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The operational phase of a building's lifecycle is receiving increasing attention, as it consumes an enormous amount of energy and results in tremendous detrimental impacts on the environment. While energy simulation can be applied as a tool to evaluate the energy performance of a building in operation, the emergence of Building Information Modeling (BIM) technology is expected to facilitate the evaluation process with predefined and enriched building information. However, such an approach has been confronted by the challenge of interoperability issues among the related application software, including the BIM tools and energy simulation tools, and the results of simulation have been seldom verified due to the unavailability of corresponding experimental data. This study aims to explore the interoperability between the commonly used energy simulation and BIM tools and verifies the simulation approach by undertaking a case study.

With Autodesk Revit and EnergyPlus selected as the commonly used BIM and energy simulation tools, respectively, a valid technical framework of transferring building information between two tools is proposed, and the interoperability issues that occur during the data transfer are studied. The proposed framework is then employed to simulate the energy consumption of a single-family house, and sensitivity analysis and analysis on such parameters as schedule are conducted for building operations to showcase its applicability.

The simulation results are compared with monitored data and the results from another simulation tool, HOT2000; the comparison reveals that EnergyPlus and HOT2000 predict the total energy consumption with a difference from the monitoring data of 8.0 and 7.1%, respectively.

This research shows how to efficiently use BIM to support building energy simulation. Relevant stakeholders can learn from this research to avoid data loss during BIM model transformation.

This research explores the application of BIM for building energy simulation, compares the simulation results among different tools and validates simulation results using monitored data.

The purpose of this research is to test the effectiveness of integrating Grasshopper 3D and measuring attractiveness by a categorical based evaluation technique (M-MACBETH) for building energy simulation analysis within a virtual environment. Set of energy retrofitting solutions is evaluated against performance-based criteria (energy consumption, weight and carbon footprint), and considering the preservation of the cultural value of the building, its architectural and spatial configuration.

This research addresses the building energy performance analysis before and after the design of retrofitting solutions in extreme climate environments (2030–2100). The proposed model integrates data obtained from an advanced parametric tool (Grasshopper) and a multi-criteria decision analysis (M-MACBETH) to score different energy retrofitting solutions against energy consumption, weight, carbon footprint and impact on architectural configuration. The proposed model is tested for predicting the performance of a traditional timber-framed dwelling in a historic parish in Lisbon. The performance of distinct solutions is compared in digitally simulated climate conditions (design scenarios) considering different criteria weights.

This study shows the importance of conducting building energy simulation linking physical and digital environments and then, identifying a set of evaluation criteria in the analysed context. Architects, environmental engineers and urban planners should use computational environment in the development design phase to identify design solutions and compare their expected impact on the building configuration and performance-based behaviour.

The unavailability of local weather data (EnergyPlus Weather File (EPW) file), the high time-resource effort, and the number/type of the energy retrofit measures tested in this research limit the scope of this study. In energy simulation procedures, the baseline generally covers a period of thirty, ten or five years. In this research, due to the fact that weather data is unavailable in the format required in the simulation process (.EPW file), the input data in the baseline is the average climatic data from EnergyPlus (2022). Additionally, this workflow is time-consuming due to the low interoperability of the software. Grasshopper requires a high-skilled analyst to obtain accurate results. To calculate the values for the energy consumption, i.e. the values of energy per day of simulation, all the values given per hour are manually summed. The values of weight are obtained by calculating the amount of material required (whose dimensions are provided by Grasshopper), while the amount of carbon footprint is calculated per kg of material. Then this set of data is introduced into M-MACBETH. Another relevant limitation is related to the techniques proposed for retrofitting this case study, all based on wood-fibre boards.

The proposed method for energy simulation and climate change adaptation can be applied to other historic buildings considering different evaluation criteria and context-based priorities.

Context-based adaptation measures of the built environment are necessary for the coming years due to the projected extreme temperature changes following the 2015 Paris Agreement and the 2030 Agenda. Built environments include historical sites that represent irreplaceable cultural legacies and factors of the community's identity to be preserved over time.

This study shows the importance of conducting building energy simulation using physical and digital environments. Computational environment should be used during the development design phase by architects, engineers and urban planners to rank design solutions against a set of performance criteria and compare the expected impact on the building configuration and performance-based behaviour. This study integrates Grasshopper 3D and M-MACBETH.

This study investigates the impact and economic viability of energy-efficient building envelope and orientation for contributing net zero energy building (NZEB) and suggests optimum thermal insulation thickness, optimum wall thickness, appropriate orientation and glazing types of window in the contexts of unique Bangladeshi subtropical monsoon climate.

The whole study was conducted through energy simulation perspective of an existing office building using building information modeling (BIM) and building energy modeling (BEM) tools which are Autodesk Revit 2017, Autodesk Green Building Studio (GBS) and eQUEST. Numerous simulation patterns were created for energy simulation considering building envelope parameters and orientations. A comprehensive data analysis of simulation results was conducted to sort out efficient passive design strategies.

The optimum thermal mass and thermal insulation thickness are 6.5 and 0.5 inches, respectively, considering energy performance and economic viability. This study highly recommends that a building should be designed with a small window-to-wall ratio in the south and west face. The window should be constructed with double glazing Low-E materials to reduce solar heat gain. The studied building saves 9.14% annual energy consumption by incorporating the suggested passive design strategies of this study.

The output of this work can add some new energy-efficient design strategies to Bangladesh National Building Code (BNBC) because BNBC has not suggested any codes or regulations regarding energy-efficient passive design strategies. It will also be useful to designers of Bangladesh and other countries with similar subtropical climatic contexts which are located in Southeast Asia and Northern Hemisphere of Earth.

Design teams have difficulties in assessing building carbon emissions at an early stage, as most building energy simulation tools require a detailed input of building design for estimation. The purpose of this paper is to develop a user-friendly regression model to estimate carbon emissions of the preliminary design of office buildings in the subtropics by way of example. Five sets of building design parameters, including building configuration, building envelope, design space conditions, building system configuration and occupant behaviour, are considered in this study.

Both EnergyPlus and Monte Carlo simulation were used to predict carbon emissions for different combinations of the design parameters. A total of 100,000 simulations were conducted to ensure a full range of simulation results. Based on the simulation results, a regression model was developed to estimate carbon emissions of office buildings based on preliminary design information.

The results show that occupant density, annual mean occupancy rate, equipment load, lighting load and chiller coefficient of performance are the top five influential parameters affecting building carbon emissions under the subtropics. Besides, the design parameters of ten office buildings were input into this user-friendly regression model for validation. The results show that the ranking of its simulated carbon emissions for these ten buildings is consistent with the original carbon emissions ranking.

With the use of this developed regression model, design teams can not only have a simple and quick estimation of carbon emissions based on the building design information at the conceptual stage but also explore design options by understanding the level of reduction in carbon emissions if a certain building design parameter is changed. The study also provides recommendations on building design to reduce carbon emissions of office buildings.

Limited research has been conducted to date to investigate how the change of building design affects carbon emissions in the subtropics where four distinct seasons lead to significant variations of outdoor temperature and relative humidity. Previous research also did not emphasise on the impact of high-rise office building designs (e.g. small building footprint, high window-to-wall ratio) on carbon emissions. This paper adds value by identifying the influential parameters affecting carbon emissions for a high-rise office building design and allows a handy estimate of building carbon emissions under the subtropical conditions. The same approach may be used for other meteorological conditions.

Application of appropriate shading device strategies in buildings can reduce direct solar heat gain through windows as well as optimize cooling and artificial lighting load. This study investigates the impact of common shading devices such as overhangs, fins, horizontal blinds, vertical blinds and drapes on energy consumption of an office building and suggests energy efficient shading device strategies in the contexts of unique Bangladeshi subtropical monsoon climate.

This research was performed through the energy simulation perspective of a prototype office building using a validated building energy simulation tool eQUEST. Around 100 simulation patterns were created considering various types of shading devices and building orientations. The simulation results were analysed comprehensively to find out energy-efficient shading device strategies.

Optimum overhang and fin height is equal to half of the window height in the context of the subtropical climate of Bangladesh. South and West are the most vulnerable orientations, and application of shading devices on these two orientations shows the highest reduction of cooling load and the lowest increment of lighting load. An existing building was able to save approximately 7.05% annual energy consumption by applying the shading device strategies that were suggested by this study.

The shading device strategies of this study can be incorporated into the Bangladesh National Building Code (BNBC) as new energy-efficient building design strategies because the BNBC does not have any codes or regulations regarding energy-efficient shading device. It can also be used as energy-efficient shading device strategies to other Southeast Asian countries with similar climatic contexts of Bangladesh.

The purpose of this paper is to examine the feasibility and design of zero-energy buildings (ZEBs) in cold and semi-arid climates. In this study, to maximize the use of renewable energy, energy consumption is diminished using passive solar architecture systems and techniques.

The case study is a residential building with a floor area of 100 m² and four inhabitants in the cold and semi-arid climate, northeast of Iran. For thermal simulation, the climate data such as air temperature, sunshine hours, wind, precipitation and hourly sunlight, are provided from the meteorological station and weather databases of the region. DesignBuilder software is applied for simulation and dynamic analysis of the building, as well as PVsyst software to design and evaluate renewable energy performance.

The simulation results show a 30% decrease in annual energy consumption of the building by complying with the principles of passive design (optimal selection of direction, Trombe wall, shade, proper insulation selection) from 25,443 kWh to 17,767 kWh. Then, the solar energy photovoltaic (PV) system is designed using PVsyst software, taking into account the annual energy requirement and the system’s annual energy yield is estimated to be 26,291 kWh.

The adaptive comparison of the values obtained from the energy analysis indicated that constructing a ZEB is feasible in cold and semi-arid conditions and is considered an effective step to achieve sustainable and environmentally friendly construction.

This paper reports on the experimentation of an integrated manufacturing and building model to improve energy efficiency. Traditionally, manufacturing and building-facilities engineers work independently, with their own performance objectives, methods and software support. However, with progresses in resource reduction, advances have become more challenging. Further opportunities for energy efficiency require an expansion of scope across the functional boundaries of facility, utility and manufacturing assets.

The design of methods that provide guidance on factory modelling is inductive. The literature review outlines techniques for the simulation of energy efficiency in manufacturing, utility and facility assets. It demonstrates that detailed guidance for modelling across these domains is sparse. Therefore, five experiments are undertaken in an integrated manufacturing, utility and facility simulation software IES < VE > . These evaluate the impact of time-step granularity on the modelling of a paint shop process.

Experimentation demonstrates that time-step granularity can have a significant impact on simulation model results quality. Linear deterioration in results can be assumed from time intervals of 10 minutes and beyond. Therefore, an appropriate logging interval, and time-step granularity should be chosen during the data composition process. Time-step granularity is vital factor in the modelling process, impacting the quality of simulation results produced.

This work supports progress towards sustainable factories by understanding the impact of time-step granularity on data composition, modelling, and on the quality of simulation results. Better understanding of this granularity factor will guide engineers to use an appropriate level of data and understand the impact of the choices they are making.

This paper reports on the use of simulation modelling tool that links manufacturing, utilities and facilities domains, enabling their joint analysis to reduce factory resource consumption. Currently, there are few available tools to link these areas together; hence, there is little or no understanding of how such combined factory analysis should be conducted to assess and reduce factory resource consumption.

In many countries, innovation in building design for improving energy performance, reducing CO2 emissions and minimizing life cycle cost has received much attention for sustainable development. This paper investigates the importance of optimization tools for enhancing the design performance in the early stages of Vietnam's cooling-dominated buildings in hot and humid climates using an integrated building design approach.

The methodology of this study exploits the non-dominated sorting genetic algorithm (NSGA-II) optimization algorithm coupled with building simulation to research a trade-off between the optimization of investment cost and energy consumption. Our approach focuses on the whole optimization problem of thermal envelope, glazing and energy systems from preliminary design phases. The methodology is then tested for a case study of a non-residential building located in Hanoi.

The results show a considerable improvement in design performance by our method compared to current building design. The optimal solutions present the trade-off between energy consumption and capital cost in the form of a Pareto front. This helps architects, engineers and investors make important decisions in the early design stages with a large view of impacts of all factors on energy performance and cost.

This is one of the original research to study integrated building design applying the simulation-based genetic optimization algorithm for cooling-dominated buildings in Vietnam. The case study in this article is for a non-residential building in the north of Vietnam but the methodology can also be applied to residential buildings and other regions.

The paper aims to clarify the relationship between energy flexibility and building components and technologies. It determines the energy flexibility potential of buildings in relation to their physical characteristics and heat supply systems with respect to external boundary conditions.

The emphasis of the evaluation is based on the timing and the amount of shiftable and storable thermal loads in buildings under defined indoor thermal comfort conditions. Dynamic building simulation is used to evaluate the potential of selected building characteristics to shift heating loads away from peak demand periods. Insights on the energy flexibility potential of individual technologies are gained by examining the thermal behaviour of single-zone simulation models as different input parameters are varied. For this purpose, parameters such as envelope qualities, construction materials, control systems for heating are modified.

The paper provides a comprehensive understanding of the influence of the different building parameters and their variations on their energy shifting potential under “laboratory conditions” with steady boundaries. It suggests that the investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the heating load of a building, also influence the resulting potential for energy flexibility. The findings show that the combination of a slowly reacting heat transfer system, such as concrete core activation and a readily available storage mass in the room, and a high insulation standard proved to have a high potential to shift heating loads.

In this paper, energy-flexible components were evaluated in a steady-state simulation approach. Outside temperature, solar irradiation and internal loads over the simulation duration were set constant over time to provide laboratory conditions for the potential analysis. On the basis of both duration and performance of the load shifting or storage event, the components were then quantified in a parametric simulation. The determined energy flexibility is directly related to the power of the heating, cooling, hot water and ventilation system, which can be switched on or off. In general, it can be seen that high power (high loads) demand usually can be switched on and off for a short duration, and low power demand usually for a longer duration. The investigated boundary conditions such as outside temperature, infiltration, envelope quality and user behaviour, which influence the load of a building, also influence the resulting potential for energy flexibility. Higher insulation standards, for example, lead to lower loads that can be switched on or off, but increase the duration of the event (flexibility time). So that, in particular, the shiftable load potential is low but results in a long switch-off duration. Furthermore, passive storage potential in buildings like the storage mass inside the room and the type of heat/cooling transfer system can affect the flexibility potential by more than three times. Especially the combination of a high storage mass and a concrete core heat transfer system can significantly increase the flexibility.

The purpose of this study is to examine the energy savings in the indoor environment, using strategies that adopt the characteristics of nature, called biomimetic solutions. This research designed a biomimetic window system to bring daylight into interior spaces in educational buildings where daylight cannot be reached. Specifically, this study assessed how the daylight that was achieved via a biomimetic window system would affect energy savings using an energy simulation method.

This study explored how biomimetic methods would affect the building environment and which biomimetic method would involve the building's energy saving with daylight. The research intended to develop a novel biomimetic window system that can bring daylight to the basement floor of an existing building on a university campus to find out how much the biomimetic window system would affect the energy savings of the building. Referring to the existing building's layout and structure, energy simulation models were developed, and the energy consumptions were estimated.

Simulation models proved that the biomimetic window system has sufficient performance to bring more daylight to the basement floor of the building. Furthermore, it was confirmed that the use of the biomimetic window system for the building could reduce energy usage compared to the actual energy usage of the current building without biomimetic windows.

First, this study was adopted as a computer-designed simulation method instead of using a real-world system. Although this study designed the biomimetic window system based on previous studies, it should be considered the possibility of other problems when the system is actually built in. Second, it is necessary to predict how much an initial budget is required when the system is built. It means that this study did not calculate the lifecycle cost of the biomimetic window system. It will also be necessary to compare energy consumption to the required initial budget. Lastly, this study was simulated based on weather data in cold regions, and it did not compare/analyze different climate regions. Different results may be predicted if the biomimetic window system is built in different climatic regions.

This research showed new practical ways to capture and transmit solar heat and light using a biomimetic solution. Furthermore, using the proposed novel biomimetic window system, the amount of energy reduction can be calculated, and this method could be applied in the interior non-window spaces of academic and related types of buildings.