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Heating, ventilation, and air-conditioning (HVAC) equipment faults and operational errors result in comfort issues and waste of energy in buildings. An Automatic Fault Detection and Diagnosis (AFDD) tool could help facility managers fix comfort and energy issues more efficiently, by identifying the most probable root causes. Existing AFDD methods mostly focus on equipment-level fault detection and diagnostics; almost no attention is given to building level fault diagnosis, considering inter-dependency between equipment through the energy distribution chain. In this work we propose a methodology to automatically derive a Bayesian network from HVAC system topology description such as Haystack. This Bayesian network models and estimates the state of all elements in the system, helping users to identify the most probable root fault. As it is able to ingest evidence from any source (field data, operators, or other models) and is capable of updating its estimates when new evidence is delivered, such a tool could have a great potential to be used interactively on the field. We applied the proposed methodology on simulated and real-world buildings and present in this paper one specific case. • Transfer building system topology and expert knowledge to a Bayesian network. • Transform equipment-level fault detection into building-wide fault diagnosis. • Experiments on simulated and real-world buildings. [ABSTRACT FROM AUTHOR]

The share of embodied energy within the total life cycle of a building is expected to increase and become more significant as low energy and net-zero energy buildings become the norm. In the last two decades, many researchers have studied the embodied energy of buildings and published their findings. However, a comprehensive, quantitative analysis of the literature on the embodied energy of buildings is missing. In this study, in order to provide a better understanding of the field as a whole, a bibliometric approach is applied to create a knowledge map and discover more information about the topic. The primary knowledge structure and the topics for study were discovered by analyzing the keywords and abstract terms of 398 papers published from 1996 to 2015. The results show that life cycle assessment is the keyword with the greatest frequency of occurrence and design is the keyword that has the highest number of co-occurrence relationships with other keywords in the 398 papers. The major three research areas for the embodied energy of buildings are life cycle assessment (LCA), building design, and greenhouse gas emissions. By using the bibliometric method, this study analyzes previous studies to provide new insights into the embodied energy of buildings. [ABSTRACT FROM AUTHOR]

• This paper quantifies model errors in fan pressurization tests in windy anisothermal conditions. • Maximum error is characterized with fan-induced, weather-induced, and reference pressures. • Both the power-law and the quadratic law can yield significant errors at low pressures. • Possibilities for testing in windy anisothermal conditions are extended compared to ISO 9972. Building pressurization test methods assume that the flow through building envelopes follows a power law or a quadratic law with a specific correction to account for wind and stack effects. This paper investigates the model error stemming from these assumptions using a numerical approach. The model developed calculates the air flow rate through a building envelope assuming it can be viewed as an array of parallel cracks following a quadratic law. On the one hand, the model gives the ideal leakage air flow rate at a given reference pressure across all leaks; on the other hand, it calculates the leakage air flow rate at the same reference pressure that would be obtained with a pressurization test. In calm isothermal conditions, sensitivity analyses show the error in the leakage air flow rate is in the range of –32% to 0% and −15% to 25% at 4 Pa for the quadratic and the power laws, respectively; it is in the range of 0% to 1.5% and −1% to 0.7% at 50 Pa. In windy anisothermal conditions, the range of the relative error strongly depends on the constraints put on the induced pressures. In our analyses, ISO 9972 constraints disqualify a significant number of tests without reducing the maximum error. The results obtained on a very large number of tests enabled us to derive a simple relationship between the maximum error on the leakage air flow rate, the fan-induced pressure, the weather-induced pressure, and the reference pressure. This relationship could be used for estimating uncertainties in pressurization tests for a given building in given weather conditions without invalidating tests a priori based on criteria such as the zero-flow pressure or the wind speed. The discussion details the model limitations. Note in particular that it applies only to steady weather conditions. Further research is necessary to consider unsteady conditions which are common in the field. [ABSTRACT FROM AUTHOR]

Designing a low energy building requires to evaluate a large number of parameters: design combinations, element thermal characteristics, HVAC systems efficiencies, etc. All of them determine the space heating and space cooling energy demands, energy consumptions, and life cycle cost over the lifetime of the building. This paper presents the achievements of SEDICAE research project consisting on a new methodology based on a tabu search and a simplified method to calculate energy consumptions. The methodology is designed to estimate the annual energy demand, life-cycle cost and energy rating. A second process is included to select the HVAC system is developed for the building designed with this methodology. In general, builders should look for low energy, but investment in building design is a limiting factor. This paper show the relationship between energy efficiency index and investment in optimized residential building. Furthermore, the best energy rate is obtained applying the HVAC systems in the integrated optimization method for residential buildings. This methodology reduces investment, reduce the energy demand and selects the best construction materials, allowing to study the cost in different economic scenarios. In this paper, a building design case study is studied in 2028 scenarios in 12 climatic zone in Spain. [ABSTRACT FROM AUTHOR]

This paper deals with the quantification of the uncertainties due to wind in building pressurisation tests. The steady wind model error stems from the heterogeneous pressure distribution around the building. We have analysed this error based on a simplified one-zone building model with one leak on the windward side and one on the leeward side of the building. Our model gives an analytical expression of this error that depends on the leakage distribution and pressure coefficients. Using test and reference pressures at 50 Pa in this model, standard measurement protocol constraints contain the steady wind model error within about 3% and 11% with wind speeds below 6 m s −1 and 10 m s −1 , respectively. At 10 Pa, the error is in the range of 35% and 60% at 6 m s −1 and 10 m s −1 , respectively. This paper also includes an estimate of the combined uncertainty including other sources of errors which can be used to assess the relevance of measurement protocols. Under idealised conditions, using 50 Pa as reference pressure and a default flow exponent, it can be expected a combined expanded uncertainty of 6%–12% for wind speeds of 6–10 m s −1 , respectively. [ABSTRACT FROM AUTHOR]

[Display omitted] • Organic PCM shows a appropriate phase change point considering the ambient temperature. • Shape stabilisation is the most prevailing incorporation because friendly and cheap operation. • Physical properties of PCM composites should get attention as equivalent to thermal properties. • The performance of PCM relies heavily on the ambient condition of construction. Building construction deserves many attentions due to its huge energy consumption, while Phase Change Materials (PCMs) provide positive solutions for improving energy efficiency and enhancing the thermal properties of construction materials. However, PCMs also present some negative impacts, such as weakening mechanical properties and increasing costs, chemical instability and so on. In this paper, the main characteristics of PCMs, design and incorporating methods, effects on energy consumption and construction reliability are comprehensively reviewed and discussed. Although many materials have the capacity of phase change, some organic PCMs are more suitable due to the higher latent heat and favourable phase change point in buildings, when eutectic PCMs present greater potential to become the optimal one but much effort is required for investigations. Current design methods and application in construction materials can meet the essential requirements, but the effectiveness is inadequate, including low efficiency of phase changing, leading to low energy storage. Subsequently, some promising research direction and critical areas for optimization are also proposed accordingly in this paper. Future development of PCMs, including novel PCM and efficient incorporation, real applications and functions in buildings are proposed. Additionally, multifunctional construction materials combining PCM deserve much attention and possess promising prospect for energy saving in sustainable and energy efficient building construction. [ABSTRACT FROM AUTHOR]

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the mathematical procedure for the determination of overall sustainability index of nine options for the agglomeration of economic, environmental and social indicators. Eleven sub-indicators were selected and calculated for all chosen options. In accordance to final energy consumption (for space heating, hot water production, cooking and the household electrical appliances) the selection, defining and determining the economic, social and environmental indicators was developed. It was done for all chosen options selected by qualitative characterization of residential objects in accordance with construction period, type of heating system and type of object (buildings or family houses). Investigation of the influence of non-linear normalization on the sub-indicators’ agglomeration was the aim of this paper. Normalized sub-indicators are obtained by selection of the appropriate linear (θ =1) or non-linear function (θ ≠1). Sustainability index and its standard deviation were calculated for different value of the parameter θ and each option in six different cases. The functional dependence between the sustainability index and the associated standard deviation of the θ parameter (characterizing the way of normalization) was obtained. [Copyright &y& Elsevier]

Abstract: Photovoltaic (PV) connected systems are experiencing rapid market growth. This is due to the continually downward trend in PV cost together with government support programs. A scenario has been assumed to analyse the geographical market of PVs. The results provide clear evidence of the influence that some variables have on the profitability of PV investments. This study presents a model for minimising investment risk and maximising the return of a renewable energy portfolio in Italy. The value of the paper is in showing that the energy and CO2 reduction potential that can be reached through consumer-oriented policy measures, but the paper also looks at the effectiveness and social implications of such measures. Private households possess immense unused potential for energy reductions (and climate protection) that could be realised through gains in energy efficiency, behavioural changes, and extended use of low-emission energy. The focus of energy policy has been on businesses rather than on private households, which are only partly captured by direct policy measures. To achieve the goals of climate policies, the current political and scientific discussion increasingly considers measures that aim to reduce energy consumption in the private sector. Quantitative estimates are presented for economic indicators and will show the various effects of policy measures on the implemented household types. [Copyright &y& Elsevier]

Abstract: This paper proposes a formulation of the global energy management problem of dwellings, which consists in a dynamic predictive control system able to generate optimized controls taking into account the model of the concerned dwellings, i.e. homes or offices. It focuses on the adjustment of the electric energy consumption and production in order to maximize energy usage efficiency, which is seen as a compromise between energy cost and overall comfort. To reach this objective, the concept of service is introduced: basically, a service participates to the comfort and may consume energy. The available flexibilities of the services provided by domestic appliances are used to compute anticipative optimal plans for appliance controls based on a mixed integer linear programming (MILP) algorithm. A reactive mechanism based on a list algorithm is added to face unforeseen events. The paper focuses on the computation of the anticipative plans. Different MILP models of common services are proposed. Application examples are given. [Copyright &y& Elsevier]

Abstract: Heat is transferred through building envelopes by conduction, radiation, and convection. Of these, convective heat transfer is often the weakest ‘link’ in the overall heat transfer model. While conduction and radiation heat transfer are supported by well-established analytical and numerical models, the treatment of convection is much less rigorous. Convection modeling involves solution of fluid dynamics problems in which the complexity of an enclosed space''s geometry and the diversity of indoor airflow patterns require many fit-for-purpose convection correlations. These must take into account specifics of the space and of the heating ventilation and air-conditioning (HVAC) system. This paper provides an overview of the current knowledge on the modeling of convective heat transfer in load calculation and building energy simulation programs. The paper also discusses various issues related to the robustness of convection coefficient correlations, and reports on new experiments conducted to test the sensitivity of existing convection correlations. The discussed issues relate to: (1) the non-uniformity of the indoor temperature field; (2) the selection of a proper characteristic dimension; (3) the effect of adiabatic and non-adiabatic obstructions in the zone; and (4) the impact of airflow disturbance. [Copyright &y& Elsevier]

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

Abstract A critical decision to be made once a building project is defined is the selection of a convenient construction method (CM) for various building elements. To deal with varied decision criteria and the classified nature of building elements, this paper implements the decision-making process in an object-oriented model, in which each building element is modeled as a class with various possible alternative construction methods as subclasses. Although the subclasses inherit all the main class attributes, each subclass is specified by additional attributes. The uncertainty and vagueness of expert knowledge on the performance of each construction method regarding the attributes are mapped with fuzzy numbers in this multi-criteria-decision-making problem to deal with the inherent imprecision of subjective judgment. To demonstrate the use and capability of the model, a case study is presented. [ABSTRACT FROM AUTHOR]

Abstract: Buildings demand energy in their life cycle right from its construction to demolition. Studies on the total energy use during the life cycle are desirable to identify phases of largest energy use and to develop strategies for its reduction. In the present paper, a critical review of the life cycle energy analyses of buildings resulting from 73 cases across 13 countries is presented. The study includes both residential and office buildings. Results show that operating (80–90%) and embodied (10–20%) phases of energy use are significant contributors to building''s life cycle energy demand. Life cycle energy (primary) requirement of conventional residential buildings falls in the range of 150–400kWh/m2 per year and that of office buildings in the range of 250–550kWh/m2 per year. Building''s life cycle energy demand can be reduced by reducing its operating energy significantly through use of passive and active technologies even if it leads to a slight increase in embodied energy. However, an excessive use of passive and active features in a building may be counterproductive. It is observed that low energy buildings perform better than self-sufficient (zero operating energy) buildings in the life cycle context. Since, most of the case studies available in open literature pertain to developed and/or cold countries; hence, energy indicative figures for developing and/or non-cold countries need to be evaluated and compared with the results presented in this paper. [Copyright &y& Elsevier]

Heating and cooling systems based on hydrogen sorption in metallic alloys have attracted researchers due to their advantages such as environmental friendliness, ability to utilize low-grade waste or renewable energy, wide operating temperature ranges, and availability of a plethora of alloys to choose from. These heat-operated systems offer a viable alternative to conventional electrically driven HVAC systems. In this paper, a metal hydride-based heating and cooling system (MHHCS) which can cater to the year-round comfort air-conditioning of locations with extreme climatic conditions is proposed. The paper describes the cyclic operation of the MHHCS for application in buildings through the different seasons of a year. The performance of the system is studied using a matched alloy pair of Zr 0.82 Mm 0.09 Ti 0.09 Fe 1.4 Cr 0.6 – LaNi 4.6 Al 0.4 chosen based on thermodynamics and reaction kinetics. This paper discusses the effects of system parameters and operating conditions on the year-round performance of the MHHCS. [ABSTRACT FROM AUTHOR]

• This paper presents a simplified theoretical model for fan pressurization tests with steady stack effect at work. • It gives the error in the measurement result for an idealized building. • Gives error of a two-leak model, shows it to be a likely bound for any distribution. • It gives recommendations to contain the error due to stack effect in field test conditions. Current building pressurization test methods considerably reduce the scope of validity of the test results when stack effect is significant without clear justification. This work attempts to fill this gap based on physical modelling and numerical simulations. In steady and no-wind conditions, it gives the error in the test result with leaks discretely distributed over the building height assuming the flow exponent is the same for all leaks. It also gives an analytical expression of the error when the building can be modelled with two leaks, one at the bottom and one at the top. The results show that the maximum absolute value of the error in the two-leak case has a very high probability to be the upper limit of the absolute value of the error obtained with any leakage distribution of more than two leaks. Consequently, one can use the two-leak model to obtain the minimum induced pressure to generate to contain the error below a given limit. For example, using an induced pressure greater than twice the stack pressure should be sufficient to contain the error in absolute value below about 5%; the error should be below 14% if the induced pressure is greater than the stack pressure. In turn, this paper gives recommendations for testing together with tables and charts to be used by field technicians. [ABSTRACT FROM AUTHOR]

There are several techniques for the performance of energy studies in buildings, where infrared thermography is widely used for the study of the composition of the envelopes, to find faults in the building materials and in the composition of the envelopes with influence on their thermal behaviour, as well as to detect areas with humidity. Common thermographic building interpretations are performed by a human operator, which involves a high level of subjectivity and mainly relies on the expertise of the operator. With the aim at minimizing this subjectivity and maximizing the accuracy of the inspections, this paper presents a procedure for the automation of thermographic building inspections mainly focused on thermal bridges. The procedure, in addition to detecting the thermal bridges by their geometric characteristics and their temperature differences with the surroundings, includes the computation of the thermophysical property of linear thermal transmittance of each candidate to thermal bridge, thus implying their characterization in addition to their detection. With this addition, together with a previous process of rectification of the thermal images analysed, the accuracy of the detection of thermal bridges regarding existing methodologies is improved in 15% considering the false positives and negatives obtained in each methodology. [ABSTRACT FROM AUTHOR]

Integrated energy management at both the district and building scales can potentially improve multi-level energy efficiency, but such a solution requires the exchange and analysis of energy performance information from different stakeholders. With the complexities of energy management, there are numerous potential stakeholders and a considerable amount of information to consider. Therefore, a primary challenge is the development of a method that identifies the key stakeholders and extracts key information that supports their performance goals. In this paper, a systematic approach to identify stakeholders and key performance indicators (KPIs) is proposed to draw key information for multi-level energy performance analysis. Firstly, a three-task method for the identification and prioritization of stakeholders is suggested; secondly, a bi-index method to select the KPIs that underpin the stakeholders’ performance goals is defined; finally, the proposed methodology is validated using a case study. The result demonstrates the feasibility of the methodology and illustrates that the selected KPIs contribute to the attainment of key information required to carry out a multi-level energy performance analysis. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES) systems with phase change materials (PCMs) as a known energy storage technology have a high potential for increasing the energy efficiency of buildings. In fact, the use of PCMs with various approaches, either active or passive, in the building helps to maintain the temperature in the thermal comfort range for occupants through decreasing the temperature swings, and lower energy consumption by the load reduction/shifting. Due to the significance of this issue, many research works have been carried out on the application of PCMs in buildings. In this study, the experimental works in the fields of PCMs in buildings are taken into account. The papers are classified based on heating, cooling, and air-conditioning. Besides these, the applications of nano-PCMs in buildings are reviewed. According to what has been carried out up to now, the gaps are identified and analyzed for preparing useful suggestions for future works. The recommendations and suggestions are presented at the end of the chapters as well as the conclusion, and the literature is summarized in some tables. [ABSTRACT FROM AUTHOR]

• Self-consumption in residential sector is studied under Spanish regulatory framework. • An average-day model versus a whole-year model is benchmarked. • Scheduling household appliances is analysed in a residential building. • Ex-ante and ex-post renewable energy sharing is investigated. Studies on self-consumption in residential use are constantly evolving, and society claims new solutions in response to changes to new paradigms. This paper aims to optimise the sizing of a self-consumption installation for collective self-consumption in a residential building under the Spanish regulatory framework. The study considers the current price volatility in the retail electricity Spanish market and focuses on the techno-economic analysis of self-consumption in a building consisting of 12 dwellings using photovoltaic energy and the possible support of a storage system. The three aspects analysed are the sizing of the self-consumption facility, the use of smart appliances to shift their consumption to more cost-effective times and the sharing of the renewable energy generated by the facility among the consumers participating in the collective self-consumption. This study employs two models, an average-day model and a whole-year model. The techno-economic analysis yields that between the two self-consumption modalities for residential consumption, the modality with surplus simplified compensation is more profitable than the one without surpluses. Finally, the study focuses on sharing the total renewable energy generated among the participants. The results indicate that both ex-ante and ex-post dynamic sharing brings few benefits. [ABSTRACT FROM AUTHOR]

This paper details a manual calibration of a 132 zones, highly monitored 5 434 m2 office building located in France. The calibration is conducted over one year of simulation at a five minute time-step. The model is mostly fed with input files containing measured data for each simulation time-step. First simulation results show that the model cannot be considered as being calibrated considering usual guidelines based on statistical indicators calculated on monthly energy consumption. Instead of going through a classical tuning process to match measured and simulated monthly energy consumption data, the choice was made to focus on explaining those discrepancies using available building information and monitoring data. A first dynamical heating and cooling powers analysis has been made, resulting in good correlation with measured values and explaining most of the discrepancies previously noticed, followed by a dynamical temperature analysis performed at the zone scale, and completed by a global statistical analysis at the building scale for the 132 zones of the building. Results showed very good agreement between measured and simulated temperature values with 90% of data points ranging between −1.72 °C and 2.02 °C of error. This demonstrate that a model that at first glance does not perform well considering particular statistical indicators can show an accurate dynamical behavior and a good performance when other variables and performance criteria are considered. This is followed by a discussion of the possible model improvements along with the limitations of statistical analysis compared to dynamic physical analysis for calibration performance assessment. The paper concludes with several proposals to improve the guidelines for calibration procedures involving the use of detailed monitoring data. [ABSTRACT FROM AUTHOR]

Traditional life cycle assessment (LCA) methods are used to conduct building environmental impact assessment (EIA) with little consideration of influential factors that vary in time and of variation in occupancy behaviors. Because the life cycle of a building is quite long, such details have significant influence on the accuracy of evaluation results. To fill in this gap and extend the LCA system, this paper developed a dynamic assessment framework based on LCA principles after reviewing the research progress of DLCA (dynamic LCA). The new framework identified four dynamic building properties (i.e., technological progress, variation in occupancy behavior, dynamic characteristic factors, and dynamic weighting factors) and considered them in corresponding assessment steps to realize real-time EIA. In addition, residential occupancy profiles were described at personal level, family level, and social level; and three potential quantification methods were introduced to explore the relationship between occupancy profiles and household energy consumption. The DLCA framework expands the connotation of the LCA system from a dynamic perspective, making it possible to present time-varying EIs of buildings over their long life cycle and guide occupancy behavior in time. This framework has the potential to be base for developing a useful tool for conducting forecast evaluation and promoting sustainability. [ABSTRACT FROM AUTHOR]

This paper aims at investigating the effect of combining thermal insulation with high thermal inertia on building’s thermal performance in a hot semi-arid climate. The impacts of these passive techniques on the cooling/heating loads and the indoor comfort are analyzed by means of dynamic simulation as well as on-site monitoring of a two floor detached house located in the Green City of Benguerir in Marrakech region (Morocco). This house, mostly built using local materials, integrates many other passive and hybrid systems. The present study focuses on the hemp-gypsum, the double slab technique for thermal insulation, the double glazing and the high thermal inertia of the walls. Thermal performance of these techniques are assessed by comparison to a hypothetical reference case of the house lacking the considered techniques and built with regular classic construction materials. The results show that the investigated passive systems have a remarkable effect on the indoor air temperature, the thermal comfort and the cooling/heating loads of the building. When the three systems are integrated into the studied house, better comfort conditions are achieved compared to the reference case as its indoor air temperature minimum is up to 5 °C higher in winter while the indoor air temperature maximum is reduced by up to 9 °C in summer. In addition, the daily air temperature amplitude (peak-to-peak difference) is drastically reduced compared to the reference case. Moreover, the discomfort hours based on an acceptable thermal comfort zone of 16 °C–28 °C are reduced by 62% compared to the reference case. Furthermore, the house performs up to 81% of reduction in the annual cooling and heating load compared to the reference case. [ABSTRACT FROM AUTHOR]

Buildings account for a significant amount of global energy use and CO 2 emissions. Thermally Activated Building Systems (TABS) are a technology with potential for significantly reducing buildings energy use. TABS are heating and cooling systems that are integrated in the building structure. They mainly exchange heat through radiation and are able to store heat in the building thermal mass. TABS high thermal mass and their interaction with the building structure make their energy evaluation and design process difficult. Development of simulation models has been essential to study the design and control of TABS. Control of TABS is challenging due to the slow response time and storage capacity. A lot of research has been conducted to develop control strategies that fully exploit its energy saving potential and that maximize the use of renewable energies. This paper summarizes the main characteristics of TABS and presents the developed simulation models and control strategies. [ABSTRACT FROM AUTHOR]

• Moisture needed to be removed in three building types is calculated. • Salt supported porous composites satisfy most climates and building types. • Zeolites are suitable for return air state, ARI summer and ARI humid climates. • Polyelectrolytes can cope with humid climates and buildings with high wet load. Energy conservation and emission reduction have become a global consensus. As a novel promising energy-saving dehumidification technology, desiccant coated heat exchanger (DCHE)-based air conditioning systems have attracted immense attention recently. This paper provides a quick and reasonable selection of desiccant materials for DCHE systems using water as the cooling medium in different buildings and climates. By the theoretical calculation of moisture needed to be removed in three types of buildings (offices, residential buildings and restaurants) and the analysis of the dehumidification capacity of desiccants in DCHEs reported in the literature, optimal desiccants for different building types and ambient air conditions under given parameters are recommended. Salt-supported porous composite desiccants possess flexible dehumidification performance and can be utilized in most climates and building types, except for extremely humid indoor environments with high requirement for fresh air. Zeolites are especially suitable for return air states, American Air-Conditioning and Refrigeration Institute (ARI) summer and ARI humid climates in buildings with moderate indoor moisture gain, such as offices or residential buildings. Polyelectrolytes can be applied in humid climates and buildings with high indoor wet loads, such as restaurants. This paper offers a promising route to the applications of desiccant materials in novel energy-saving air conditioning technologies. [ABSTRACT FROM AUTHOR]

• The review focus on developing data-driven models for building energy prediction. • Seven feature types and five feature extraction methods are presented. • Data-driven algorithms, including statistical and machine learning methods, are reviewed. • Aspects reflected from expected prediction results are discussed. • Input updating strategies for multi-step energy prediction are summarized. Building energy prediction plays a vital role in developing a model predictive controller for consumers and optimizing energy distribution plan for utilities. Common approaches for energy prediction include physical models, data-driven models and hybrid models. Among them, data-driven approaches have become a popular topic in recent years due to their ability to discover statistical patterns without expertise knowledge. To acquire the latest research trends, this study first summarizes the limitations of earlier reviews: seldom present comprehensive review for the entire data-driven process for building energy prediction and rarely summarize the input updating strategies when applying the trained data-driven model to multi-step energy prediction. To overcome these gaps, this paper provides a comprehensive review on building energy prediction, covering the entire data-driven process that includes feature engineering, potential data-driven models and expected outputs. The distribution of 105 papers, which focus on building energy prediction by data-driven approaches, are reviewed over data source, feature types, model utilization and prediction outputs. Then, in order to implement the trained data-driven models into multi-step prediction, input updating strategies are reviewed to deal with the time series property of energy related data. Finally, the review concludes with some potential future research directions based on discussion of existing research gaps. [ABSTRACT FROM AUTHOR]

[Display omitted] • Trees reduce the thermal radiation absorbed by the west wall. • Short-wave radiation disturbance peak values are 2–3 times that of long-wave. • Planting is recommended at a min distance ≤4 m from the wall canopy. • Planting center distance should be less than 1/2 the width of the wall. Many studies have shown that planting trees near the west wall of a building is conducive to saving energy for cooling in summer. However, there is a lack of research quantifying the thermal radiation disturbance caused by the location of trees near the west wall. This paper studies the influence of long-wave and short-wave thermal radiation disturbance of trees at different locations around the west wall in summer through field experiments and ENVI-met simulations. It was found that the thermal radiation disturbance (T RD) of trees on the west wall of the building is mainly caused by short-waves which produce 2–3 times greater disturbance than that of long-waves. According to the fitting relationship between the change rate of daily thermal radiation disturbance, the view factor and the tree projection area, the functional formula between them is obtained. These findings provide a theoretical foundation for scientifically evaluating the influence of tree location and practical applications for guiding the planning and landscaping of vegetation around building walls. [ABSTRACT FROM AUTHOR]

Phase change materials are a promising strategy to reduce energy consumption in a wide range of applications including the building sector. Many studies have been done to evaluate the impact of PCM on thermal properties of building materials, however there exists little information on the influence of PCM on other properties of the support materials. This knowledge is necessary to determine the feasibility to apply and use building materials containing PCM. In this paper, the effect of the addition of different percentages of microencapsulated phase change material on the properties of two commercial single layer mortars has been studied. Physical and thermal properties as well as fire reaction have been evaluated. [ABSTRACT FROM AUTHOR]

The modeling and simulation of domestic hot water systems, including solar thermal and co-generation technologies, relies on accurate, high time-step resolution water consumption profiles. Due to the expensive nature of field studies, previous profiles have been limited in number of participants, or have been generated synthetically using probabilistic modelling techniques. The Solar City program in Halifax has measured hot water flow rate and temperature data in 119 homes at a time-step of 1 min; and includes a survey of occupancy rates and other relevant meta-data. In this paper, we discuss the data acquisition and processing (with a focus on flow rate data), and conduct analysis to reveal consumption trends and produce a new set of time-step profiles for modeling and simulation. Average hot water consumption per household is 172 L/day with a strong dependency on number of occupants. The hourly profile peaks twice daily, and shifts by several hours on Sunday. The average draw temperature was found to be 51.8 °C, which is lower than the default value of 55 °C applied by many building modeling/simulation packages. The average cold water supply temperature was found to be roughly sinusoidal about 12.4 °C with approximately one-month lag compared to ambient air temperature. [ABSTRACT FROM AUTHOR]

Energy demand for heating and cooling of buildings can be minimized through usage of thermal energy storage (TES) systems in building materials. TES in microencapsulated phase change materials provides a new solution to thermally regulated energy efficient buildings. This study summarizes the investigations and analysis of microencapsulated PCMs for building applications. Microencapsulated phase change materials (MPCMs) can be incorporated with many materials that are commonly used in building construction. This paper provides overview of various encapsulation techniques, test methods for MPCMs as well as applications of MPCMs in buildings. There are several micro-encapsulation methods by which the microcapsules of a wide range of sizes between 0.05 μm and 5000 μm can be produced. The MPCM incorporated with concrete, mortar, plaster and other materials have a significant potential to increase the thermal capacity of the mixture. Several authors reported testing of building materials with MPCM. Though the increase of thermal capacity with addition of MPCM is significant the decrease of mechanical properties, such as compressive strength, is relatively small. [ABSTRACT FROM AUTHOR]

• Develop a new strategy to evaluate GAN accuracy for building power demand prediction. • Identify and evaluate five GANs for predicting large-scale building power demand. • Recommend Original GAN and cGAN for large-scale building power demand prediction. As an unsupervised-learning data-driven model, Generative Adversarial Networks (GANs) have recently attracted a lot of attention for various applications. There is potential to apply GANs for large-scale building power demand prediction, which is needed for power grid operation. However, there are many GAN variations and it is unclear which GAN is suitable for this application. To answer this question, this paper identifies five promising GANs (Original GAN, cGAN, SGAN, InfoGAN, and ACGAN) and evaluates their performance for predicting building power demand at a large scale. Physics-based building energy models are developed to generate training and reference data. A new evaluation indicator that combines accuracy and reproducibility is proposed to evaluate the performance of different GANs in predicting building power demand. The results show that SGAN and InfoGAN are not suitable because they cannot control the number of generated building samples for different building types. The prediction performance among the Original GAN, cGAN, and ACGAN can vary depending on training sample sizes and number of building types. If the training sample size is sufficiently large, Original GAN and cGAN can predict building power demand more accurately than ACGAN with the same number of samples. If training samples are limited, Original GAN provides better accuracy than cGAN and ACGAN. When the number of building types increase, the prediction accuracy increases for cGAN, decreases for ACGAN, and remains the same for Original GAN. As a result, cGAN and Original GAN are recommended for large-scale building power demand prediction. [ABSTRACT FROM AUTHOR]

The accuracy in assigning a climatic zone to a city is essential for studying the correct sizing of domestic hot water, heating, and cooling systems, as well as of construction materials. In Spain, the current system for allocating climate zones is one proposed by the Código Técnico de la Edificación (Technical Building Code) (CTE) and includes a method based on Royal Decree 235/2013, Procedimiento Básico para la Certificación de Eficiencia Energética de Edificios de los Edificios (Basic Procedure for Certification of Energy Efficiency of Buildings), as well as on the recognized document CERMA to calculate energy demands, CO 2 emissions, and energy ratings. The climatic data of cities is not always available, so the CTE method has proposed some solutions, but they are not always precise enough. In this paper, we propose an alternative classification of climatic zones as a result of applying a new method based on approximation and interpolation functions, with a maximum error of 5.773e − 15 in summer and 6.661e − 16 in winter. This new method has been applied and tested in Andalusia in Southern Spain, a region with 772 municipalities. According to the climatic data available, the new proposed method has resulted in more precise climatic zones than the two versions of the CTE (2009 version and the 2013 update). The results are closer to reality, and the method is exportable to any region. [ABSTRACT FROM AUTHOR]

The thermal habits of Odoo were examined and energy consumption data were also predicted. Special tests were performed for the time of the competition, and whole year was also analysed. The climatic data were of Madrid as the competition took place there. The modelling environment was MATLAB's Simulink with a built-in module of Simscape. It is for especially examining thermal behaviours. MATLAB itself is capable of solving differential equations by time, for this reason dynamic simulations can be performed. First the building structure was created, and then the heatflows affecting the internal temperature were added. In this paper detailed process of creating the model is presented, and some results are discussed, including some possibilities of further improvements. [ABSTRACT FROM AUTHOR]

Being increasingly insulated, new buildings are more and more sensitive to variations of solar and internal gains. Due to an important use of electrical heating systems, especially in housing, France is facing a growing problem of peak load on its electricity grid. Controlling the heating system often constitutes an efficient solution to shift heating loads while maintaining indoor comfort. The proposed energy management is a predictive set of optimal commands issued from a dynamic programming optimization knowing in advance the weather, occupancy and internal gains for the next 7 days. This method is tested on a low energy house situated in France with an annual heating demand of 14 kWh/m 2 . In this paper, load shifting according to utility rate incentives and carbon emissions are studied. The importance of building models as well as envelope insulation and thermal mass on energy management results is shown. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for an optimal control of the heating system at the building scale. This control is a new approach of energy planning that aims to decrease the heating consumption/expenses over a defined prediction horizon while respecting the occupants’ thermal comfort. It employs a simplified building thermal model to simulate the building thermal behavior taking into consideration the weather predictions. This approach is based on the application of Monte Carlo method, i.e., a random generator for the heating system scenarios. The aim is to determine the optimal heating plan for the prediction horizon that fulfills the constraints regarding the thermal comfort of occupants and the minimization of the energy consumption/expenses together with achieving a load shedding. [ABSTRACT FROM AUTHOR]

The use of software tools to aid building design, or to show compliance, is now commonplace. This has motivated investigations into the potential of optimisation algorithms, used in such software, to automatically optimise designs, or to generate a variety of near-optimal designs. Optimisation always requires the evaluation of a large number of possibilities, before a final selection is made. Normally when using a building simulator to assess the quality of designs, all possible solutions in the early stages of optimisation (when there is a high volume of choices) are evaluated using the same tool, so that the computational time for the assessment of each of the possibilities is the same as the time required for the final, refined choice of solutions. This paper suggests using a method of evaluation which changes as the algorithm evolves: whereas accuracy is initially compromised to improve the speed of the algorithm, the process is subsequently altered to produce a more accurate, evaluation process. This is a case of dynamic optimisation that requires an algorithm able to cope with changes in the objective landscape. A self-adaptive evolutionary strategy has been chosen, for its ability to “learn” about changes, and the influence of the different decision variables in the objective function as they arise. The results show that this method can reach the same optimal design, with substantially lower computational time than the optimisation methods found in the literature. [ABSTRACT FROM AUTHOR]

Designing a low-energy building requires the evaluation of a large number of parameter combinations. Currently, there are several software programs available that are able to calculate the energy performance and life-cycle cost. However, these programs provide little information regarding what actions will improve the energy performance and how much will they cost. An iterative software program that optimises the parameters would be a solution: however, the larger the database, the slower the data processing and optimisation. The SEDICAE project applies a new methodology based on a tabu search and a simplified method to calculate the demand. A tabu search is a good method to avoid local minima and to permit an evaluation of different solutions. The methodology is designed to estimate the annual energy demand, life-cycle cost and the energy rating. In this paper, 48 different scenarios were analysed with SEDICAE software. [ABSTRACT FROM AUTHOR]

A large part of energy consumption in homes, offices and commercial spaces is related to Heating, Ventilation and Air-conditioning (HVAC) devices. The effective parameter on the consumption of HVAC systems is internal heat gains that arise from occupants, electric equipment and lighting. In order to reduce the energy consumption of these systems, internal heat gains should be predicted accurately. Since there are few investigations performed on the prediction of internal heat gains, in this paper, three predictive models, namely multiple regression model, Levenberg–Marquardt back-propagation (LM-BP) model and similar days method based on combined weights, have been deployed. By assessing the influential factors on internal heat gains, fundamental theories, structures, equations and parameters of these models are thoroughly proposed. To examine the prediction techniques, an office building in China was considered. It was found that all the proposed models have high accuracy; however, the LM-BP neural network showed the most precision among other models with RMSE = 15.59, MAE = 10.16 and MAPE = 6.35. This model had a higher agreement with the actual internal heat gains compared to the predetermined working programs in the ASHRAE standard 90.1. The proposed models used in this study can lead to providing a theoretical base for scholars and engineers to improve the predictive control of HVAC systems, which plays an important role in enhancing thermal comfort, saving energy of residential buildings. [ABSTRACT FROM AUTHOR]

• A novel energy-water ratio is developed for assessment of energy-water nexus. • A thermal model is developed to energy-water nexus. • The thermal model can be used to evaluate the value of energy-water nexus. • Different interdependence between energy-water at the building level are found. • The improved energy efficiency of boiler can save not only energy but also water. Energy and water are two critical resources, and their security has been becoming a regional, national and global priority. The paper investigates the energy-water nexus at the building level through developing a novel energy-water ratio and a thermal model, to provide insight about the interaction mechanism between energy and water at the building level. The developed energy-water ratio has clear physical meaning. The thermal model developed can be used to explore the dynamic interdependences and feedback mechanism between energy and water, and to evaluate the value of interdependence and the real value of infrastructure through linking to business model. The dynamic of energy-water nexus for three kinds of buildings in London is then examined under present and future climate scenarios. Results show that the interdependences of energy-water for these three kinds of buildings vary over time and are different each other. The different interdependences are shaped by the combined effect of both the configurations of infrastructures for building and the environmental condition. The improved energy efficiency of boiler can save not only energy but also water, indicating the positive interaction between energy and water. Results have informative implications for sustainable building and investment in household infrastructures, and suggest an integrated way for co-managing both energy and water effectively. [ABSTRACT FROM AUTHOR]

Abstract: Energy consumption of buildings depends significantly on the criteria used for the indoor environment and building design and operation. The environmental factors that define the indoor environmental quality are: thermal comfort, indoor air quality, acoustic comfort and visual comfort. This paper approaches the numerical prediction of thermal comfort in closed spaces on the basis of PMV–PPD model, and its testing to asymmetric or nonuniform thermal radiation, as well as the indoor air quality simulation and control. The following are developed: a computation and testing model of thermal comfort in buildings, a computational model for indoor air quality numerical simulation, as well as a methodology to determine the outside airflow rate and to verify the indoor air quality in rooms, according to the European Standard CEN 1752. Also, the thermal comfort criteria for design of heating systems, the relationship between thermal environment and human performance, as well as the influence of carbon dioxide on human performance and productivity are presented. The performance of the developed computational models, implemented in two computer programs, is illustrated by using some numerical comparative applications for two building construction types. [Copyright &y& Elsevier]

Abstract: There are many sophisticated building simulators capable of accurately modelling the thermal performance of buildings. Lumped Parameter Models (LPMs) are an alternative which, due to their shorter computational time, can be used where many runs are needed, for example when completing computer-based optimisation. In this paper, a new, more accurate, analytic method is presented for creating the parameters of a second order LPM, consisting of three resistors and two capacitors, that can be used to represent multi-layered constructions. The method to create this LPM is more intuitive than the alternatives in the literature and has been named the Dominant Layer Model. This new method does not require complex numerical operations, but is obtained using a simple analysis of the relative influence of the different layers within a construction on its overall dynamic behaviour. The method has been used to compare the dynamic response of four different typical constructions of varying thickness and materials as well as two more complex constructions as a proof of concept. When compared with a model that truthfully represents all layers in the construction, the new method is largely accurate and outperforms the only other model in the literature obtained with an analytical method. [Copyright &y& Elsevier]

Abstract: Production of autoclaved aerated concrete (AAC) from power industry waste cinders represents a progressive technology for processing of industrial waste in a new form of building material with good qualities. Despite these positive aspects, the share of cinder concrete in the building industry is less popular. The low popularity is partially caused by the poor aesthetic of cinder concrete in comparison with sand-based AAC; however, the main cause is the slightly smaller thermal and moisture qualities of fly ash-based AAC, respecting uncertainty because there are no supporting scientific research and publications about it. This paper is dedicated to a study of the thermal and moisture properties of the cinder concrete and mutual behaviour with the sand-based AAC. It was determined that fly ash-based AAC demonstrated slightly larger moisture sorption in comparison with sand-based concrete under similar conditions. On the contrary, the thermal insulating properties of fly ash-based concrete, as indicated by the heat conductivity, exhibits less moisture influence in comparison with sand-based AAC. Concerning volume changes, fly ash-based AAC showed, in the condition of low moisture, slightly better properties when compared with autoclaved aerated sand concrete. [Copyright &y& Elsevier]

Abstract: Buildings worldwide account for a surprisingly high 40% of global energy consumption and produce an increasingly large carbon footprint. Future sustainability of the building sector is therefore strongly dependent on the installation of energy efficient technologies. However, even though these technologies are becoming more and more efficient, human behavior still plays a very important role in the overall building energy consumption. In this paper, a model for occupant behavior within the building in relation to energy consumption, along with a building energy consumption model is proposed based on stochastic Markov models. The energy consumption model is used to predict possible energy saving gains from building retrofitting projects. The objective is to ensure the return on investment from these projects. The obtained results demonstrate that the proposed energy consumption model learns occupant behavioral patterns from the building. Additionally, it reliably reproduces them, predicts the building energy consumption and identifies potential areas of energy waste. [Copyright &y& Elsevier]

Abstract: This paper deals with exergoeconomic analysis of a dormitory heated by a conventional boiler in a central heating system. The energy and exergy flows are examined from the generation stage to the envelope of the building. The energy and exergy flows between the stages are obtained using a predesign tool for an optimized building design. Exergetic and exergoeconomic analyses of some heating equipment are comprehensively evaluated. A conventional boiler and a water heater in the central heating system are considered in the analysis. Based on the analysis results obtained, the total exergy input rate is calculated to be 1455kW while the largest exergy loss rate is found to be 987.6kW. Exergetic efficiencies of the conventional boiler and the water heater are also obtained to be 15.6% and 20.4%, respectively. [Copyright &y& Elsevier]

Abstract: Jordan heavily relies on imported oil and gas for meeting its energy need as the same time the construction sector consumed more than half of the total electricity consumption in Jordan in 2008. In order to provide the occupants with thermal comfort at least cost, applying energy saving measures into early design stage can be significant to achieve this goal. This paper discusses an assessment of best orientation of the building, windows size, thermal insulation thickness from energetic, economic and environmental point of view for typical residential building located in Mediterranean region. The results show that about 27.59% of annual energy consumption can be saved by choosing best orientation, optimum size of windows and shading device, and optimum insulation thickness. The Life Cycle Cost (LCC) is reduced by 11.94%. The specific energy consumption per square meter is 64kWh/m2 a. [Copyright &y& Elsevier]

Abstract: Infrared thermography is generally used in energy efficiency studies in buildings, as well as in moisture detection studies and building inspections for heat losses. Commonly, thermographic studies are qualitative, based on detection of differences of temperature between points; and they only include thermal measurements on specific points or areas, associated to many other factors such as the thermal properties of the materials and environmental temperature and humidity. But this way of working presents a lot of limitations, as there is no way of executing precise quantitative measurements, because thermographic models are simple in geometry and thermographies include geometrical distortions introduced by the camera they are taken with. Laser scanning technology can be an optimal complement for the thermographic measurement, because it provides the metric information that allows the quantification of the thermal studies if the clouds of points are texturized with thermographies. In this paper a methodology for registering thermographies in clouds of points is explained, with the following steps: procedure for processing the metric calibration of the thermal camera, register of thermographies in the cloud of points based on control points, and finally, processing the textured cloud of points to obtain rectified thermographies, with no optical distortions. [Copyright &y& Elsevier]

Abstract: To mitigate the overheating problem in the warmer seasons, and thereby improve thermal performance and energy efficiency of the double-skin façade (DSF) system, this study introduced an innovative design approach involving the integration of passive thermal mass technique with the air channel of the conventional DSF. To assess the contribution of this integration to energy efficiency of the system, a numerical model was developed, capable of determining the thermal performance of the conventional DSF. The numerical model is composed of airflow and thermal models. This paper briefly describes the development of the models as well as the models’ verifications. Models were then used to carry out a series of parametric studies to investigate the effect of thermal mass on the energy performance of the integrated system. The simulation results revealed that mechanically ventilated DSF can save energy based on configuration from 21% to 26% in summer and from 41% to 59% in winter as compared to conventional DSFs without thermal mass. The results also showed the total saving for a naturally ventilated DSF is negligible year-round. [Copyright &y& Elsevier]

Abstract: The general methodology for estimating energy consumption in buildings, in accordance with the EN ISO 13790, needs the use of constants that are valid for each set of climatic conditions. Furthermore, there are variables other than building structure and weather conditions that have an influence. In this sense, recent research works showed the real effect of permeable coverings on indoor environmental conditions, by controlling indoor moisture. The effect of the associated heat and mass transfer on heating or cooling energy consumption is evident during the initial hours of building occupation. In the present paper, the general methodology of building heat demand calculation is modified to consider different levels of permeability of internal coverings, in order to obtain a more accurate model. Results showed that permeable coverings are related with a higher building utilisation factor, and that the value of this factor is higher in summer than in winter season. Consequently, despite the fact that the sensibility of energy consumption to internal coverings may be lower than to building envelope, new constants are proposed to express a relationship between building permeability and energy consumption, in order to apply the certification equation. [Copyright &y& Elsevier]

Abstract: This paper deals with the numerical three-dimensional prediction of the induced flow patterns around and inside a building, which is cross-ventilated in a natural way. The air change rate is controlled by two opposite openings on the building envelope, as a function of wind velocity and its incidence angle. The numerical methodology is based on the finite volume numerical solution of the Navier–Stokes equations, using the CFD commercial code FLUENT. The numerical results are compared with available experimental data regarding the refresh rate of the building''s room and the relative velocity profiles at the window openings, indicating a good agreement. Furthermore, a detailed description of the natural ventilation process is provided, whilst additional information regarding the induced velocity and pressure field is presented; information which cannot be easily extrapolated by experimental methodologies. Finally, the impact of the inner topology of the building on the induced flow field is investigated. [Copyright &y& Elsevier]

Abstract: An Earth-to-Air Heat Exchanger (ETAHE) is a low energy cooling and heating building component. It uses the ground''s thermal storage to dampen ambient air temperature oscillations by delivering the air through a horizontally buried duct. To reduce airflow resistance, some hybrid ventilated buildings have recently adopted large cross-sectional area ducts. This paper describes the development of an Artificial Neural Network based Heat Convection (ANN-HC) algorithm to predict local average Nusselt Numbers along the duct surfaces. Furthermore, the ANN-HC algorithm is integrated with a transient three-dimensional heat transfer model based on finite element analysis of heat conduction in the ground domain surrounding the ETAHE to establish a new thermal modeling method for ETAHEs. A case study is presented to demonstrate the working principle of the new method. It is shown that the method can very well simulate the interactions between an ETAHE and its environment. [Copyright &y& Elsevier]