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• Publicly available data was collected to construct reference buildings. • Random personnel behavior was modeled using time use survey data and Markov chains. • Building scenes in unbuilt areas were created using scenario generation algorithms. • A 28.3 % reduction in prediction error was achieved compared to traditional methods. • A more precise spatial distribution of energy consumption is illustrated. Urban Building Energy Model (UBEM) is a widely used method for load forecasting in urban energy planning. It typically depends on reference buildings to simplify particular scenarios and uses energy calculation software for load forecasting. However, significant challenges exist when using this approach in unbuilt areas, because there is no established distribution of buildings or a widely recognized database of reference buildings. To overcome this technical barrier, this paper introduces a new workflow - Scenario Urban Building Energy Model (S-UBEM). This approach utilizes publicly available databases to establish a reference building database and a stochastic human behavior database. By utilizing these databases and planning documents, the methodology can construct building energy use scenarios for the undeveloped area, ultimately achieving load forecasting. In this paper, the proposed method is validated by transforming the built-up area into an unbuilt state. The results demonstrate that S-UBEM more accurately represents the spatial and temporal distribution of energy consumption. This is evidenced by a 28.3 % reduction in the annual energy prediction error compared to the conventional method, as well as by visualizing the distribution of energy consumption at the building level. [Display omitted] [ABSTRACT FROM AUTHOR]

A large part of the energy for heating and cooling is consumed due to human needs for thermal comfort in the living environment. It is important to use a suitable method to design an energy-efficient building to satisfy the thermal comfort of residents throughout the year. This paper focuses on the implementation of the sensitivity analysis in the area of energy analysis of a prefabricated timber building on box models. The sensitivity analysis plays an important role in early planning, partially also presenting the energy analysis. A combination of the building energy simulation and the sensitivity analysis technique identifies key variables by order, which can either have a strong or insignificant impact on the further design of the energy efficiency of a building. Moreover, this paper presents a sensitivity analysis method performed on the case study of six different timber building models where design parameters, such as geometry, insulation features, glazing ratio and distribution, shading control and interior set-point temperatures, are varied in environments with different climatic conditions: moderate (Ljubljana), warm (Athens), and cold (Helsinki). The sensitivity analysis for a range of variable input parameters is conducted by using the global sensitivity analysis technique, i.e. the Morris method, which is based on the elementary effect. The main objective of the article is to provide guidance for researchers, professionals and building planners about the parameters they should focus on in the early planning of an energy-efficient timber building to reduce the energy required for heating and cooling, thereby ensuring constant thermal comfort in the living environment. The results of the sensitivity analysis, which serve as guidelines, show that the overall U-factor of a window, the solar heat gain coefficient, and a set-point temperature for heating are design variables that most affect the heating energy demand for the considered one- and two-storey box models in the three locations. The dominant parameters have on average 30% more influence on heating energy demand in cold climates than parameters in moderate climates and 88% more than in warm climates. While shading control and solar heat gain coefficient are the most influential parameters for cooling energy demand, with the dominant parameters in warm climates having on average 39% more influence than parameters in moderate climates and 49% more influence than parameters in cold climates. In the total energy demand for the operation of all box models under all climatic conditions, special attention should be paid to shading control. In addition, in moderate and cold climates, the overall U-value of the window and the internal set- point temperature in winter must be considered, and in hot climates, the solar heat gain coefficient is important. In the case of the two-storey box model, designers need to be careful about the glazing-to-wall ratio which depends on the orientation of the glazing (south-north or east-west). In this case, the dominant parameters have on average 47% more influence in warm climates than in cold climates and 56% more than in temperate climates. • Prefabricated timber-framed box models located in cold, moderate and warm locations were introduced. • Architectural parameters that minimize the total energy demand are searched. • The Morris method was used to identify the most influential parameters. • A guideline for early design of energy efficient timber buildings under different climatic conditions was developed. • Window characteristics, AGAW, shading and set-point temperature in winter have the strongest influence on energy demand. [ABSTRACT FROM AUTHOR]

This publication is considered the most promising path leading to the creation of energy-efficient engineering solutions for various buildings. This path begins with the first design calculations. The foundation for creating cost-effective heating and ventilation systems is carried out at the stage of forming the heat and mass balances of the premises as building components. Besides drawing the heat and mass balances must be closely connected with the study of the geometric parameters of premises and the thermal performance of the building envelope. In this paper a special way of heat load computing of heating and ventilation systems is considered. It is shown that considered method allows refining the calculations of heat losses of the building. The application of the proposed method to determine the transmission heat losses with the elemental approach is considered. The calculating method of ventilation heat losses with different variations of accounting the infiltration component is shown. Way of the joint account of heat energy consumption factors in a single mathematical apparatus is presented. The method of optimizing of heat loads during extreme operating conditions is reviewed. The paper shows further way application of accurate method in the design of buildings and the results of calculations. Some conclusions are suggested as a conclusion of this article. [ABSTRACT FROM AUTHOR]

This paper provides a critical review on the building neighborhood properties influencing the energy and airflows in urban neighborhoods. Specifically, the review focus is on the multi-scale modeling required to quantify this influence of the building neighborhood properties on the energy consumption in buildings. The energy consumption patterns of buildings located in dense city centers are highly dependent on the surrounding urban neighborhood, compared to the low density, suburban/rural regions, where the building energy consumption patterns are similar to an isolated building energy consumption patterns. Due to the complex nature of the outdoor airflow around the buildings in urban neighborhoods, a practical modeling approach utilizes multi-scale modeling to account for different spatial and temporal scales for the relevant transport processes. Specifically, this modeling approach aims to identify the most important neighborhood properties influencing building energy consumption. The urban morphology parameters, such as the urban plan area density, frontal area density, and mean height of the buildings represent successful examples of emerging properties suitable for development of generalized solutions and physical models at the neighborhood scale. This paper also reviews different modeling approaches that account for the impacts of the urban neighborhood properties on the thermo-fluid property of the air, surfaces, and sky in the built environment as the required inputs for accurate assessment of building energy consumption. Furthermore, these emerging properties of urban neighborhoods directly affect (1) the mitigation strategies for a better adaptation, (2) design performance metrics of neighborhoods for the green building rating systems, and (3) socio-environmental factors. [ABSTRACT FROM AUTHOR]

Abstract Building energy consumption accounts for 30% of the overall energy end use worldwide. This number is even much higher in urban areas. With rapid urbanization in China, cities are expanding with new constructions. It is essential to create an updated urban-scale building energy consumption database to represent energy use for different types of buildings in China, which could help urban planners, managers and decision makers to understand temporal and spatial building energy consumption distribution and ensure required electricity and/or gas supply. However, such urban-scale database is rarely found in China. This paper creates baseline EnergyPlus models for residential, small office and large office buildings and validates the baseline models using survey data from literature. Parametric simulations are conducted to consider different design factors, such as building enclosure, lighting power density, equipment power density, HVAC schedule, etc. In total 351 EnergyPlus models are generated to cover different energy use intensity scenarios. Data-driven regression analysis is conducted to predict building energy consumption using building price/rent. The prediction results are expected to provide design decision support for urban planning and power distribution for new constructions. [ABSTRACT FROM AUTHOR]

In a changing outdoor climate, new buildings as well as the existing building stock need to adapt in order to keep providing their inhabitants and users a comfortable and healthy indoor environment, with a minimum or - preferably - no increase in energy consumption. In this paper, the effectiveness of six passive climate change adaptation measures applied at the level of building components is assessed using building energy simulations for three generic residential buildings as commonly built in - among others - the Netherlands: (1) detached house; (2) terraced house; (3) apartment. The study involves both residential buildings that are built according to the regulations and common practice in 2012, and residential buildings that were constructed in the 1970s, with a lower thermal resistance of the opaque and transparent parts of the building envelope. The climate change adaptation measures investigated are: (i) increased thermal resistance; (ii) changed thermal capacity; (iii) increased short-wave reflectivity (albedo); (iv) vegetation roofs; (v) solar shading; and (vi) additional natural ventilation. This paper quantifies the effectiveness of these climate change adaptation measures for new residential buildings as well as for renovation of the current building stock. The performance indicator is the number of overheating hours during a year. It is shown that exterior solar shading and additional natural ventilation are most effective for this performance indicator. Furthermore, increasing thermal insulation to reduce energy use for heating demands additional measures to prevent overheating. [ABSTRACT FROM AUTHOR]

From an economic point of view, it is crucial to minimize the life cycle costs (LCC) of buildings undergoing energy renovations, hence an optimization approach is needed. Building energy use and power demand as well as energy efficiency measures are important issues while performing an LCC optimization. Thus it is of great importance to accurately predict the building energy use and power demand before and after energy renovation. This paper aims to address the performance of an in-house LCC optimization software, OPERA-MILP, which has a rather fast optimization procedure. The aim is fulfilled through comparison with building energy simulation software IDA ICE before and after cost-optimal energy renovation. Three historic buildings with different layout and construction properties are used as a case study. The results show good agreement in the calculations of buildings' power demand and energy use between OPERA-MILP and IDA ICE. The percentage difference in calculated annual energy use and buildings' power demand with OPERA-MILP compared to IDA ICE is shown to be maximum 11% and 8% for the studied climate zones, respectively. Total impact on LCC is estimated to be equal to or less than 8%. [ABSTRACT FROM AUTHOR]

Bioclimatic potential analysis is one of the starting points for bioclimatic building design. However, as climate changes are being brought into the spotlight, bioclimatic potential is being put into question as well, because traditionally used passive strategies at a specific location may no longer represent properly balanced approach. Therefore, the purpose of this paper was to systematically evaluate bioclimatic potential of the selected five locations. At these locations, bioclimatic potential was observed separately for each of the last five decades. In the second part, present and future energy performance of one bioclimatic and one non-bioclimatic real residential building was simulated. The results show that yearly balance between heating and cooling passive strategies changed through time in all the locations. For example, the use of overheating prevention strategies is becoming more significant than it used to be in the past. Specifically, the period of year when shading is needed to achieve thermal comfort increased by 2–7% points, depending on location. Energy performance analysis of the selected buildings showed that by 2050 both analysed buildings will become cooling dominated and that by 2050 the current design solutions in bioclimatic buildings will become irrelevant or at least extremely inefficient. In general, in temperate climate zone the prevailing bioclimatic strategies integrated in architecture focus on heating season. Therefore, bioclimatic strategies in a particular location must be re-evaluated in order to design new and retrofit existing energy efficient contemporary buildings with comfortable indoor thermal conditions. [ABSTRACT FROM AUTHOR]

Selecting suitable weather data is the premise of getting valid conclusion from building energy simulation. By analyzing the generation process of Typical Meteorological Year (TMY), this paper points out that existing well-accepted TMY generation methodologies mainly emphasis the thermal aspect of climatic environment during their typicality selecting process. Light aspect has not been taken into consideration. A case study is carried out to explore whether there would be a divergence of conclusion when conducting daylight-related simulations with different TMY data. Performance metrics including Daylight Factor (DF), Daylight Autonomy (DA), Useful Daylight Index (UDI) and daylight illuminance distribution have been compared. The result indicates that for static metric as DF, the variation between using different TMY data is insignificant. However, for dynamic metrics such as DA, UDI and illuminance distribution, the divergence is obvious. Researchers are suggested to take caution of this effect when comparing simulation conclusions from different studies. [ABSTRACT FROM AUTHOR]

Both a well-designed on-board monitoring campaign and an adequate data-driven statistical modeling method are required to accurately characterize the building's overall heat transfer coefficient (HTC). In this paper, we reflect on the latter by means of a theoretical deduction of the heat balance equation and case studies on simulation data. We demonstrate the impact of using air temperatures as a proxy for equivalent temperatures and neglecting the intercept when characterizing the HTC using a linear regression method on measurement data. [ABSTRACT FROM AUTHOR]

The approaching wind velocity is an important input parameter in wind-driven ventilation studies. The approaching wind velocity at a certain height must be approximated from the measured meteorological wind velocity because the wind data in weather data files are usually measured at a meteorological station at only one given height. The most commonly used approximation method is the power law, in which the power law index (PLI) is only one parameter. Its typical values are provided in some data sources, the use of which generally involves several assumptions. An important assumption is that it is constant. We conducted observations of the wind velocity profiles above a high-density area in Tokyo, Japan, using a Doppler LIDAR system. Our observations revealed that the PLI value is not a constant but rather a time-dependent variable. In ventilation studies, neglecting this phenomenon possibly limits the usefulness of the results because the ventilation airflows depend on the PLI value in given building characteristics and given weather data. This paper presents a probabilistic simulation model for evaluating the performance of natural ventilation, which takes the uncertainties in the PLI values into account. The simulation results provide a set of possible values for savings in cooling energy that are possible with natural ventilation. Different choices of PLI values can lead to errors of up to 45% in the estimation of potential savings in cooling energy when using natural ventilation. This study can support building designers and engineers in the reasonable design of naturally ventilated buildings. [ABSTRACT FROM AUTHOR]

The European Directive 844/2018, the EN 16798–1 and −2, and the ISO 17772 Standards establish that when designing a new building or energy retrofitting an existing building, the Indoor Environmental Quality must be considered. One aspect of IEQ is thermal comfort, which is affected by the mean radiant temperature, t r. This variable is the only one that an HVAC system cannot control directly. In fact, it depends on the temperatures of the surfaces surrounding the subject which are influenced by the air temperature. It can be calculated using the methods envisaged by the ISO EN 7726 standard or alternative approximate methods. It is therefore important to understand whether the differentt r calculation methods affect the PMV value and, therefore, the classification of the thermal environment according to the EN 16798-1 Standard. For many years, building dynamic energy simulation software tools which integrate energy analyses with the evaluation of thermal comfort have been used for the design and verification of the energy performance of buildings. This paper compares different methods of calculating the mean radiant temperature used by Energy Plus with the Design-Builder interface and analyses the influence of the results on the evaluation of thermal comfort in three buildings. • The evaluation of t r by building simulation software can exhibit high errors. • Windows, climate, and subject position affect the reliability of simplified methods. • Zone Averaged method is effective only at the centre of the room. • Surface Weighted method exhibits lower errors near windows. • Simplified methods exhibit high uncertainties in thermal comfort assessment. [ABSTRACT FROM AUTHOR]

Abstract: Building energy computer simulation software is a useful tool for achieving sophisticated design and evaluation of the thermal performance of buildings. For successful thermal and energy simulation of buildings, it requires hourly weather data such as dry bulb air temperature, relative humidity, solar radiation, wind speed, etc. Nowadays, an urban city faces a problem of an urban heat island which causes the urban area to have a higher air temperature than the rural region. Since the currently available weather dataset used in building simulation software mainly comes from weather stations located in remote and rural areas, the impact of the urban heat island on thermal and energy performance of buildings may not be effectively reflected. This paper reports an approach to construct a modified typical meteorological weather file, taking into account the urban heat island effect in the summer season. Field measurements have been carried out in the summer months and the corresponding urban heat island intensities were then determined. With a morphing algorithm, an existing typical meteorological year weather file was modified. An office building and a typical residential flat were modeled with a renowned building energy simulation program EnergyPlus. Computer simulations were conducted using the existing and modified typical meteorological year weather files. It was found that there was around a 10% increase in air-conditioning demand caused by the urban heat island effect in both cases. The implications of this and further work will also be discussed in this paper. [Copyright &y& Elsevier]

Sao Paulo city has one of the world's largest metropolitan areas, with more than 300 high-rise and high standard office buildings. Most of those constructions adopt the ‘International Style’ pattern for the facade solution, with high single glazed window-to-wall ratios. This paper presents a discussion about energy performance of envelope solutions of high-rise office buildings in Sao Paulo city, through a data assembling of 40 LEED certified office buildings and a thermal and energy performance analysis. Parameters identified as being mainly responsible for building energy performance were raised, based on results of computer simulation in EnergyPlus. As a result, guidelines for envelope design with suggested ranges for each selected parameter were presented, considering thermal performance characteristics and energy savings potential. [ABSTRACT FROM AUTHOR]

This investigation presents an estimation of the energy performance of an office building which is equipped with a heat pump system. The paper presents the simulation methodology of a multi-zone office building for temperate climate conditions of Belgrade city. Our baseline model was developed according to the guidelines of designing office spaces, accessories and communication. The parameters of the building envelope, heat pump system and indoor environmental criteria were mandatory elements of the simulation. The medium office building model is constructed according to the Serbian energy efficiency regulation, Official gazette RS no. 61/2011. The EnergyPlus simulation results outline the importance of applying simulation techniques in energy performance assessment for qualitative decision-making. Findings highlight the office building's energy performance equipped with an air-to-air heat pump system, with and without heat recovery equipment. [ABSTRACT FROM AUTHOR]

To facilitate an increase in comfortable and healthy indoor environments, a lot of people have researched and conducted studies related to this field. However, it has proven difficult to find optimal indoor conditions because each of the elements that make up the thermal environment has different properties. Natural ventilation is an important factor in meeting and creating the thermal environment as well as improved indoor air quality. Moreover, the continuation of efforts to reduce energy consumption in buildings is also required from the design stage due to the depletion of energy resource and global warming. Therefore, this study aims to provide a material of natural ventilation for educational facilities by calculating the energy consumption of a classroom in accordance with indoor temperature distributions in summer. A target educational facility with classrooms was selected in Seoul, Republic of Korea. This study assumed that the classroom windows were fully opened and were then analyzed for indoor temperature distributions and energy consumption according to natural ventilation. In addition, the simulation was conducted based on the actual daily schedule in the school. The results were achieved by utilizing the Computer fluid dynamics simulation and Building energy simulation. This paper will be the basis of research related to occupant behavior and patterns indoors. [ABSTRACT FROM AUTHOR]

In this paper, in order to accurately simulate building thermal performance, a coupling strategy between the hourly Computational Fluid Dynamics (CFD) simulation of the indoor airflow in a room and the dynamic Building Energy Simulation (BES) of the heat transfer through its envelope based on real-time information exchange is developed, and the radiation heat transfer among the internal surfaces of its envelope is also calculated. The governing equations are solved by Finite Element Method (FEM). Then, the developed program is applied to co-simulate an office room with a ventilating and radiant floor cooling system. The results show that the dynamic heat transfer characteristics of the external wall and the indoor air in the room change with outside weather conditions in detail. [ABSTRACT FROM AUTHOR]

• A brief historical overview of micro and urban climate CFD modelling is provided. • Three major limitations and challenges of the current CFD models is discussed. • Mesh generation should be optimized in respect to many aspects of urban climate. • Connections between cities' bigdata and CFD model inputs is a challenging topic. • Oversimplification can results in a significant departure from the reality. Despite the popularity of the micro/urban climate CFD modeling as a powerful approach to simulate convective exchanges in urban areas, yet its application faces three profound limitations, including (1) computational barriers, (2) data acquisition, and (3) over-simplifications of underlying physics. Computational resources are not qualitatively studied to be allocated to their best of performance in urban climate models. Moreover, bigdata of city components and inhabitants are sometimes inaccessible or difficult to be effectively interpreted to be fed into CFD models. Furthermore, commonly adopted oversimplifications, and misinterpretation of underlying physics of urban climate can substantially render falsified results, no matter if they look otherwise followed by extravagant visual reports. This paper, hence, aims to explore the capabilities and limitations of urban climate CFD modeling. It further scrutinizes the common oversimplifications in the modeling techniques, potentially resulting in CFD capacities to be lost in the translation. The paper describes the extend to which CFD tools can be the favourable options and otherwise, while it underpins the areas in which further research is needed to conform urban climate CFD models as practical design and decision-making tools. It also offers a brief overview in the recent advancements in response to the mentioned challenges. [ABSTRACT FROM AUTHOR]

With respect to the growing requirements on energy performance of buildings, sundry ways how to improve thermal performance of buildings are being searched. One of the ideas is to use some kind of additional “second skin” to create such an environment which would ensure better external boundary conditions and thus improve energy balance of the very house. This paper deals with a case study of a test house which is exposed to the impact of a glasshouse, in which is situated, compared to the situation when no additional skin is used and normal ambient environment affects the house. The aim of the glasshouse is to improve energy performance of the house in winter period. The skin is of such a distance from the house to create extended living space around the house for habitants. Potential contribution of the second skin on the thermal balance of the house is analysed for the climate of the Czech Republic for various scenarios. A simple lumped parameter thermal model (first order model) is used for dynamic simulations with hourly time step. Based on known simplifications of the model, suitability of its application to such kind of issue is also discussed. [ABSTRACT FROM AUTHOR]

Energy use in residential and commercial buildings and towers represents more than 30% of energy consumption. The increase in number of buildings and towers in most of the major cities worldwide led to several initiatives for energy conservation programs with the main objective to achieve energy savings. Most energy strategies include energy conservation beside the increase in the penetration of renewable energy technologies. This paper shows business model and engineering design framework for practical implementation of energy conservation in buildings. Key performance indicators are modeled and used to evaluate energy conservation strategies and energy supply scenarios as part of the design and operation of building energy systems. The proposed system approach shows effective management of building energy knowledge on the basis of Energy Semantic Networks (ESN), which supports the simulation, evaluation, and optimization of several building energy conservation scenarios. Case study hotel is used to illustrate the proposed building energy conservation framework. [ABSTRACT FROM AUTHOR]

• A novel EPC related holistic building retrofit approach was proposed in this paper. • Principles applied "Fabric priority", "Renewable in supplement", "Avoid complex installation". • A novel energy limiting difference (ELD) is proposed as an assessment factor. • 11 energy retrofit measures were defined and grouped into 18 combination packages. • This holistic approach facilitates the rapid retrofit design and decision-making process. This paper presents a novel Energy Performance Certification (EPC) related holistic building retrofit approach for a Norwegian apartment block built in 1980s. Based on the pre-combination principles of "Fabric priority", "Renewable in supplement", "Avoid complicated installation", 11 energy retrofit measures (ERMs) were defined and combined into 18 typical retrofit combination packages (COMBs). Targeted simulations with the aim to explore the interconnected and coupled impacts of selected ERMs are performed in a dynamic simulation tool IES Virtual Environment (VE). A novel Energy Limiting Difference (ELD) assessment factor has been defined, which only considers the difference between primary and renewable energy consumption in the extreme cold winter and hot summer months. The post retrofit EPC standard for each COMBs are then linked with these ELD assessment factors respectively. The relationship between ELD assessment factors and the relevant EPC grades for the 18 COMBs is plotted and verified against the obtained EPC results. Without performing the simulation for each month in conventional retrofit approaches, this approach leads to at least 78 % reduced simulation efforts. This ELD-EPC related approach could therefore be used as useful guidelines for similar apartment building retrofits incorporating renewable energy measures in high-density areas in the cold climate region. [ABSTRACT FROM AUTHOR]

It is of great energy-saving significance to provide accurate occupancy schedules for building energy simulation. Inaccurate occupancy information can lead to biased results. However, the reference occupancy schedules provided by the standard documents are fixed and differ significantly from the actual occupancy fluctuations. Moreover, the large amount of accurate occupancy information is difficult and expensive to obtain, limiting the development of occupancy fluctuation pattern exploration and occupancy prediction. In this paper, a framework is proposed to provide accurate and flexible occupancy schedules based on occupancy-related variables and occupancy information extracted from surveillance videos through Convolutional Neural Network-based density estimation methods. Machine learning algorithms are used in the framework to predict occupancy owing to their powerful predictive capabilities. A case study based on educational buildings is conducted to examine the performance of the framework and to compare its predicted occupancy schedules with those provided by national standard documents. The average recognition accuracy of the proposed framework for different crowd densities is as high as 95.67%, and the mean absolute percentage error for the prediction of the occupancy by the proposed framework is only 16.88%. The average deviation degree between the predicted occupancy rate schedules and the actual occupancy rate schedules is reduced from 676.08% to 23.19%. The average deviation degree of building energy simulation results caused by the occupancy rate schedule is reduced from 42.56% to 0.93%. These results provide conclusive evidence that the proposed framework can provide realistic and flexible occupancy schedules to improve the accuracy of building energy simulation. • A framework for crowd counting and prediction in public buildings with high-density scenes. • Occupancy information obtained from images by CNN-based density estimation methods. • Average recognition accuracy of 95.67% for different crowd densities. • Average all-day prediction accuracy of 83.12% for occupancy of the target building. [ABSTRACT FROM AUTHOR]

Building energy simulation (BES) tools are fundamental for predicting energy performance and comfort. However, detailed models are computationally complex and demand high simulation times. These lead to difficulties in parametric runs and numerical optimizations. Performing numerous retrofit scenarios is hardly feasible, especially in multi-zone buildings with complex geometries. This paper introduces a novel approach to model order reduction (MOR) of BES models. The approach utilizes a deep learning-based unsupervised convolutional neural network autoencoder (CNN-AE). The method decomposes complex time series data derived from detailed simulations into lower dimension features. The low-dimension representations can be grouped through clustering algorithms to build a reduced-order model (ROM). The approach in this study automatically finds archetype zones of the original model that represent the energy behavior of a group of rooms, and removes redundant ones. The energy demand of the whole building can be estimated through these archetype zones. Our investigation shows that CNN-AE can be efficiently applied to reduce complex building energy simulation models. As proof of concept, a detailed model of a multi-zone campus building with 889 thermal zones is compared to the ROM derived from the CNN-AE. Comprehensive autoencoder hyperparameter training to optimize the accuracy of the model is provided. The ROM supports different purposes, such as energy scenario developments, with a total error of less than 1% compared to the original model, and reduced simulation times by a factor of more than 16. • A novel approach to MOR for BEM through convolutional neural network autoencoders • The proposed autoencoder outperforms conventional feature extraction methods • The autoencoder performance is dependent on hyperparameters and parameters selected • Results of hyperparameter optimization of the network are provided • The autoencoder based ROM shows high accuracies and reduced simulation times [ABSTRACT FROM AUTHOR]

Abstract: An energy model generated during the design phase of a building could - in principal - be converted into a calibrated energy model and used to improve the building’s operational performance. However, this rarely happens in practice. Through a survey of 306 building professionals, this research investigates whether this model reuse is technically feasible, based on today’s design-phase models, and what non-technical barriers might stand in the way of its implementation. An important finding is that 75% of the engineers/energy modelers surveyed believed that their models could be used by a third party in building commissioning and operation. At the same time, many modelers voiced various reservations that might prevent them from sharing their energy models with the owner or design team. These reservations varied from a desire to protect their intellectual property, to liability concerns, to the fear of incurring additional unpaid work. In response to these findings, this paper provides suggestions for overcoming these non-technical challenges and includes references for contract precedents. [Copyright &y& Elsevier]

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Abstract: The paper discusses methods of selecting typical weather data and describes the selection of test reference years (TRYs) for Subang, Malaysia. The TRYs were selected using the Finkelstein–Schafer statistic, from 19 years of meteorological data recorded during the period 1980-98. Changing the weighting of the various meteorological variables (dry bulb temperature, solar radiation, relative humidity and wind speed) in the range appropriate for building performance studies had little effect on the selection, so it is recommended that equal weightings should be used unless there are particular reasons for using some other weighting. The replacement of relative humidity by moisture content had little effect on the selection. [Copyright &y& Elsevier]

Abstract: Empirical validation of building energy simulation codes is an important component in understanding the capacity and limitations of the software. Within the framework of Task 34/Annex 43 of the International Energy Agency (IEA), a series of experiments was performed in an outdoor test cell. The objective of these experiments was to provide a high-quality data set for code developers and modelers to validate their solar gain models for windows with and without shading devices. A description of the necessary specifications for modeling these experiments is provided in this paper, which includes information about the test site location, experimental setup, geometrical and thermophysical cell properties including estimated uncertainties. Computed overall thermal cell properties were confirmed by conducting a steady-state experiment without solar gains. A transient experiment, also without solar gains, and corresponding simulations from four different building energy simulation codes showed that the provided specifications result in accurate thermal cell modeling. A good foundation for the following experiments with solar gains was therefore accomplished. [Copyright &y& Elsevier]

Abstract: Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today''s building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt''s approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened. [Copyright &y& Elsevier]

• A novel framework is proposed to couple CFD and building energy models. • The method includes two different resolution meshes of CFD f and CFD c. • Off-line CFD f provides flow information for CFD c which participates in the coupling. • About 200 times faster convergence is achieved using the proposed coupling method. Building energy simulation (BES) tools show limitations in calculations of the convective heat transfer exchange with the surrounding urban areas. Therefore, dynamic coupling of BES to computational fluid dynamics (CFD) techniques is a common strategy to improve the simulation performance. Nonetheless, dynamic coupling itself is understood to be computationally intensive and unaffordable even in simplistic neighbourhood-scale scenarios. This paper proposes a novel framework for integration of a high-resolution CFD model (CFD f) into a coupled model of low-resolution CFD (CFD c) and BES. In specific, the CFD f model (fine grids) operates as the off-line component in the whole procedure that provides the boundary conditions, including the flow patterns, to CFD c (coarse grids) at the openings in the form of the mass flow information to BES to start the iterative process. After that, CFD c and BES domains execute a fully dynamic external coupling to deliver an accurate energy simulation. A case study is designed for a simple neighbourhood on a typical hot day for sheltered buildings with night-purge cooling. The results highlight in a significant improvement in results with representing neighbourhood effect and in a substantial reduction of computation cost of the dynamic coupling procedure. [ABSTRACT FROM AUTHOR]

Given that human behavior is increasingly recognized to play an essential role in building energy use, the validity of occupant-related assumptions in the building code and in the energy performance modeling tools used for demonstrating code compliance is a central concern. This paper investigates the current occupant-related assumptions in the National Building Code (NBC) of Canada compared to new and emerging data sources, along with their potential energy and design impacts. Six parameters were selected: setpoint temperatures, domestic hot water (DHW) use, appliances lighting and plug (ALP) loads, internal heat gains, mechanical ventilation, and the number of occupants. For each parameter, available data sources were compared against the NBC assumptions. Our analysis indicates that several code assumptions are substantially different from findings in recent measurement-based studies. For the temperature setpoints, the mean heating and cooling setpoints are approximately 1.5 °C cooler than the current NBC specification (21 °C and 25 °C, respectively). For DHW, the total daily volume is highly dependent on the number of occupants; hence, the current assumption of NBC (225 L/day) may not reflect the typical current use. Moreover, the hourly schedule for DHW use specified by NBC is significantly different than all data sources found (primarily in the timing and magnitude of morning and evening peaks in usage). For internal heat gains, the available data suggests a similar profile as NBC, except for that absence of a morning peak. Therefore, the findings presented in this study illustrate a need for revising the current building standards/codes. • A comprehensive review of new and emerging occupant-related data in Canada. • Occupant-related assumptions in NBC varies from the new available datasets. • Thermostat data from over 13,000 homes across Canada were analyzed. • The total daily volume of DHW use is highly dependent on the number of occupants. • A daily ALP loads profile from multiple sources was developed. [ABSTRACT FROM AUTHOR]