance with active air conditioning systems. Such strategies may have potentials for further improvements. This paper presents a systematic approach to address the dynamic optimization of integrated operation of NV and active building air conditioning using typical variable–air–volume (VAV) systems as the case. In the optimization scheme, the physical model is developed per differential algebraic equations (DAEs). The simultaneous collocation method is introduced to translate the dynamic optimization into a nonlinear program, which is then implemented in the GAMS platform and handled by IPOPT solver. The study results indicate that the optimized strategies lead to a remarkable energy saving of 23.19–49.31% in different climate conditions compared to the traditional local control scheme without NV, and a saving of 14.97–39.70% compared to that with pre-defined NV. [ABSTRACT FROM AUTHOR]

The increase of complexity in school buildings to ensure for users comfort and social and functional demands are changing energy consumption patterns. In the Portuguese context, a recent rise in energy consumption, after a major national refurbishment programme, confirms the need to improve energy management in schools in order to reduce their environmental impact. Besides building design and systems, users are also a determining factor impacting energy consumption in buildings. However, behavioural issues are still among the areas least covered by scientific literature. The present paper analyses the energy consumption patterns of eight Portuguese case-study schools, with a methodological approach that integrates quantitative and qualitative data analysis. The approach made it possible to link the energy consumption patterns of the schools (selected as Key Performance Indicators) with the user behaviour and management strategies. As a result, six Key Performance Strategies (KPS) were identified so as potentially to enhance the energy performance of school buildings through use and management. Some of the identified KPS can be implemented directly through school management policies to reduce energy use and enhance efficiency. Others can be incorporated in future building design strategies. Some have the potential for being hereafter integrated into the simulation models of buildings’ energy performance. [ABSTRACT FROM AUTHOR]

In this paper is presented methodological approach to the energy efficiency optimization of high density data centre, in a synergy with relevant performance analysis of corresponding case study. Related case study goal—to optimize energy efficiency to the level characterized by the power usage effectiveness nearly equal 1 (PUE ≈ 1), has been successfully realized, tracing an energy efficiency optimization road to a hyper energy efficient data centre of the superb IT and energy performance. In addition to the corresponding energy densities, and energy efficient removal of extremely high heat dissipation, to reach superb IT performance very special focus is to be devoted to finally controlling indoor air temperature and humidity conditions. It has been shown that, by an integrated approach to the optimization of building construction, data centre's intrinsic IT systems and equipment selection is to be done also with the reference to its specific energy efficiency and the most recent breakthroughs in IT infrastructure fields, as well as in data centre's high performance air-conditioning and infrastructure's high precision cooling. Finally, data centre greening, implementing renewable energy sources has been analysed. [ABSTRACT FROM AUTHOR]

Liquid desiccant dehumidification system has received much attention in recent years for its important economic benefits in energy saving of buildings. Furthermore, the specific surface area of desiccant solution can be expanded dramatically by the ultrasonic atomization technology, which generates numerous tiny droplets with diameter about 50 μm. However, the tiny atomized droplets are found to be easily captured by the wall of dehumidifier chamber, resulting in the poor performance of this type of system. In this paper, a new criterion called “droplets suspension rate” together with an optimized design method was proposed to improve the performance of ultrasonic atomization liquid desiccant dehumidification system via optimizing its dehumidifier chamber. Experiments were carried out to verify the improvement, where the dehumidification effectiveness, desiccant consumption rate and the air temperature rise were adopted as indicators to evaluate the performance of the system. The results showed that the performance of ultrasonic atomization liquid desiccant dehumidification system was enhanced significantly and the desiccant consumption was reduced markedly after the improvement. Moreover, the improved system was found to be able to utilize lower-grade desiccant solution. The criterion and the method proposed may build a foundation for the better design of ultrasonic atomization liquid desiccant dehumidification system. [ABSTRACT FROM AUTHOR]

Vacuum insulation panels (VIPs) have thermal resistance values, at the center of the panel, up to 10 times or more than those of conventional thermal insulation materials. In Canada, known for its predominantly extreme cold climate, the potential to apply VIPs in the building construction industry is estimated to be enormous, particularly with the introduction of the new 2011 National Energy Code of Canada for Buildings (NECB 2011). VIPs can play a major role in Canadian buildings to meet energy requirements of the NECB 2011. However, the lack of long-term performance credentials and various constructability issues are among the major barriers for mass application of VIPs in the Canadian construction industry. This paper presents the design strategy, construction details, instrumentation and thermal performance monitoring observations of a VIP retrofitted wall system in Yukon, located in Northern Canada. Experience gained from the construction process and available thermal performance data over a period of three years provide encouraging indicators for the constructability and long-term thermal performance of VIPs in Canadian subarctic weather. [ABSTRACT FROM AUTHOR]

Though many building energy benchmarking programs have been developed during the past decades, they hold certain limitations. The major concern is that they may cause misleading benchmarking due to not fully considering the impacts of the multiple features of buildings on energy performance. The existing methods classify buildings according to only one of many features of buildings—the use type, which may result in a comparison between two buildings that are tremendously different in other features and not properly comparable as a result. This paper aims to tackle this challenge by proposing a new methodology based on the clustering concept. The clustering concept, which reflects on machine learning algorithms, classifies buildings based on a multi-dimensional domain of building features, rather than the single dimension of use type. Buildings with the greatest similarity of features that influence energy performance are classified into the same cluster, and benchmarked according to the centroid reference of the cluster. The proposed methodology contains four steps: feature selection, clustering algorithm adaptation, results validation, and interpretation. The experimentation was carried out with a comparison between the proposed methodology and the Energy Star approach. It was shown that the proposed methodology could account for the total building energy performance and was able to provide a more comprehensive approach to benchmarking. In addition, the multi-dimensional clustering concept enables energy benchmarking among different types of buildings, and inspires a new perspective to investigate building performance typology. [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]

• 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]