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Abstract The ventilation effect in different places in the teaching building is different. The aim of this paper is to study the relative ventilation relationship of the rooms in "line" type middle school teaching building. Taking Xiamen in the subtropical region as a typical city, a number of parameters such as the inside and outside corridors, different room sizes and different ventilation angles were set as variables, using the CFD simulation method. Combined and separated effects of the defined parameters on natural ventilation performance are evaluated using the ratio of air-age area as criteria. The result shows that the "line" type teaching building with outside corridor ventilation is 35.55% better than the inside corridor. In addition, the ventilation in large room is 30.84% better than that in small rooms. In 0°–35° wind direction, the closer the room to the incident wind the better in ventilation, but in a certain angle range of 59°–90°, the room farther away from the incident wind, the better in ventilation. The best wind angle of "line" teaching building ventilation is 305°–55°. The research results in this paper can help architects to design buildings more scientifically and reasonably. Highlights • "Line" type teaching building should adopt outside corridor form, it is conducive to ventilation in subtropical area. • The outside corridor ventilation effect is 35.55% better than the inside corridor. • Large room is suitable for laboratory and small room is suitable for temporary lounge cause ventilation feature. • The ventilation effect of the classrooms is related to the wind direction and classroom positions. [ABSTRACT FROM AUTHOR]

This paper describes the results of experimental tests and computer simulation modelling aimed at evaluating the performance of an electrochromic (EC) window with respect to solar radiation control and the relative impact on the energy consumption of buildings of the residential type for two typical Italian climates. The research is carried out by a test-cell equipped with a small area EC double glazing unit and by a simulation program of buildings’ energy behaviour in transient regime. The experimental results show that EC devices which modulate solar radiation mainly by absorption, like the one investigated in this paper, generate secondary solar heat gains which entails a 20% decrease of the maximum potential energy flux reduction. Also, this effect could rise the temperature of the internal glass pane of the glazing to levels for which risk of thermal discomfort for the occupants may occur. The computer simulation modelling involves a residential building unoccupied during a large fraction of daytime in weekdays. The savings potential of the investigated EC window are calculated relative to a conventional clear float double glazing unit. Results show that the EC glazing may lead to a considerable decrease of the cooling energy demand (and of the total building energy consumption) in cooling dominated climates. The energy saving benefits become less marked in heating dominated climates and, for low values of the window-to-wall ratio, can be overcame by the increase in lighting and heating energy requirements that results in an increase of the total building energy demand. [ABSTRACT FROM AUTHOR]

Recently, demand flexibility has been highlighted as a promising distributed resource from the customer side, especially from industrial customers like commercial buildings, capable of providing grid support services. However, the quantification of demand flexibility is a complex process that requires a methodology including the requirements of both the grid operators and the customers. This paper proposes a novel approach to quantify the available demand flexibility of individual buildings, while taking into account the underlying building energy physics. The proposed approach constructs on the operational flexibility concept from the power systems, and extends it to include a comfort domain, identifying different flexibility parameters with the aim of giving a better insight into the flexibility potential of commercial buildings. This method includes a development of building energy simulations to assess the effects of weather variations, construction types, and comfort constrains on demand flexibility. The proposed quantification method has been validated using 15 different office building models and two different climate zones, i.e., the Netherlands and Texas, US. The results presented in this paper suggest that buildings located in a hot climate could offer higher flexibility potential during shorter time ranges, while buildings in a cold climate could offer lower flexibility potential but during longer time ranges. Determining these differences could potentially facilitate the dispatch of flexible demand resources, to assess their real potential, and to schedule demand flexibility between stakeholders. [ABSTRACT FROM AUTHOR]

Many retrofit projects are being carried out in existing buildings to reduce energy consumption. However, the energy consumptions before and after retrofit need to be known in order to evaluate such retrofit projects. Even though the energy consumption after retrofit can be determined through measurement, the energy consumption before retrofit cannot be known. This study is to more easily estimate energy usage prior to the retrofit. Generally, dynamic simulation or regression model should be used to estimate the energy consumption of buildings before retrofit. However, existing regression models have no way to calibrate the model if it is inaccurate. In this paper, we use a clustering technique to improve the accuracy of the regression model. The estimation of energy consumption before retrofit is referred to as “baseline model” and the inverse model is used to create this baseline model. The inverse model is created through monthly data, daily data, and other similar data. In this study, the inverse model was created through daily data and the baseline model was derived from it. The conventional change-point Model and the cluster inverse model presented in this paper were compared and evaluated with the criteria presented through M&V (Measurement and Verification). The results suggest that the cluster inverse model which reflects the characteristics of data is more appropriate when the baseline model is derived from daily data. [ABSTRACT FROM AUTHOR]

Harvesting daylight for improving building energy performance has become an important issue in recent years. Most energy simulation tools use a Daylight Factor (DF) based algorithm to capture the complexity of daylight behaviors. However, DF has a limitation for fully accounting realistic daylight conditions, and several modifications or integrations with other supporting tools were developed to compensate for this limitation. This paper uses the Kriging method to predict daylight conditions for a whole year, and couples this method with energy simulation tools. Kriging is a group of geo-statistical techniques used to interpolate the value of a random field at an unobserved location from discrete observed values at nearby locations. In previous research, the Kriging method showed promising outcomes; that result was significantly better than current daylight modeling in energy simulation tool, and very close to the results from advanced physics-based daylight simulation tool. However, Kriging also comes with certain limitations that require further investigation. One major hurdle was Kriging’s long computational time compared to current daylight models in energy simulation tools. For this reason, this paper aims to find possibilities to reduce computational time to realistic levels that can be applicable in practice. Furthermore, it proposes a method to integrate Kriging-based daylight model with an energy simulation tool that can plot hourly indoor light distribution. This proposal obtains more realistic results than current energy simulation daylight models, while reducing computational expense. [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]

Abstract Sensitivity analysis (SA) can be applied to building energy models (BEM) to identify which input parameters that drive the majority of the model output variation. The screening-based Morris method is often applied for this purpose; however, consideration regarding the effect of the user-defined number of levels (p) and trajectories (r) on the obtained results are rare. This paper investigates how the choice of p and r affects the outcome of a SA using the Morris method on a high fidelity BEM. The results indicates that the Morris method was not able to replicate the ranking from the variance-based Sobol' method no matter the choice of r and p. It was, however, able to identify groups of input parameters (parameter clusters) most sensitive to the model output variability, but it required significantly more r than usually applied in studies featuring the Morris method. The reason is that marginal differences in absolute values of elementary effects (the sensitivity indices of the Morris method) for some input parameters may lead to a change in ranking position several times as the number of r increases. Users of the Morris method must therefore not be predetermined on the size of the parameter cluster; instead, they must make a visual assessment of the convergence of the parameter ranking to qualitatively determine the appropriate size of parameter cluster. The final recommendation for future studies deploying the Morris method for SA applied to a high fidelity BEM is to choose p ≥ 4 as it seems to lead the analysis towards a more truthful ranking, and then run simulations in steps of r = 100 when making the visual assessment to determine convergence and the size of parameter cluster. The identified need for more r questions the general notion that the Morris method is a computationally efficient screening method in terms of absolute time use. However, the Morris method is still much more computational efficient than a Sobol'-based analysis if the purpose of the SA is to identify a cluster of input parameters most sensitive to the model output variability. [ABSTRACT FROM AUTHOR]

Building life cycle assessment (LCA) aims at guiding decision towards more sustainable alternatives of a building project. But, in order to successfully reduce the high environmental impacts of the building sector, the results of building LCA have to be robust. Sensitivity analysis (SA) helps at investigating the sources of uncertainty and variability in a model and assessing the results' robustness. Choosing an adapted SA method remains difficult: using the more precise SA methods would require a too large calculation time, particularly for an application in early design phase. In this paper, the most influential factors of building LCA tools, linked with energy simulation tools, were investigated using screening and global SA methods that are compatible with the building LCA fields. The relative influence of the uncertain factors served as a metric to compare more precisely the results given by this large panel of methods. The results show that despite their different precision vs computational cost compromises, all the methods identified the same set of influential factors. In the studied case of a passive single family house, they consisted in the building lifetime, the electricity production mix and factors affecting the energy consumption. However, the relative influence of the factors differed. Two new method adaptations were investigated in order to obtain precise results in a reasonable simulation time. The adaptation of the Plackett and Burman (PB) screening performed well compared to the reference method (Sobol indices), as the same set of influential factors was always identified in a calculation time divided by almost 30. [ABSTRACT FROM AUTHOR]

Building energy models (BEMs) are typically used for design and code compliance for new buildings and in the renovation of existing buildings to predict energy use. The increasing adoption of BEM as standard practice in the building industry presents an opportunity to extend the use of BEMs into construction, commissioning and operation. In 2009, the authors developed a real-time simulation framework to execute an EnergyPlus model in real time to improve building operation. This paper reports an enhancement of that real-time energy simulation framework. The previous version only works with software tools that implement the custom co-simulation interface of the Building Controls Virtual Test Bed (BCVTB), such as EnergyPlus, Dymola and TRNSYS. The new version uses an open standard interface, the Functional Mockup Interface (FMI), to provide a generic interface to any application that supports the FMI protocol. In addition, the new version utilizes the Simple Measurement and Actuation Profile (sMAP) tool as the data acquisition system to acquire, store and present data. This paper introduces the updated architecture of the real-time simulation framework using FMI and presents proof-of-concept demonstration results which validate the new framework. [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]

Climatic conditions strongly affect the energy performance of buildings, and due to the synergy between global climate change and the Urban Heat Island (UHI) effect, the climatic conditions inside and outside the city are highly different. However, weather data collected at airports are commonly used for building energy simulations and these data do not take into account real temperature distribution in cities. Many studies in the literature address the topic but mostly considering only a couple of urban and non-urban stations. In this paper, the urban climate in Rome, Italy, is analysed after monitoring of the air temperature and relative humidity in four selected neighbourhoods and one reference station from October 2014 until September 2017. Rome is characterised by a composite urban pattern and high variability of building types, of which the four selected areas are representative. The heating degree days decrease up to 18% and cooling degree days increase up to 157% in the urban area with respect to the rural reference and the area most affected by the UHI is the city centre. The UHI is more intense in summer than in winter (average increase between 0.7 °C and 1 °C); while the diurnal and nocturnal UHI depends on the season and the neighbourhood. Then, the energy performance of a representative apartment block and a typical office building was computed using the measured data. Regarding the predicted energy performance, comparing the four urban sites and the reference site, the UHI causes a reduction of heating consumption up to 21% in residential building and 18% in the office building. An increase of cooling consumption up to 74% is instead computed for the residential building and up to 53% for the office building. [ABSTRACT FROM AUTHOR]

The requirements concerning energy performance of buildings and their internal installations, particularly HVAC systems, have been growing continuously in Poland and all over the world. The existing, traditional calculation methods following from the static heat exchange model are frequently not sufficient for a reasonable heating design of a building. Both in Poland and elsewhere in the world, methods and software are employed which allow a detailed simulation of the heating and moisture conditions in a building, and also an analysis of the performance of HVAC systems within a building. However, these systems are usually difficult in use and complex. In addition, the development of a simulation model that is sufficiently adequate to the real building requires considerable time involvement of a designer, is time-consuming and laborious (Menberg et al., 2019) [1]. A simplification of the simulation model of a building renders it possible to reduce the costs of computer simulations. The paper analyses in detail the effect of introducing a number of different variants of the simulation model developed in DesignBuilder on the quality of final results obtained. The objective of this analysis is to find simplifications which allow obtaining simulation results which have an acceptable level of deviations from the detailed model, thus facilitating a quick energy performance analysis of a given building. [ABSTRACT FROM AUTHOR]

Solar heating should be recommended strongly for domestic buildings in the Qinghai–Tibetan plateau due to the area's high intensity radiation. In this paper, a novel hybrid solar heating system is presented, that includes a solar kang system, a Trombe wall and a direct gain window. The effects of five combined solar heating operation modes on the indoor hourly temperature for one case domestic building located in the Qinghai–Tibetan plateau were investigated by field measurement and numerical simulation. The optimal operation mode for improving the indoor thermal environment was determined. Furthermore, the effectiveness of each operational mode on the east room was quantitatively evaluated and ranked. The results show that the numerical simulation and field experimental results were well agreed, although there were some differences in specific values. In addition, the results it indicated that a solar kang running all days and Trombe wall running daytime played a significant role in improving the indoor thermal temperature. These relevant findings could provide a reference for solar heating system design and indoor thermal comfort improvement for rural domestic buildings in the Qinghai–Tibetan plateau. [ABSTRACT FROM AUTHOR]

Energy consumption models play an integral part in energy management and conservation, as it pertains to buildings. It can assist in evaluating building energy efficiency, in carrying out building commissioning, and in identifying and diagnosing building system faults. This review takes an in-depth look at energy-demand prediction models for buildings in that it delves into recent developments in building energy approaches used to predict energy usage. By enlisting current approaches to the modelling of buildings, methods for building energy simulations can be categorized into four level classes as follows: (i) data-driven approaches; (ii) physics-based approaches; (iii) large scale building energy forecasting approaches; and (iv) hybrid approaches. The focus of this review is to target the data-driven approach and large-scale building energy predicting-based approaches. Here the data driven approaches can be categorized by (1) artificial neural network based approaches; (2) clustering based approaches; (3) statistical and machine learning-based approaches; and (4) support vector machine based approaches. From there, the type of data-driven based approach is further grouped by (a) benchmarking models; (b) energy-mapping models; (c) energy forecasting models; and (d) energy profiling models. Large-scale building-energy prediction techniques is then categorized as follows: (1) white-box based approaches; (2) black-box based approaches, and (3) grey-box based approaches. The current study explores first-rate data-driven based approaches about building energy analysis for industrial, commercial, domestic, etc., within a rural and urban setting. This review paper is based on the necessity of identifying points of departure and research opportunities for urban and rural-level analyses of building level energy performance. A variety of issues are explored which include: energy performance metrics; end-use of different building types; multiple levels of granularity; and urban and rural scales. Each technique encompasses a variety of input information as well as varying calculations or simulation models along with furnishing contrasting outcomes that suggest a variety of usages. A thorough review of each technique is presented in this study. This review highlights strengths, shortcomings, and purpose of the methods of numerous data-mining based approaches. A comprehensive review of energy forecasting models that are specified in the literature part is also provided. [ABSTRACT FROM AUTHOR]

Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching. [ABSTRACT FROM AUTHOR]

Climatic zoning for building energy efficiency applications is an important element in building energy policy and regulations. There are several methodologies available to conduct climatic zoning, providing significantly different results. Currently, there are no procedures to assess the validity of a proposed climatic zoning, hindering the decision to use one particular climatic zoning methodology instead of another. This paper introduces a quality index and a procedure to support the validation of climatic zoning. The procedure is based on building performance simulation results concerning the building stock that is targeted in the climatic zoning policy or program. Simulation results are used to calculate a new index, the Mean Percentage of Misclassified Areas (MPMA), which assesses the quality of the zoning under analysis. The capabilities of this procedure were demonstrated by the evaluation of four alternatives for the climatic zoning of Nicaragua, obtained using different methodologies and previously reported in the literature. The building stock used in this case study is composed of a few archetypes based on typical naturally ventilated dwellings in this country. Simulations were conducted using the program EnergyPlus for a total of 328 locations in Nicaragua. Degree-hours of discomfort based on the adaptive model of ASHRAE Standard 55 were used as a performance indicator. Results indicate that zoning obtained using cluster analysis and cooling degree-days may misclassify 1 out of 5 areas in Nicaragua (MPMA around 18–20%). This study concludes that the validation procedure and proposed index are useful for highlighting qualities and deficiencies of existing climatic zoning methods, particularly when these methods are used in less conventional applications, such as for policy making targeting naturally ventilated dwellings in tropical climates. The application of this procedure in more than 50 countries which adopt climatic zoning is foreseen as the next step in his area, substantially affecting the prescription of building materials and components worldwide. [ABSTRACT FROM AUTHOR]

Building performance simulations (BPS) are used to test different designs and systems with the intention of reducing building costs and energy demand while ensuring a comfortable indoor climate. Unfortunately, software for BPS is computationally intensive. This makes it impractical to run thousands of simulations for sensitivity analysis and optimization. Worse yet, millions of simulations may be necessary for a thorough exploration of the high-dimensional design space formed by the many design parameters. This computational issue may be overcome by the creation of fast metamodels. In this paper, we aim to find suitable metamodeling techniques for diverse outputs from BPS. We consider five indicators of building performance and eight test problems for the comparison six popular metamodeling techniques – linear regression with ordinary least squares (OLS), random forest (RF), support vector regression (SVR), multivariate adaptive regression splines, Gaussian process regression (GPR), and neural network (NN). The methods are compared with respect to accuracy, efficiency, ease-of-use, robustness, and interpretability. To conduct a fair and in-depth comparison, a methodological approach is pursued using exhaustive grid searches for model selection assisted by sensitivity analysis. The comparison shows that GPR produces the most accurate metamodels, followed by NN and MARS. GPR is robust and easy to implement but becomes inefficient for large training sets compared to NN and MARS. A coefficient of determination, R 2 , larger than 0.9 have been obtained for the BPS outputs using between 128 and 1024 training points. In contrast, accurate metamodels with R 2 values larger than 0.99 can be achieved for all eight test problems using only 32–256 training points. [ABSTRACT FROM AUTHOR]

This paper presents a study on energy performance of an earth air heat exchanger (EAHE) for buildings in Maghreb climatic context (Oran, Bechar and Adrar cities in Algeria). In order to check the influence of the material, two air conducts (one of galvanized sheet metal and the other in polyvinyl chloride–PVC) are considered under the same geometric conditions (a 20 m conduct length, 120 mm diameter and 2 m burial depth). They are used separately for the ventilation in simple current flow of two adjoining rooms constituting a test cell located at the university campus IGCMO-USTOMB (Oran, Algeria). An experimental device has been set up to measure the temperature at different points (air inlet/outlet air duct). Measurements were run in August 2015, and the monitoring of both exchangers allowed us to evaluate their cooling performance: 35.41% for the Zinc pipe and 58.42% for the PVC pipe. Experimental results were compared to those obtained from the simulation (under the Trnsys 16) and a fair similarity is obtained. In order to optimize the energy performance of the exchanger (EAHE), numerical simulations are carried out by varying different parameters: climate, burial depth, length and diameter of the duct. Other simulations have shown that the energy supplied by the cooling exchanger (EAHE) is more significant in the south of the country (Adrar and Bechar) than in the north (Oran). [ABSTRACT FROM AUTHOR]

This paper analyses annual energy performance of atrium type hotel building in Belgrade. The objective is to examine the impact of the atrium on the hotel building’s energy demands for space heating and cooling. Integrated approach through numerical simulations that include Belgrade climate data and thermal comfort parameters, indicates an optimal model of hotel building with atrium for this area. Building energy simulation is carried out using EnergyPlus simulation engine, as a basic tool in the process of building energy optimization. The methodological approach includes the creation of a hypothetical model of an atrium type hotel building, numerical simulation of energy performances of several design alternatives of the hotel building with atrium, and comparative analysis of the obtained results. The main task of analysis is to change certain parameters in the particular model (for example, building structure, orientation, etc.) and to observe how the changes influence energy performance of the building. The goal of this research is to show that the atrium contributes to the heating and cooling energy savings in the rest of the building, but also that the atrium itself demands a lot of energy for its air-conditioning. The most sustainable solution should be to cover energy demands for atrium by using the renewable energy sources. In this case, the atrium can contribute to the energy efficiency of the hotel building in Belgrade climatic conditions, thus reducing its negative impact on the environment. [ABSTRACT FROM AUTHOR]

[Display omitted] • The hysteresis is due to the difference of primary nucleation mechanism during heating and cooling. • The PCH is related to the properties of the material itself and the experimental measurement conditions. • The hysteresis temperature is positively correlated with the heating/cooling rate. • The hysteresis effect is more obvious in an incomplete phase transition. • Numerical models of the hysteresis effect of complete and incomplete phase transition are summarized. As an efficient energy storage material, phase change material can be combined with lightweight buildings to reduce the energy consumption of the building envelopes effectively, while it is often accompanied by phase change hysteresis(PCH) and supercoiling (SC) phenomena during the phase transition. SC means that the nucleation does not solidify at the theoretical solidification temperature and needs to be nucleated at a lower temperature. PCH indicates the difference between the melting temperature and the solidification temperature of the phase change materials (PCMs). So far, a lot of research on SC has been done and there is still a lack of research on PCH. On the one hand, the PCH is proportional to the energy loss of the system, the latent heat of PCMs cannot be exploited if PCH is beyond the operating temperature range of the system. On the other hand, when PCMs are combined with building envelopes, the greater the hysteresis temperature, the better the thermal performance of the wall. It's vital to use the hysteresis temperature to improve the performance of the system. Especially, PCMs are equipped in building envelopes, the hysteresis phenomenon of incomplete phase transition will be more obvious because of large temperature fluctuation outside. The hysteresis effect of PCMs in building envelopes is discussed in this paper, the numerical simulation methods and experimental research of PCH are reviewed and analyzed from two aspects of complete and incomplete phase transition. It showed that the PCH should be considered when simulating the thermal behavior of PCMs in building envelopes. The results would be more accurate if two enthalpy-temperature curves (H(T) curve) are used to represent the melting and solidification process, respectively. In addition, the nucleation mechanism of PCH has not been discussed in previous articles and there is no explanation about whether the hysteresis phenomenon is caused by the properties of the material itself or is affected by experimental measurement conditions. Therefore, the related issues are discussed in this paper, it is considered that the PCH is not only related to the properties of the materials but also affected by the experimental measurement conditions. [ABSTRACT FROM AUTHOR]

Abstract: In the last years many studies concerning the evaluation of the thermal conductance of building elements via measurements have been carried out; this value has to be ensued from the analysis of recorded temperature and heat flux profiles. The determination of this property in situ would allow a more accurate a more accurate evaluation of the real heating energy demand of a building. Papers discussing different data analysis methods are present in literature and measurements on test components under real conditions and evaluations on different theoretical aspects by means of numerical simulations have been already developed. This paper aims at widening the existent literature of the in situ evaluation of the thermal conductance, through the discussion of the results of a measuring campaign which lasted four years on real buildings, and by comparing the reference specific thermal conductance (C) values with those computed on the basis of the measurements. Various tests on the same elements are discussed. Finally an analysis on the influence of the C value on the evaluation of the net heating energy demand of a building in different climates is presented. [Copyright &y& Elsevier]

Abstract: This paper presents a method to determine the optimum capacity of distributed generation technologies for buildings. The Combined Heat and Power (CHP) unit has both absorption and electric chiller for cooling loads, and a supplementary boiler for heating loads. The demand is uncertain in the model. The underlying uncertainty is modeled using probabilistic theory. In this method, the expected value of the objective function is evaluated using numerical approaches. A simulation based optimization method is presented which can estimate the cost of system operation and find the appropriate design by means of stochastic programming. The effect of minimum economic turn-down of the facilities is also discussed in this paper. The optimum capacity of distributed generation technologies has a great effect on the cost of the building. Therefore, the proposed method is applied for a hospital in Iran as a case study. The results show that the optimum capacities of CHP and absorption chiller decreases and the capacities of the electric chiller and boiler rise by an increase in demand uncertainty. In addition, the appropriate minimum economic turn-down of facilities has a considerable effect on the overall system cost. [Copyright &y& Elsevier]

Abstract: Recent results show that a predictive building automation can be used to operate buildings in an energy and cost effective manner with only a small retrofitting requirements. In this approach, the dynamic models are of crucial importance. As industrial experience has shown, modeling is the most time-demanding and costly part of the automation process. Many papers devoted to this topic actually deal with modeling of building subsystems. Although some papers identify a building as a complex system, the provided models are usually simple two-zones models, or extremely detailed models resulting from the use of building simulation software packages. These are, however, not suitable for predictive control. The objective of this paper is to share the years-long experience of the authors in building modeling intended for predictive control of the building''s climate. We provide an overview of identification methods for buildings and analyze their applicability for subsequent predictive control. Moreover, we propose a new methodology to obtain a model suitable for the use in a predictive control framework combining the building energy performance simulation tools and statistical identification. The procedure is based on the so-called co-simulation that has appeared recently as a feature of various building simulation software packages. [Copyright &y& Elsevier]

In this paper the authors present an algorithm that abstracts an arbitrarily shaped set of building volumes into a group of simplified ‘shoebox’ building energy models. It is shown that for generic perimeter and core floorplans the algorithm provides a faster but comparably accurate simulation results of annual load profiles vis-à-vis multi-zone thermal models generated according to ASHRAE90.1 Appendix G guidelines. Envisioned applications range from rapid thermal model generation for urban building energy modelling to schematic architectural design. Following a description of the algorithm, its ability to produce load profiles for a mixed-use neighborhood of 121 fully conditioned buildings for a variety of climates is demonstrated. The comparison yields relative mean square errors in simulated annual building energy use intensity of five to 10 percent compared to ASHRAE 90.1 compliant building energy models while reducing simulation times by a factor of 296. [ABSTRACT FROM AUTHOR]

This paper presents a novel method to determine building envelope thermal transmittance (known as U-values) and air infiltration rate by a combination of Energy modeling (DesignBuilder and EnergyPlus), regression models and genetic algorithm at quasi-steady state conditions. DesignBuilder is used to develop the thermal model of an office building, including physical building models, materials specification, occupancy schedules, detailed HVAC system and components for energy simulation purposes. Specifically, the simulation was carried out in EnergyPlus at diverse U-values and air infiltration rates to produce a large datasets. Subsequently, the results were used to generate a linear regression model to evaluate the associations of thermal demands with U-values and air infiltration rate. Genetic algorithm was then applied to obtain a set of U-values and air infiltration rate with the minimum difference between field measurement and model prediction. The calibrated U-values and air infiltration rate were employed as inputs in EnergyPlus to model one workday heat consumption. When compared with thermal demand from measured data, the accuracy of the calibrated model improved significantly. [ABSTRACT FROM AUTHOR]

In recent years, the construction industry has been comprehensively focusing on energy performance of buildings and on achieving higher standards of living comfort. One of the most sophisticated ways to attain both at the same time is (re)achieving building’s climate balance by using bioclimatic design. Therefore, the main goal of this paper was to present a bioclimatic potential prognosis and to show its application on an example of the Alpine-Adriatic region. The bioclimatic potential prognosis was made for 21 characteristic locations. For this purpose, bioclimatic chart plots were made using elementary weather data and additionally, the actually received solar irradiance was precisely considered at every location. The latter was shown to have a large influence on the analysis results. Furthermore, an evaluation of performed bioclimatic potential prognosis was made with simulations of a generic building model using Energy Plus. The generic building model was tested in five selected locations and the heating and cooling demand results were compared with the bioclimatic potential analysis. The results showed that the application of the presented method can indicate which passive solutions should be applied in building design at a specific location in order to facilitate smaller energy usage and consequential higher indoor comfort. In addition, the presented approach can be used in order to incorporate the latest or predicted climate data into bioclimatic potential analysis. The latter has a significant influence on the design of buildings of the future. [ABSTRACT FROM AUTHOR]

Energy efficient renovation of the existing housing stock is imperative to reduce building energy consumption since the building sector in Europe accounts for an estimated 40% of the energy used from all sectors and more than 80% of the buildings today will still exist in 2020. Following Europe’s energy objectives, the paper investigates, based on the European Union Directives, the current energy refurbishment rates and examines the future energy performance of the Cyprus housing stock, in order to determine if they are adequate in achieving the Europe energy targets. The research focuses on pilot houses in Cyprus, which include dwellings from all typologies as classified, according to the IEE project EPISCOPE. The houses were monitored and based on the collected data and the performed simulations, their current and future energy performance are presented in the form of Energy Performance Indicators (EPIs). From the study, it is observed that with the current trends the national climate protection energy targets are unattainable. This is mainly due to the inadequate rate and depth of energy refurbishment of the existing housing stock and the ineptness of the Directives to address effectively the reduction of the cooling energy needs in the new constructions. [ABSTRACT FROM AUTHOR]

The paper shows the results of measurements of carbon dioxide concentrations conducted in the school buildings located in two different climates: Białystok (Poland) and Belmez/Córdoba (Spain). CO 2 concentration in first 45 min met requirements of regulations, but with medium occupation of places in classrooms, then the recommended values were excided. We developed a model for CO 2 level estimation. This model allowed us to simulated the CO 2 concentration for full occupation of classrooms in both countries. In these cases CO 2 concentration would exceed maximum value (1000 ppm) during the first hour. Furthermore required air change rates were calculated: for actual occupation they should be in a range 2.5–5 h −1 to maintain IDA2 and carbon dioxide concentration below 1000 ppm, while in case of full occupation even 6–9 h −1 . Finally, surveys of student satisfaction were performed in situ during the measurements of CO 2 level to obtain the dependence of student comfort perception on this concentration. [ABSTRACT FROM AUTHOR]

Evaluation methods can be used to determine what constitutes good energy performance in a building. With an increasing focus on energy use of buildings worldwide, this evaluation assumes a fundamental importance. This paper provides a comprehensive review of the available methods for analysing, classifying, benchmarking, rating and evaluating energy performance in non-domestic buildings. Methodologies are grouped in five categories: engineering calculations, simulation, statistical methods, machine learning and other methods. Techniques for evaluating buildings are described, their principal applications are shown and limitations are identified. The use of performance evaluation in energy efficiency programmes and standards is mapped. There is a need to further develop interactions between the main modelling techniques to produce simple, robust and validated models. Also, evaluation techniques must be developed to consider comfort or service provision in the buildings as a factor in energy performance. [ABSTRACT FROM AUTHOR]

Abstract: Many systems used in buildings for heating, ventilating, and air-conditioning waste energy because of the way they are operated or controlled. This paper explores the application of model predictive control (MPC) to air-conditioning units and demonstrates that the closed-loop performance and energy efficiency can be improved over conventional approaches. This work focuses on the problem of controlling the vapor compression cycle (VCC) in an air-conditioning system, containing refrigerant which is used to provide cooling. The VCC considered in this work has two manipulated variables that affect operation: compressor speed and the position of an electronic expansion valve. The system is subject to constraints, such as the range of permissible superheat, and also needs to regulate temperature variables to set points. An MPC strategy is developed for this type of system based on linear models identified from data obtained from a first-principles model of the VCC. The MPC strategy incorporates economic measures in the objective function as well as control objectives. Tests are carried out on a simulated VCC system that is linked to a simulation of a realistic building that is developed in the U.S. Department of Energy Computer Simulation Program, EnergyPlus. The MPC demonstrated significantly better tracking control relative to conventional approaches (a reduction of 70% in terms of the integral of squared error for step changes in the temperature set-point), while reducing the VCC energy requirements by 16%. The paper describes the control approach in detail and presents results from the tests. [Copyright &y& Elsevier]

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell’s Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell’s method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell’s Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell’s Hybrid method presently used in HVACSIM+. [ABSTRACT FROM AUTHOR]

Several new technologies can be today implemented in buildings in order to achieve the NZEB goal. In this paper a novel computer model for predicting the energy demand of buildings integrating phase change materials, photovoltaic-thermal collectors, adjacent sunspaces and innovative daylighting control is presented. Through this tool, DETECt 2.2, written in MatLab and conceived for research purposes, the overall energy and economic performance of multi-zone NZEBs can be assessed. Both the active and passive effects on the energy demands of all the above mentioned technologies, even if simultaneously utilized, are taken into account by means of an integrated building modelling approach. In addition, parametric and sensitivity analyses, with a single simulation run, can be carried out for design purposes. A novel relevant case study referred to the energy design of a non-residential NZEB for Mediterranean climates is developed. For this building a suitable energy optimization analysis was also carried out. For each use of the indoor space, the optimal value of the pivotal design and operating parameters is calculated. Details about the optimal position of building PCMs and thermal insulation layers, also coupled to BIPV and/or BIPV/T systems, are provided. For the obtained best configuration very low heating and cooling demands are achieved (0.9 and 1.5 kWh/m 3 y, respectively). Results about a simplified economic analysis carried out on the investigated energy saving technologies are also reported. At last, new NZEB definition details and criteria are provided for non-residential buildings located in the southern European zones (Mediterranean climates). [ABSTRACT FROM AUTHOR]

Most current building thermal codes impose upper limits to the predicted annual building energy demand for heating, ventilation and air conditioning. In the building design phase these predictions are obtained using thermal simulations with variable complexity. The simplest approach uses a single lumped thermal capacitance to model the high thermal mass building elements, combined with five thermal resistances (known as the 5R1C model proposed in EN ISO 13790 standard). This model is used by many European countries as the reference simplified methodology to assess overheating risk and calculate yearly building energy demand. This paper presents a successful extension of this model that allows for its application to the prediction of the internal air temperature of free-running buildings with double skin façades. The extension consists in an increased number of thermal resistances used to model the double skin façade zone. The extended model is validated using a set of detailed thermal measurements obtained in a free-running double skin test cell. For the case analysed the simplifications used in the RC model do not reduce the overall accuracy: the mean absolute error for room air temperature is approximately 1 °C, the same order of magnitude of more detailed EnergyPlus simulations (1.2 °C). [ABSTRACT FROM AUTHOR]

Occupancy information in a building is critical in terms of indoor environmental quality, energy consumption and building energy simulation. However, it is not easy to gather and model the occupancy information. Within the framework of institutional buildings, the large occupancy number and the very high occupancy variation will pose a higher challenging for occupancy number counting and modeling. This review paper reviewed the techniques and modeling methodologies in buildings and listed the pros and cons for further consideration for the application in institutional buildings. [ABSTRACT FROM AUTHOR]

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermal loads, leading to more efficient operations than other system types. This paper introduces a new model that simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Compared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has more component models based on physics and thus has significant innovations in: (1) enabling advanced controls, including variable evaporating and condensing temperatures in the indoor and outdoor units, and variable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailed refrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, and pipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and (4) improving the usability of the model by significantly reducing the number of user input performance curves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from field tests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP system performance, which is key to determining code compliance credits as well as utilities incentive for VRF technologies. [ABSTRACT FROM AUTHOR]

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. Exploiting the equation-based language led to 2200 times faster solution. [ABSTRACT FROM AUTHOR]

Occupant behavior is a major contributing factor to building energy consumption. Large discrepancies might occur when occupants with diverse types in terms of behavior patterns reside in an identical building. Moreover, it is vital to derive several kinds of typical occupant behavior that represent the assemblage of occupants in a simplified way as the reference for building designers and energy policy makers. This paper presents a preliminary research on occupant behavior categorization through the building energy simulation, where some typical occupant air-conditioning behavior patterns use in Chengdu, China have been derived from a large-scale questionnaire survey based on the energy consumption levels. These typical occupant behavior patterns could be used as the context for an overview of building energy in a community, as well as the evaluation of building energy-saving technology where occupants are involved. Further efforts are required in the algorithm of dividing occupant behavior into typical patterns, the validation of the classification results, and the analysis of other behaviors. [ABSTRACT FROM AUTHOR]

Traditionally, in building energy modeling (BEM) programs, occupant behavior (OB) inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents a new OB modeling tool, with an occupant behavior functional mock-up unit (obFMU) that enables co-simulation with BEM programs implementing functional mock-up interface (FMI). The components detailed in the development of the obFMU include an overview of the DNAS (drivers-needs-actions-systems) ontology and the occupant behavior eXtensible Markup Language (obXML) schema, in addition to details on the creation of the obFMU that contains the co-simulation interface, the data model and solvers. To demonstrate functionality of the tool, three examples of occupant behaviors were simulated, including: (1) turning on and off lights, (2) opening and closing windows, and (3) turning on and off the air conditioners. The obFMU can be used via co-simulation with all building simulation programs that implement the FMI, thus users are not limited to a particular tool. Another advantage is the use of obXML schema to represent occupant behavior, standardize the description of occupant behavior enabling information exchange. [ABSTRACT FROM AUTHOR]

The paper introduces an approach to replicate building stock energy data using energy survey data. For demonstration of the approach, the research uses energy consumption data for office buildings in Chicago from Commercial Building Energy Consumption Survey (CBECS) 2003. The replication starts from derivation of the energy use distribution for a building stock in a specific location from the survey data. Then probabilistic methods are used to map building stock model space to real-world data space reflecting a weather adjustment of the energy survey data. The approach leverages a linear surrogate model of the physics-based reduced order normative energy model. The normative building energy model can rapidly estimate the building energy performance with respect to its design and operational characteristics. The research investigates a statistical procedure to inversely estimate building parameters using regression and Bayesian inference model based on the Markov Chain Monte Carlo (MCMC) sampling techniques. The research serves a new paradigm of the building stock aggregation that can lead to an efficient energy model, which contributes the body of knowledge of energy modeling beyond the single building scale. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) has been studied in the building science realm for about three decades. However, the following two aspects of the building control have not been studied thoroughly in MPC research. One is the impact of the mixed-mode cooling system on the active heating ventilation and air conditioning (HVAC) energy consumption, and the other is the differences of individual thermal comfort preference and its impact on energy. This paper proposes an occupant-oriented mixed-mode EnergyPlus predictive control system to optimize HVAC energy consumption while meeting the individual thermal comfort preference. A web-based dashboard is implemented in the test-bed building for three months to collect individual thermal comfort preference data. The data analysis results suggest that occupants have various tolerances and preferences about thermal comfort. The simulation results show that, during one week of a typical swing season, the mixed-mode system further reduces the active HVAC energy consumption, and the diversified occupant thermal comfort preference has significant impact on HVAC energy consumption. [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]

This paper quantifies green roofs energy savings which is a challenging topic, namely in Mediterranean climate with distinct heating and cooling seasons. The thermal behavior of a green roof case study in Lisbon, Portugal, was assessed through an experimental campaign during heating and cooling periods of the year of 2013. These experimental results were then used to calibrate a building energy simulation in EnergyPlus. After validation, the numerical model was used to compare the energy performance of intensive, semi-intensive and extensive green roofs. The three green roof types lead to similar heating energy needs but extensive green roof solution shows higher cooling energy needs than semi-intensive and intensive ones, of 2.8 and 5.9 times more, respectively. Furthermore, the performance of each type of green roof and different insulation properties was compared to traditional roof solutions. With no thermal insulation, extensive green roofs require 20% less energy use than black roofs and show a similar annual behavior than white roofs. Semi-intensive and intensive green roofs energy use is 60–70% and 45–60% lower than black and white roofs, respectively. Well insulated roofs do not take full advantage of evapotranspiration cooling effects, which is particularly noticeable when comparing with high reflective white roofs. [ABSTRACT FROM AUTHOR]

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead. [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]

In tropical countries such as India, increasing the roof albedo helps to reduce the heat ingress through the roof. This further reduces air-conditioning energy consumption in conditioned buildings and increases comfort in unconditioned buildings. In order to help users determine the benefits of high albedo roofs under varying conditions, a simple calculator has been developed. Parameters such as location, building type, roof area, and surface properties of the roof are taken as inputs. Annual EnergyPlus simulations are performed for the given parameters and the results are displayed in both graphical and tabular formats. It also calculates the simple payback by comparing a given base case roof albedo with the proposed roof albedo. The calculator can perform comfort simulations for unconditioned buildings and simulates measures including a radiant barrier system and under deck roof insulation. The calculator also runs a parametric simulation between insulation thickness and roof albedo to find an optimum roof insulation thickness based on incremental internal rate of return. This paper presents the features of the cool roof calculator and the type of analysis that can be performed using the cached results. [ABSTRACT FROM AUTHOR]

In this paper, measures such as planting urban greenery and using high-albedo paint to mitigate the urban heat-island effect, conserve energy, and reduce CO 2 emissions were assessed. As a typical energy-saving method for buildings, reducing the internal heat sources and increasing the insulation are also assessed. We used a coupled urban canopy and building energy model to predict the heat loads of buildings in city districts, the effects of air-conditioning on energy consumption, and air temperature changes. In this model, a vertical one-dimensional local atmospheric model is coupled with an air-conditioning load calculation model for buildings, making it possible to assess the interaction between anthropogenic heat release due to air-conditioning usage and the outside thermal environment. In this study, we selected a target study region in the city of Kawasaki, Japan. When typical city districts were assessed, planting greenery or increasing albedo achieved temperature reductions of 0.6–1.0 °C and 0.1–0.5 °C, respectively, and energy savings of 40–80 and 70–90 kJ/m 2 /day (per unit floor area) on a typical summer day. The results from the large-scale assessment show that urban greening or albedo increases achieved the highest energy savings, of up to 400 t-CO 2 /day, in the entire target study region. [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]

Innovative and efficient ways to carry out numerical simulations are worth of investigation to reduce the computational complexity of building models and make it possible to solve complex problems. This paper presents a reduced order model, based on Proper Generalised Decomposition (PGD), to assess 2-dimensional heat and moisture transfer in walls. This model is associated with the multizone model Domus using an indirect coupling method. Both models are co-simulated to perform whole-building hygrothermal simulation, considering 2D transfer in walls. The whole-building model is first validated with data from the IEA Annex 41. Then, a case study is considered taking into account a 2-zones building with an intermediary shared wall modelled in 2 dimensions to illustrate the importance of the technique to analyse the hygrothermal behaviour of the wall. It has been highlighted that the whole model enables to perform more precisely analyses such as mould growth on the internal surface. In addition, important theoretical numerical savings (90%) are observed when compared to the large original model. However, the effective numerical savings are not so important (40%) due to the limitations of the co-simulation method. [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]

A deep three-years survey of the existing social housing stock in Emilia Romagna, Italy, has been completed helping to accomplish a full acknowledgement of more than 70 buildings in terms of both their envelopes and heating system characteristics. Analysing the outcome data, a simplified parametric calculation protocol has been created to operate a preliminary audit and energy retrofit simulation on the entire social housing stock of the Region. The results of the study, initial data about the energy state-of-the-art of the building cluster and feasible retrofit solutions, are useful to identify where to focus for a further and more accurate energy diagnosis. This paper represents a synthesis of a three-years research work, demonstrating the potential of the parametric assessment method in terms of evaluating environmental and energy benefits, deriving from scheduled retrofit actions, to assist technicians in endeavouring interventions priority. [ABSTRACT FROM AUTHOR]