BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies
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Department of Industrial and Information Engineering and Economics, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy
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Department of Civil, Construction-Architectural and Environmental Engineering, University of L’Aquila, Piazzale Pontieri 1, Monteluco di Roio, 67100 L’Aquila, Italy
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Author to whom correspondence should be addressed.
Energies 2023, 16(23), 7845; https://doi.org/10.3390/en16237845
Submission received: 3 November 2023
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Revised: 24 November 2023
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Accepted: 28 November 2023
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Published: 29 November 2023
(This article belongs to the Section G: Energy and Buildings)
Abstract
:The main objective of this review is to summarize and thoroughly investigate the most popular and promising BIM (building information modeling) and BEM (building energy modeling) interoperability strategies employed in the last years (2004–2023), highlighting pros and cons of each strategy and trying to understand the reason for the still limited BIM–BEM interaction. This review summarizes the main countries, areas, modeling tools, and interoperability strategies, with the advantages and disadvantages of each one. The methodology is based on the PRISMA protocol, and two databases were used for the research: Scopus and Google Scholar. A total of 532 publications were selected and 100 papers were deemed useful for the purposes of this review. The main findings led to the identification of four different interoperability strategies between BIM and BEM tools: (1) real-time connection; (2) standardized exchange formats and middleware corrective tools; (3) adherence to model view definitions; (4) proprietary tool-chain. These strategies were found to be characterized by different degrees of complexity, time required for information exchange, proprietary or opensource software, ability to reduce information loss, and detailed energy results. The results of this study showed that, to date, there is no better interoperability strategy, and that further efforts are needed so that interoperability between the two tools can become commonplace.
1. Introduction
In March 2023, the European Parliament approved the “Green Homes Directive”, which, among other provisions, stipulates that all new buildings must be carbon neutral starting from 2028 [1]. Consequently, the way buildings are currently designed needs to be reviewed, not only by testing the application of new ecological building materials [2,3] but also by providing for the use of innovative technologies capable of including the energy efficiency issue as early as the project’s preliminary phase. The challenge of designing a high energy performance building requires the creation of a shared working environment where the architectural and energy spheres can communicate easily and exchange information expeditiously. In the past two decades, building information modeling (BIM) has established itself as a tool with the potential to revolutionize the construction industry [4]. In fact, due to the growing complexity of buildings, managing construction projects is becoming increasingly challenging [5]. In this context, BIM, as a multifunctional method, can assist the entire building design process, contributing to the realization of green buildings [6]. The potential of BIM lies in its faithful and detailed digital reproduction of the architectural features of a building.
However, BIM only allows for preliminary qualitative assessments, not allowing for in-depth analysis for building energy design. To date, BIM can be employed for qualitative solar studies [7]. In fact, the software contains a detailed solar path analysis module that assists designers in optimizing the building’s orientation during the early stages of a project [7]. However, the functionality of BIM in the energy field is still very limited. Although BIM may dynamically contain thermal and physical information of the various building components, it is not able to perform an in-depth analysis of the building’s energy performance and outline optimization scenarios. Consequentially, the capabilities of BIM should be implemented by those offered by BEM software, developed specifically for conducting energy simulations.
For this reason, increasing efforts to research techniques for integrating BIM and BEM into a single simulation tool are needed, to find a comprehensive software capable of calculating the thermal loads and energy consumption of buildings [8]. The BIM–BEM combination, integrating the architectural and energy aspects of a building, could effectively enhance design choices, leading to the creation of energy-efficient and environmentally friendly structures [9]. Furthermore, the collaborative use of BIM could help to reduce design errors and increase the productivity of the construction industry [10]. Despite extensive research efforts and existing strategies to convert BIM data into analytical models readable in the BEM environment, the transformation process still tends to be prone to errors [11].
To date, BIM interoperability is a major research and development topic for the architectural engineering and construction (AEC) industry [12]. In the last decade, several review studies have been conducted on BIM and BEM, generically treating the topic of interoperability. In fact, in some cases, it does not represent the focus of the article, but is treated as one of the various functions of BIM and BEM. In other cases, although it represents the main theme of the study, it is not addressed in detail in all its facets, which also include the in-depth examination of the different export strategies [9,13,14,15,16,17,18,19,20,21,22,23,24].
Two of the aforementioned studies [9,14] mentioned the various interoperability strategies currently used by simply offering a list of them. Most of the works analyzed [13,15,16,18,21,22,23,24] provided an overview of the BIM–BEM process, discussing, in some cases [13,15,18,21,23,24], one of the various interoperability strategies in depth. In particular, the review conducted by Andriamamonjy et al. [9] was mainly scientometric. It classified the various articles into clusters, each of which dealt with an aspect of BIM. The BIM–BEPS interoperability problem was not the main topic of the review. In Alsharif’s study [14], interoperability was addressed as one of the various features of BIM, not representing the focus of the article. Farzaneh et al. [13] and Di Biccari et al. [24] conducted a bibliometric evaluation of the works considered, classifying them according to the interoperability strategy, and examining the strategy based on adherence to model view definitions in depth. The works of Bahar et al. [15], Gao et al. [21], and Gerrish et al. [23] discussed, in detail, model export methodologies based on IFC and gbXML formats. Similarly, Fernald et al. [18] reviewed the various tools used for BIM-to-BEM translation in the context of the strategy based on standardized exchange formats. The review by Pezeshki et al. [16] mainly talked about the potential of energy modeling. In the study by Senave et al. [22], attention focused more on the software used for the transition of the model from BIM to BEM rather than on the process itself. The study of Maskil-Leitan et al. [19] focused on the management of BIM–BEM communication by stakeholders, examining information exchange problems between participants in the process, rather than between the two. In the studies by Lesniak et al. [17] and Khodeir et al. [20], the authors mainly dealt with the status of the application of both BIM and BEM in their country.
Therefore, no study has adequately examined the issue of BIM–BEM interoperability summarizing and thoroughly investigating the strategies used for exporting BIM models to the BEM environment.
The main purpose of this work is to offer a review of the different BIM–BEM interoperability strategies from 2004 to 2023, highlighting their advantages, disadvantages, and future developments, through a detailed examination of case studies. For each of the interoperability strategies, the potential and limitations are discussed, showing the reasons why effective interoperability between the two modeling tools has not yet been found.
Starting with an explanation of the methodology employed, a systematic review of the selected papers is provided. In the second part of this paper, an overview of BIM and BEM applications is provided, with particular attention to the study of energy issues. Interoperability techniques between the two modeling approaches are then described in detail in Section 4. Finally, the results obtained are discussed (Section 5), comparing interoperability strategies and highlighting advantages, disadvantages, and potential future developments.
2. Research Methods and Materials
In this section, the significance of this study and the methodology employed are presented and discussed.
2.1. Significance of this Study
The significance of the proposed review study lies in the importance of facilitating the exchange of information between architectural and energy software.
Although the potential of BIM and BEM is known, the current difficulties that arise during the model export process do not allow for efficient software communication and, consequently, widespread use of the BIM-to-BEM method. Offering an in-depth analysis of the various interoperability strategies present today could help highlight the limitations of each of them and, at the same time, offer research insights for their optimization.
2.2. Methodology
The literature research was conducted following the guidelines provided by the PRISMA checklist [25], to carry out systematic, transparent, and replicable research. In detail, Table A1 of Appendix A lists all the checklist items addressed in this review.
The main research questions that this study attempted to answer are listed below:
- RQ1: What is meant by BIM–BEM interoperability?
- RQ2: How can BIM–BEM interoperability facilitate energy analyses of buildings?
- RQ3: What are the currently existing strategies for BIM–BEM interoperability?
- RQ4: What are the advantages and disadvantages of BIM–BEM interoperability strategies?
The main databases used for research are Scopus and Google Scholar, which are among the world’s leading sources for scientific research, providing researchers with access to millions of documents from journals, books, series, protocols, reference works, and proceedings.
A primary article search was conducted using search strings, based on the chosen keywords, as shown in Table 1. The Boolean operators “AND” and “OR” were employed to refine the search process. From this initial search, 532 articles were identified.
Subsequently, an initial screening was performed through the reading of titles and abstracts, based on well-defined criteria, shown in Table 2. This screening resulted in the exclusion of 438 papers, of which 10 were published in non-English language, 178 were duplicated, 183 were unavailable, and 67 were irrelevant.
The qualitative assessment of the remaining articles was performed through an in-depth reading of the full-text content. Based on this second screening, 23 other works were excluded from the analysis, as they were deemed irrelevant to the purpose of this review. Finally, an additional 29 papers deriving from a citation search were added to the 71 articles selected after various screenings.
As a result, a total of 100 publications were selected, of which 61 were from Scopus, 10 were from Google Scholar, and 29 from the citation, including original research papers, conference papers, reviews, and book chapters.
The method used for the literature search and screening process is shown in Figure 1, in order to allow users to assess the trustworthiness and applicability of this review’s findings.
Following PRISMA’s suggestion [25], tabulation was chosen to summarize the results of this study. In detail, each work was recorded, reporting the main information such as authors and their country of origin, year of publication of the paper, publisher, database used for research, keywords reported in the article, type of article, the object of the research, and main contents. The main information is summarized in Table A2 of Appendix A.
Analyzing the trend of selected publications, it is clear that, despite fluctuations over the years, the trend is growing, showing that the topic of interoperability between BIM and BEM has increasing interest in the scientific community.
The selected papers highlighted that the topic is quite widespread, with the U.S. leading the most prolific countries with 29 published papers (Figure 2).
Figure 3 shows the most used keywords in the collected articles, among which “BIM” and “Building information modeling” hold the record, followed by “BEM”, “Interoperability” and “Building Energy Modeling”. In particular, “BIM” was found in 56% of the articles, “Building Information Modeling” in 35%, “BEM” in 26%, “Interoperability” in 19%, and “Building Energy Modeling” in 10%.
3. BIM and BEM Applications: An Overview
3.1. BIM-Based Analyses for the Design of Green Buildings
According to the National Building Information Model Standard Project Committee in the United States, “BIM is a digital representation of physical and functional characteristics of a facility. A BIM is a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle; defined as existing from earliest conception to demolition” [26]. Through detailed three-dimensional modeling, it can offer an extremely precise representation of the building components, allowing the various users to fully understand all the characteristics of the project [27].
In a context in which the construction industry represents one of the sectors most responsible for global carbon emissions [28], learning how to design sustainable buildings is essential [29,30]. BIM could be the key to revolutionizing the entire construction industry, leading to a substantial reduction in its environmental impact [31,32]. In fact, this technology is able to support the designer in managing the characteristics of a building during the entire design and construction process, facilitating, for example, the prediction of the exact quantity of materials needed during the construction phase, the management of waste during the demolition phase, and the choice of energy-efficient design solutions during the design phase. Since the adoption of BIM, various efforts have been made to understand how this tool can contribute to the design of green buildings [4,33,34].
Antòn et al. [35] demonstrate that the integration and exchange of data between BIM software and lifecycle assessment (LCA) applications can bring a significant benefit in improving the environmental performance of buildings during their entire lifecycle. On the one hand, BIM is an excellent support in the design phase, helping to better manage information and data; on the other hand, the LCA is used to evaluate all the environmental impacts of the project [36]. Moreover, BIM-based models could represent the main source of information needed to conduct a comprehensive lifecycle assessment of buildings, avoiding the burden of manual data reentry [37].
In general, building lifecycle analysis requires the intervention of various professional figures, each with a specific skill. This leads to a multidisciplinary work environment that is potentially difficult to manage, with the risk of losing information by committing design errors [38]. Building information modeling, thanks to its collaborative logic, makes dialogue with other software possible, allowing professionals from various disciplines to share data and information and efficiently integrate all design aspects.
BIM is a useful support during the entire lifecycle of a building, starting from the design phase, up to the demolition/renovation phase [4,39,40], as shown in Figure 4.
The design stage of a building is crucial for making informed and environmentally sound decisions [41,42,43,44,45]. The BIM-based model enables construction stakeholders to work collaboratively for efficient project delivery, ensuring that sustainability measures are easily and effectively integrated into the entire design process [4,41,46]. The ability of BIM to exchange data and information with other software allows different professionals to work on the same project, dealing with different aspects, establishing a harmonious and multidisciplinary dialogue. The potential interoperability of BIM makes it possible to already insert energy aspects in the conceptual phase of the project, allowing for the evaluation of design alternatives that can benefit the building during its operational phase in terms of indoor comfort and energy saving [47,48]. An accurate prediction of buildings’ energy efficiency is important to minimize as much as possible their environmental impact [49,50,51,52,53,54].
Furthermore, the three-dimensional model created in the design phase is also useful for predicting the exact amount of materials to be used for construction [55], helping to reduce waste [56].
As for the operational phase, BIM could be a useful tool for controlling the indoor thermal comfort of an environment. In this context, Marzouk et al. [57] developed a wireless sensor network (WSN) integrated with a BIM model to monitor the thermal comfort of a subway. In their work, the WSN was used to measure the temperature and humidity of the air inside the subway, while the BIM model was used to visualize the recorded data.
Finally, the BIM tool can help in waste management during demolition and renovation processes. For example, Cheng et al. [58] developed a system that can extract material and volume data from the BIM environment for detailed waste estimation and planning.
3.2. BIM for Energy Analyses
The design phase is essential to ensure that the building provides high energy performance [59]. Thanks to BIM, some energy aspects can be evaluated, such as solar radiation [59,60].
In fact, BIM is equipped with a module for simulating the sun path [7], thanks to which the impact of building orientation and shading strategies, which strongly influence the energy behavior of a building [61], can be assessed during the entire year, at any time [62].
Ciccozzi et al. [63] explored the potential of Revit in the preliminary design of a photovoltaic system, analyzing shading (Figure 5) and incident solar radiation on a sample building for academic use. The purpose of the study was to identify the most suitable surfaces for installing the modules.
However, despite the enormous potential of BIM, its use for energy performance analyses is still quite limited. In fact, although BIM may contain thermal and physical information about building components, it is not able to carry out complex energy analyses. Consequently, to fill this gap, BIM-based models need to be further analyzed through specialized software, i.e., building energy modeling (BEM).
3.3. BEM for Energy Analyses
Over the last 50 years, a wide range of energy simulation programs have been developed for the analysis and prediction of buildings’ energy performance [64]. Usually, these software use simulation engines based on mathematical equations capable of representing building behavior and calculating its energy requirements [65]. Crawley et al. [64] compared the characteristics of twenty energy simulation programs in order to highlight their applicability. Among these, the authors mentioned EnergyPlus and DOE-2. EnergyPlus is a free, opensource whole-building energy simulation tool able to determine energy consumption and water use [66,67]. Since EnergyPlus is a console-based program that reads input and writes output to text files [66], it is often used with graphical interfaces, including DesignBuilder [68], Insight 360 [69] and OpenStudio [70], of which the last two can also be installed as plugins on Autodesk Revit and Sketchup [71,72], respectively. DesignBuilder is extremely intuitive, and it is widely used to carry out dynamic energy simulations on various types of buildings [73,74,75]. As for DOE-2 [76], it was developed in collaboration with the Lawrence Berkeley National Laboratory (LBNL) [77]. This software is able to predict energy consumption and costs for all types of buildings. DOE-2 also uses graphical interfaces, such as Green Building Studio (GBS) [78] and Insight 360 [69], to simplify the energy analysis process. Green Building Studio is the most appropriate software for quick output and easy comparison of multiple solutions [79].
An in-depth review analysis conducted by Pereira et al. [80] showed that the most used BEM software turned out to be EnergyPlus.
To automate the lengthy energy modeling processes, simulations based on BIM models have become increasingly frequent [81]. By using BIM-based models, modeling times are minimized [82] and, at the same time, the energy aspects of the project are perfectly integrated with the architectural features. The transfer of data from one software to another, i.e., from BIM to BEM, falls under the question of so-called interoperability, which still requires great effort for efficient strategies to be developed.
4. Results
Interoperability refers to the ability to exchange information between different software [9]. Efficient communication between modeling tools is fundamental to establishing a collaborative design environment [9]. In recent years, the interoperability between BIM and BEM tools has attracted increasing interest. The BIM-based BEM methodology uses architectural design information as input for the creation of the energy model, enabling efficient design decisions to be made after evaluating various design alternatives [21]. The purpose of this methodology is to create the energy model of the building in question starting from the architectural model, saving time in terms of modeling and better integrating energy aspects with architectural ones. However, often, the potential of BIM cannot be fully exploited due to a loss of information (both geometric and thermal data) that occurs during the export of the model [80,83]. In some cases, this data loss consists of an incorrect transfer of geometric surfaces [84], and in others, a lack of information related to the thermal properties of the walls or the HVAC system [85].
This lack of data could lead to inaccuracies in the simulation results [81]. Currently, due to the unresolved problems encountered in the process of data transfer, the interoperability between BIM and BEM is not much exploited by professionals [86]. In fact, unless the building under study is simple, substantial manual corrections are required after exporting the model from one software to another. This could make the BIM-to-BEM process excessively cumbersome and, consequently, not applicable when project delivery times are tight. However, this topic has found a lot of interest among researchers, who aim at the development of new methodologies capable of improving integration between the two software [9]. The importance of research in this field derives from the need to best integrate energy aspects with architectural ones in order to obtain efficient interaction between passive (e.g., envelope) and active (e.g., HVAC system) components of a building. In this context, it is essential to seek tools capable of managing the various aspects of a project, ensuring a dynamic response to the different variations that emerge during the design phase. To date, there are four main BIM–BEM interoperability strategies [9,14]:
- Real-time connection.
- Standardized exchange formats and middleware corrective tools.
- Adherence to Model View Definitions (MVDs).
- Proprietary tool-chain.
Below, a review of the various BIM–BEM interoperability strategies is provided, highlighting all the advantages and disadvantages of each one.
4.1. Strategy 1—Real-Time Connection
In the most recent versions of BIM software, it is possible to install plugins for energy simulation, which allow for the generation of an energy analytical model directly from the architectural model [14]. In this way, the process of exporting/importing data from one software to another would not be necessary and many errors in the model would be avoided [14]. Also, any changes made to the design would have an immediate impact on the energy analysis results [14]. This interoperability strategy allowed Maglad et al. [59] to evaluate the energy performance of a building immediately after the creation of its architectural model, obtaining significant savings in terms of modeling time. This allowed the authors to consider different design strategies in order to arrive at a more informed and efficient choice.
From a literature search, Autodesk Insight 360, which can be installed as a plugin on Revit, resulted as the most used tool for energy analyses based on the “Real-time connection” interoperability strategy [49,50,59,61,87,88,89].
In this context, in the work of Maglad et al. [59], mentioned previously, Insight 360 was used for energy optimization of a building case study, i.e., A-Block COMSATS Abbottabad (Pakistan). After detailed modeling on Autodesk Revit, the building was geolocated, taking the closest weather station to the place indicated as a reference. Based on the location, meteorological, and thermal data assigned to the various building components in the modeling phase, the energy model was generated in the form of base color codes for different components in order to be simulated using Insight (Figure 6). Basically, the software required three steps to perform the energy analysis: (1) energy model creation; (2) design options generation; (3) energy optimization results. The analysis provided energy needs and consumption of the building and various intervention strategies for its energy optimization, concerning the orientation, the window-to-wall ratio, and the lighting. More information about Autodesk Insight 360 functionalities is available on its official website [69].
Insight 360 was also used by Yarramsetty et al. [61] to analyze the impact of the building’s orientation on its energy consumption.
In a study by Boloorchi [87], a single-family home in Georgia was modeled in Revit to conduct a thorough fenestration analysis. In detail, the dimensions, position, material, and shading of the windows were studied with Insight 360 to identify the best solutions for building energy savings.
Gonzalez et al. [88], using Insight 360, ran five simulations of a hypothetical two-story single-family home, selecting five different locations. The aim was to study the energy response of the building based on the climatic conditions to which it was subjected.
Insight 360 was also used to analyze the lighting of two classrooms in a school building located in Brazil [89]. In this case, the study conducted in Revit supported the actual energy analysis of the building carried out in DesignBuilder.
To date, these BIM plugins can only provide a rough energy analysis concerning the entire building, but cannot yet provide guidance on individual thermal zones or building components. Therefore, the BIM plugins can be employed for preliminary rather than detailed energy analyses. Among other things, many operations that can be performed with the aforementioned applications are limited and cannot be customized [87].
4.2. Strategy 2—Standardized Exchange Formats and Middleware Corrective Tools
Currently, the Industry Foundation Class (IFC) and Green Building XML (gbXML) are the two most widely used standardized exchange formats for importing and exporting data from one software to another [90].
The gbXML format was tested in the work of Gourlis et al. [91] for the export of the models of two industrial plants, a partially historical plant (Case B) and a new one (Case M). On the one hand, the model of Case B was created to be exported to energy simulation software, with all the necessary geometric simplifications. On the other hand, for Case M, an existing architectural model was used for the study. In both cases, the architectural models were made in Revit and exported to OpenStudio (Sketchup plugin). The results showed that geometric errors were minimized in Case B, while substantial manual corrections in the modeling were required in Case M.
Delgado et al. [92] created the BIM-based model of a residential building in northern Portugal using a point cloud obtained with software based on structure-from-motion (SfM) algorithms starting from photogrammetry. The export to gbXML on DesignBuilder was successful and allowed for comparison between the numerical data derived from the simulation and the experimental ones obtained with monitoring.
In the work of Ham et al. [93], an automated method for assigning thermal properties to BIM building components in gbXML format was proposed. In detail, the thermal resistances of the BIM elements were updated based on the results of a thermographic survey. In this way, it was possible to conduct an energy analysis as accurately as possible.
In a study by Chen et al. [85], BIM–BEM interoperability was tested by exporting a residential building model to four different energy software (Ecotect, EQUEST, DesignBuilder, and IES-VE). The data exchange took place via the gbXML format. The results showed an inconsistency in the geometric information and an incorrectness in the HVAC parameters.
Steel et al. [94] presented their experiences in the field of software interoperability using mostly the industry standard IFC data modelling format. In most cases, models made in one IFC-compatible software are viewable in another without any difficulty. However, when the model size is too large, its display probably will not be easily supported in energy software.
In general, various studies have examined the differences between IFC and gbXML formats, the technical challenges, and the approaches used for their application [46,53,84,90,95,96].
In particular, Dong et al. [90] analyzed the differences between the two standardized exchange formats in terms of data representations, data structures, and applications. First, IFC can represent any geometric shape, while gbXML can only represent rectangular ones [97]. However, gbXML is able to transfer the environmental data and the thermal zones created on the BIM, unlike IFC [90,98].
A comparison of the two formats was also performed by Porsani et al. [84] through the modeling of two sample buildings, namely, a residence and an industrial warehouse. After creating the architectural models in Revit, the gbXML files were imported into DesignBuilder and OpenStudio, and the IFC files into CYPETHERM HE. DesignBuilder is allowed to edit the geometries, the spaces, and materials, while OpenStudio only the materials and thermal zones. The authors found that exporting the gbXML file was easier than the IFC format, even though the transfer of the industrial warehouse model was unsuccessful due to a loss of geometry data. Therefore, according to the authors, exporting models with complex geometry presents problems, such as the correct geometric surface transfer, that make energy simulation not accurate. Regarding the residential building, the simulations of the models in the two formats led to different results, which should be investigated in order to understand the motivation behind them. Figure 7 shows a comparison between the models exported in the two formats.
One of the major gaps currently present in the exchange process using standardized formats, both with IFC and gbXML formats, is the data loss that occurs once the model is imported into the analytical software [99].
With middleware tools, IFC and gbXML files can be enriched by implementing much missing information [9,14]. A literature search revealed several studies on the development of middleware corrective tools to improve communication between BIM and BEM, as summarized in Table 3 [100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123].
As said, IFC schema can mainly export geometry information. For this reason, in various papers, such as that of Cemesova et al. [100], extensions to this format have been proposed, to complete the model by also inserting energy data, such as the properties of the materials, the characteristics of the plant system, or the thermal zones.
For example, the information contained in the IFC files, mainly related to the geometry of the building, is not sufficient to carry out the BEM-based energy performance simulation of photovoltaic systems. Therefore, Gupta et al. [101] proposed to link the BIM-based model to external archives containing meteorological data and technical specifications of the system components (PV module, inverter).
The IFC format is geometrically very detailed and contains a lot of potentially redundant information for energy simulation. This excess of data could lead to export errors. Examining several case studies, Maile et al. [124] listed the geometry problems encountered with the use of the IFC format. Among these, duplicate objects, incorrect space volumes, missing spaces, missing space boundaries, missing exterior walls, misalignment of space geometry, building element geometry, and column dislocation have been detected. BSPro COM-Server is one of the tools currently used by several researchers to simplify the geometric representation of IFC to the more restrictive three or four vertex planar surfaces [103].
Differently, the gbXML format has a geometric data structure designed to be in line with energy software requirements [104]. In the work of Yang et al. [104], a workflow to optimize the geometric data contained in a gbXML file was proposed. This workflow aims to construct the building model by extruding the room boundaries. The presented method was tested on two sample buildings, showing that the model obtained through the use of the developed workflow has cleaner geometry than that of models deriving from standard gbXML files (Figure 8).
One of the barriers to BIM–BEM integration is the large number of input parameters needed to perform energy analysis. The metamodel could be the solution to this problem as it consists of a simplified model able to correlate the inputs to the results deriving from more complex mathematical models (for example energy modeling tools). Bracht et al. [105] developed an integration tool to link models made with different BIM software to the metamodel obtained in gbXML format. The study, however, was carried out on a building with a simple geometry. Consequently, it would be advisable to test the method on more complex building geometry to verify its applicability.
In the work of Chiaia et al. [106], “Space Boundary Tool” (SBT) middleware was used as an “interoperable bridge” between Revit and EnergyPlus to better exchange information between the two software without data loss. The experimentation led to good results. The format used for the exchange was the IFC.
Wang et al. [107] presented a framework for an automated HVAC system design tool. This procedure was tested in an office building located in Shanghai. However, full automation of the exchange process has not been reached. In fact, the authors manually simplified the BIM model before exporting it to the BEM software through the gbXML format (Figure 9).
To minimize the loss of information and optimize modeling times on EnergyPlus, some works [111,113,114] developed an interface to convert geometric information from IFC to IDF (Input Data Files), the input format of the energy software.
Likewise, Barone et al. [118] presented a workflow capable of converting BIM into an input file readable using energy simulation software. The tool was tested on a sample building located in Naples, Italy. Thanks to the developed workflow, various design strategies were considered for the energy improvement of the building. These included the introduction of an air-to-water heat pump, photovoltaic glass, and the replacement of shading systems with photovoltaic shelters. Particular attention was devoted to studying the optimal level of detail of the modeling required for a reliable energy assessment of the building. Before exporting to gbXML, the model was duly simplified where necessary.
Through an in-depth analysis of three case studies, Kamel et al. [121] found that the gbXML format does not correctly export all the data required for energy analysis. As a result, the authors proposed a tool capable of modifying a gbXML file before its export, in order to solve problems related to the building envelope.
Although middleware corrective tools constitute the most widely used interoperability strategy today, their flaw is the dependence on another data source, different from the BIM, which could lead to errors in the model as the possible presence of duplicates. In addition, the middleware tool is limited, as it is meant for a specific simulation software and situation; therefore, it is not applicable to every case study [9].
4.3. Strategy 3—Adherence to Model View Definitions (MVD)
There are many workflows in the IFC format that are far from the purpose for which energy simulation tools were created. In fact, BEMs do not need all the information contained in the IFC. Model View Definitions were created to solve this problem. MVDs are a subset of the IFC schema [125]. They define which datasets are usable for export to BEM software [125] using the Information Delivery Manual (IDM) methodology. This strategy is very flexible as it is not based on a proprietary tool [9].
An example of the application of this approach is represented by the work of Pinheiro et al. [126]. Indeed, in their study, an MVD was developed after identifying the necessary exchange requirements needed for exporting to EnergyPlus and Modelica, based on a collection of use cases. The use cases varied in levels of complexity from a single room to a large commercial building resulting in a total of eight use cases, each featuring a different HVAC system. The methodology used was IDM/MVD (Figure 10) and it focused on the latest release of the IFC schema, i.e., IFC4, which is currently the most used version of IFC.
Andriamamonjy et al. [127] created an MVD intended to improve the exchange of information between the IFC file and Modelica, defining the requirements for energy simulation.
On the other hand, a Simulation Domain Model (SimModel), created by Lawrence Berkeley National Laboratory in collaboration with Digital Alchemy Pro represents an approach to integrate Modelica into the BIM environment. SimModel could form the basis for a new IFC Model View Definition, which could allow for the exchange of information between HVAC design applications and BEMs [128]. Wimmer et al. [129] extended the research on using SimModel by connecting it to different Modelica libraries, taking into consideration several complex use cases.
Although the interoperability strategy based on MVDs is promising, it still has limitations due to the incomplete compatibility of BIM with IFC4 and customized MVDs [9].
4.4. Strategy 4—Proprietary Tool-Chain
This interoperability strategy involves using proprietary software (usually the BIM Application Programming Interface—API) to transfer information between BIM and BEM. By adopting this method, data loss is minimized, as the software API is fully BIM compatible.
Rahmani Asl et al. [130] created a BIM-based performance optimization framework (BPOpt) capable of transforming BIM models into input files for energy software. The development of the software was based on the interaction between Revit and Dynamo, an application capable of expanding the parametric capabilities of Revit. The developed framework used the Revit API to transform the information contained in the BIM into the data necessary for the creation of the energy model. The energy simulation was performed on Green Building Studio (GBS) through the creation of an automatic connection between BIM and BEM software.
Gao et al. [44] utilized Revit API to extract project information for energy simulation and generate reports within Revit User Interface through Visual C#.
Through the use of the API, Yan et al. [131] created two prototypes, Revit2Modelica and Revit2Radiance, able to optimize the communication between the tools.
Object-oriented modeling (OOM) is considered by several researchers a very good method to perform multidomain energy simulations [132]. Modelica is an example of software that uses the object-oriented physical modeling (OOPM) language to model the dynamic behavior of buildings. Creating Modelica simulations is time-consuming due to the complexity of providing the necessary parameters (such as the components of an HVAC system or the thermal properties of materials) for a complete solution. In this context, the use of a BIM-based model to automatically transfer these parameters can eliminate a large part of the manual task [133]. Many efforts have been made to improve the export from BIM to Modelica [133]. For example, Kim et al. [134] have developed a Modelica library to translate BIM elements into OOPM-based energy models using the API.
According to Jeong et al. [135], using Revit API instead of standardized IFC and gbXML formats, allows to “(1) preserve object relationships established by parametric modeling, (2) define a model view of Revit to support bidirectional data exchange with the object-oriented simulation solver— LBNL Modelica Buildings Library”. This approach was tested in their work [136] for the development of an algorithm capable of transforming the object-oriented architectural model of the building into an energy model.
Continuing the work already undertaken with the development of the SimModel framework [129], Remmen et al. [137] studied the linking of the SimXML file with the mapping rules of the various Modelica libraries. The procedure was made possible thanks to a Python tool which, through a generic API, accessed the mapped data to create the model on Modelica.
A Python framework is also used by Thorade et al. [138] to improve communication between BIM and Modelica. Applying the framework to a simple case study proved efficient. The authors intend to test the methodology on more complex case studies in the future.
In the work of Utkucu et al. [139], Dynamo was used to set the parametric relationships of the facade of a sample building for its energy optimization, through Revit API.
Parametric modeling has great potential for energy analyses, since it is possible to have a rapid comparison between the architectural project and the energy performance associated with it. This approach allows the designer to evaluate different alternatives to make effective decisions. This concept was demonstrated in a study by Rahmani Asl et al. [140], where the authors exploited the Revit API to parametrically model a sample building and the Green Building Studio API to simulate it energetically.
Furthermore, in some cases, through the use of specific tools, it is possible to have a real-time connection between the architectural model and the energy model. An example of these tools is Design Performance Viewer (DPV) [141,142,143], which can be used in order to integrate energy calculations directly into the BIM editor using the API. With this system, the designer can switch between displaying the model and the resulting energy performance at any time.
In summary, the proprietary tool-chain strategy demonstrates many advantages, including reduced data loss in the transition from the architectural model to the energy model, immediacy in reading energy results, and the possibility of evaluating different strategies during the design process. The main downside to this approach is that proprietary software is generally only compatible with the vendor’s tools, not allowing for large-scale application.
5. Discussion
The four interoperability strategies employed to enable a connection between BIM and BEM software showed advantages and disadvantages, but none proved to be significantly better than the others. Figure 11 shows a synoptic overview of the steps required to move from BIM to BEM with the four interoperability strategies analyzed.
The present literature review revealed that the most used interoperability strategy is that of standardized exchange formats and middleware corrective tools, with 60% of publications, followed by the proprietary tool-chain (23%), and real-time connection (11%). The least common strategy was found to be adherence to MVD (6%), as shown in Figure 12.
Based on the literature review, it is worth noting that all the interoperability strategies are capable of correctly exporting data from the BIM-based to the BEM-based model, except for the standardized exchange formats and middleware corrective tools (strategy 3) which, although resulting in being the most widely used, showed limited ability to export data correctly. Moreover, not all strategies enable direct BIM–BEM interoperability, but in some cases (strategies 2 and 3) intermediate steps are needed, as shown in Figure 12.
Although strategy 1 (real-time connection) allows for energy simulations to be carried out very quickly, a detailed energy analysis cannot be performed due to the performance limitations of the software. Differently, the other three interoperability strategies showed the ability to perform even complex dynamic energy analysis. Clearly, this ability results in a greater time burden for model creation. In particular, except for strategy 1, any changes in the BIM model are not directly translated to the BEM model, leading to a software interaction process that is not always efficient and liable to information losses.
Unlike the first three strategies, which showed considerable adaptability to the different cases analyzed, strategy 2 was less flexible to be applied to all case studies, as middleware tools are almost always designed for specific simulation software.
Moreover, it is interesting to observe that all interoperability strategies showed a good ability to customize software operations, except for strategy 1, which limits the design choices to a restricted number of parameters. For instance, very important variables, such as the power of the heat generator, and the type of emission devices, cannot be customized. Finally, the only strategy that depends on proprietary software is strategy 4.
In Figure 13, the main advantages and disadvantages of each interoperability strategy are summarized, based on the articles examined in this study.
Therefore, it was possible to appreciate the potential and limitations of each of the interoperability strategies employed to date. The results obtained showed that there is no strategy that is clearly better than the others and that each strategy still has limitations that preclude its widespread use. At the moment, it is up to the designer to choose the one best suited to their needs. Thus, research must continue to search for flexible, opensource, accurate interoperability solutions that can enable massive deployment of BIM and BEM tools, making building energy design affordable for everyone.
The main advantages and disadvantages of each strategy are briefly listed in Figure 14.
Remark 1.
For further information regarding the individual works, refer to Table A2 of Appendix A.
6. Conclusions
This work presented an in-depth BIM–BEM interoperability analysis. The research highlighted that the interest in architectural and energy modeling has grown significantly in the last few years, and BIM–BEM integration is one of the main research goals.
It was found that interoperability strategies are usually analyzed individually, but there are no articles that summarize and compare them in-depth.
In detail, the main findings of the literature review revealed that:
- (1)
- The most adopted strategy is standardized exchange formats and middleware corrective tools. To date, perfect integration of the two programs is still far away. In most cases, the transition from the architectural to the energy model requires manual changes before carrying out the energy simulation, especially when the case study is complex. This is mainly due to the loss of information, the presence of geometric errors, and lack of thermal and physical data. Middleware tools try to overcome this problem by integrating the information lost. However, their dependence on another data source limits their use.
- (2)
- The real-time connection strategy, not requiring the model export process, avoids all the problems related to this phase. On the other hand, the review showed that this strategy leads to an excessive generality of the results.
- (3)
- The proprietary tool-chain strategy has great potential, as it preserves object relationships established by parametric modeling, reducing incompatibility errors. However, the dependence on proprietary software limits the widespread application of this method.
- (4)
- Adherence to Model View Definitions (MVDs), designed to optimize the model exchange in IFC format, is independent from proprietary software. Its main limitations currently lie in the insufficient compatibility of the different BIM software applications with IFC4 and customized MVDs.
In conclusion, BIM–BEM interoperability is very broad and leaves space for various insights, since every strategy, which has shown advantages and disadvantages, requires deepening and refining. The results obtained are encouraging and pave the way for many research branches, as none of the interoperability strategies has proven clearly better than the others.
Future developments of the work will focus on testing and comparing different interoperability strategies trying to improve communication between software. The idea is to find solutions capable of solving some of the problems that currently arise in the transition phase of the model as much as possible, to make the BIM to BEM method more accessible and widespread.
Author Contributions
Conceptualization, A.C. and T.d.R.; methodology, A.C., T.d.R. and D.A.; resources, A.C. and T.d.R.; data curation, A.C.; writing—original draft preparation, A.C. and T.d.R.; writing—review and editing, T.d.R., D.P. and D.A.; supervision, T.d.R., D.P. and D.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A
Table A1.
PRISMA 2020 checklist. Adapted from [25].
Table A1.
PRISMA 2020 checklist. Adapted from [25].
| Section and Topic | Item # | Checklist Item | Location Where Item Is Reported |
|---|---|---|---|
| TITLE | |||
| Title | 1 | Identify the report as a systematic review. | |
| ABSTRACT | |||
| Abstract | 2 | See the PRISMA 2020 for abstracts checklist. | |
| INTRODUCTION | |||
| Rationale | 3 | Describe the rationale for the review in the context of existing knowledge. | |
| Objectives | 4 | Provide an explicit statement of the objective(s) or question(s) the review addresses. | |
| METHOD | |||
| Eligibility criteria | 5 | Specify the inclusion and exclusion criteria for the review and how studies were grouped for the syntheses. | |
| Information sources | 6 | Specify all databases, registers, websites, organizations, reference lists, and other sources searched or consulted to identify studies. Specify the date when each source was last searched or consulted. | |
| Search strategy | 7 | Present the full search strategies for all databases, registers, and websites, including any filters and limits used. | |
| Selection process | 8 | Specify the methods used to decide whether a study met the inclusion criteria of the review. | |
| Data collection process | 9 | Specify the methods used to collect data from reports. | |
| Data items | 10a | List and define all outcomes for which data were sought. Specify whether all results that were compatible with each outcome domain in each study were sought (e.g., for all measures, time points, analyses), and if not, the methods used to decide which results to collect. | |
| Synthesis methods | 13a | Describe the processes used to decide which studies were eligible for each synthesis (e.g., tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)). | |
| 13b | Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions. | ||
| 13c | Describe any methods used to tabulate or visually display results of individual studies and syntheses. | ||
| 13d | Describe any methods used to synthesize results and provide a rationale for the choice(s). | ||
| RESULTS | |||
| Study selection | 16a | Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram. | |
| Study characteristics | 17 | Cite each included study and present its characteristics. | |
| DISCUSSION | |||
| Discussion | 23a | Provide a general interpretation of the results in the context of other evidence. | |
| 23b | Discuss any limitations of the evidence included in the review. | ||
| 23d | Discuss implications of the results for practice, policy, and future research. | ||
| OTHER INFORMATION | |||
| Registration and protocol | 24a | Provide registration information for the review, including register name and registration number, or state that the review was not registered. | |
| 24b | Indicate where the review protocol can be accessed, or state that a protocol was not prepared. | ||
| 24c | Describe and explain any amendments to information provided at registration or in the protocol. | ||
| Support | 25 | Describe sources of financial or nonfinancial support for the review, and the role of the funders or sponsors in the review. | |
| Competing interests | 26 | Declare any competing interests of review authors. | |
| Availability of data, code, and other materials | 27 | Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review. | |
Table A2.
Summary of the analyzed works.
| References | Year | Country | Publisher | Database | Keywords | Type of Article | Research Object | Main Research Contents |
|---|---|---|---|---|---|---|---|---|
| Andriamamonjy et al. [9] | 2019 | Belgium | Elsevier | Scopus | building information model (BIM); building energy performance simulation (BEPS); scientometric analysis | Review article | BIM functionalities; BIM–BEPS interoperability; interoperability strategies | Review of the integration of BIM and building energy performance simulation (BEPS) and of the different strategies to improve their interoperability. |
| Li et al. [11] | 2023 | USA | Elsevier | Scopus | BIM interoperability; BEM; object mapping; invariant signatures; building design; IFC | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM) | Development of mapping algorithms capable of interfacing BIM and analytical models by automatically mapping objects based on their invariant signatures. |
| Farzaneh et al. [13] | 2019 | Canada | Elsevier | Scopus | BIM; BEM; design process; technology; research gap; literature review | Review article | BIM–BEM interoperability, discussion about Model View Definition (MVD) | Overview of the BIM–BEM process and recent technological developments and proposal of a framework to improve BIM–BEM interoperability. |
| Alsharif [14] | 2019 | Australia | Swinburne University of Technology | Google Scholar | Review article | BIM and BEM applications; BIM–BEM interoperability; interoperability strategies | Review of the current applications of BIM-based BEM process and of the different strategies to improve their interoperability. Presentation of a case study of the application of BIM-based BEM between two common software tools “Revit and IES VE”. | |
| Bahar et al. [15] | 2013 | France | MDPI | Scopus | thermal simulation; BIM; interoperability; integration review | Review article | BIM and BEM functionalities; BIM–BEM interoperability | Description of the BIM and BEM functionalities, review of the current trends in thermal simulation, discussion on the interoperability between BIM and BEM. |
| Pezeshki et al. [16] | 2019 | Iran | Elsevier | Scopus | BEM; building energy; BIM; optimization; new methods | Review article | BEM application; BIM–BEM interoperability | Reviews of building energy modeling (BEM) development and review of BIM–BEM interoperability. |
| Lesniak et al. [17] | 2021 | Poland | MDPI | Scopus | building information modeling (BIM); building energy model (BEM); architecture, engineering, and construction (AEC) projects; barriers; Ishikawa diagram | Review article | BIM advantages; BIM–BEM interoperability | Discussion on the importance of BIM during the life cycle of a building and analysis of BIM–BEM interoperability. Focus on the use of BIM in Poland. |
| Fernald et al. [18] | 2018 | Canada | Conference | Google Scholar | eSim; building performance simulation; model translation; energy modelling; BIM to BEM; interoperability | Review article | BIM–BEM interoperability | Analysis on BIM to BEM translation workflows and their challenges and limitations. Focus on the optimization of BIM–BEM interoperability. |
| Maskil-Leitan et al. [19] | 2018 | Israel | Springer | Scopus | building information modeling (BIM); building energy modeling (BEM); corporate social responsibility (CSR); sustainability; social network analysis (SNA) | Review article | Relevance of BIM’s social capabilities to the BEM process | Analysis of the integration of BIM socio-technical system into the BEM process, with the possibility of improving the process through stakeholder management. |
| Khodeir et al. [20] | 2017 | Egypt | Elsevier | Scopus | building information modelling (BIM); building energy models (BEM); architectural firms Egypt | Review article | BIM and BEM applications in Egypt; BIM–BEM interoperability | Analysis of the state of the art of BIM and BEM application in Egypt and focus on BIM–BEM interoperability. |
| Gao et al. [21] | 2019 | UK, Germany | Elsevier | Scopus | building information modelling (BIM); building energy modelling (BEM); IFC; gbXML | Review article | Application of BIM and BEM in the design process; BIM–BEM interoperability | Review on the building design process, and applications of building information modelling and building energy modelling in the design process. Review on the development of building information modelling-based building energy modelling methods and the development of prevalent informational infrastructures. |
| Senave et al. [22] | 2015 | Belgium | WITPRESS | Google Scholar | BIM, building energy performance (BEP); energy simulation (software); interoperability; information query; data transfer; design stages | Review article | Relation between BIM and energy simulation in the different stages of design | Review of the relation between BIM and energy simulation in the different stages of design, with an emphasis on the conceptual stage. |
| Gerrish et al. [23] | 2016 | UK | Emerald Publishing Limited | Scopus | design and development; stakeholders; information exchange; building energy modelling; building information modelling; level of development | Review article | BIM–BEM interoperability | Presentation of a process map for exchanging information between buildingdesigners and BEM practitioners highlighting the extents of information required at key stages throughout the construction design process. |
| Di Biccari et al. [24] | 2022 | Italy | Elsevier | Google scholar | Review article | BIM–BEM interoperability; interoperability strategies | Analysis of the state of the art of the interoperability between BIM and BEM and illustration of the different existing strategies to improve it. | |
| Hu [31] | 2018 | USA | MDPI | Scopus | renovation; education buildings; building information model; building environmental model; building performance model; nearly zero energy | Original research article | BIM–BEM interoperability | Presentation of a framework to test the interoperability among different digital tools and platforms. The framework has been used for the energy renovation of existing education buildings. |
| Rathnasiri et al. [32] | 2020 | China, Sri Lanka, UK | International Journal of Design and Nature and Ecodynamics | Scopus | green building information modeling; existing green buildings; energy simulation | Original research article | BIM for energy analyses | Test on the possibility of using Green BIM techniques to conduct energy analyses. |
| Visschers et al. [33] | 2016 | The Netherlands | Eindhoven University of Technology | Google Scholar | Original research article | BIM–BEM interoperability optimization | Development of a tool capable of converting IFC files into gbXML files for optimizing BIM–BEM interoperability. | |
| Fonseca Arenas et al. [34] | 2023 | UK | Elsevier | Scopus | building information modelling; life cycle assessment; sustainability; buildings | Review article | BIM for energy analyses | Analysis of different methodologies such as building information modeling (BIM), lifecycle assessment (LCA), and building energy modeling (BEM) through a systematic literature review. |
| Cormier et al. [38] | 2011 | France | Conference | Scopus | Original research article | BIM–BEPS interoperability | Overview of the services provided by the platform for the BIM management in a multi-user environment; BIM-BEPS interoperability. | |
| Bonomolo et al. [40] | 2021 | Italy | MDPI | Scopus | BIM; BEM; simulation modelling; dynamic simulation | Original research article | BIM–BEM interoperability | Analysis of the interaction between BIM and energy simulation, through a review of the main existing commercial tools. The analysis has been conducted on a case study. |
| Cho et al. [43] | 2011 | USA, Korea | Conference | Scopus | building information modeling; LEED; energy efficiency; high-performance building; scope definition; PDRI; whole-building design | Original Research Article | BIM–BEM interoperability | Comparison of EnergyPlus and IES < Virtual Environment > as BIM-based energy simulation tools. The analysis was conducted on a case study. |
| Gao et al. [44] | 2019 | UK, Germany | Conference | Scopus | early design stage; BIM-based building energy simulation; design optimization; Revit | Original research article | BIM–BEM interoperability | Presentation of a BIM-based real time building energy simulation and optimization tool |
| Stegnar et al. [45] | 2019 | Slovenia | Elsevier | Scopus | progressive BIM; project information management; renovation; energy performance; sustainability | Original research article | BIM for energy analyses | Test on the use of BIM for energy analyses |
| Lin et al. [46] | 2019 | China | MDPI | Scopus | green BIM; thermal comfort; energy consumption; tradition market; PMV; IES VE | Original research article | BIM–BEM interoperability | Use of green BIM model to explore the energy efficiency performance and comfort level of a case study. |
| Paneru et al. [48] | 2021 | USA | MDPI | Scopus | energy; sustainability; environment; building information model; energy | Original research article | BIM for energy analyses | Develop of a comprehensive framework for the integration of energy analysis with existing Building Information Modeling tools. |
| Carrasco et al. [49] | 2023 | Spain | MDPI | Scopus | BIM; thermal loads; simulation; cost-effectiveness | Original research article | BIM–BEM interoperability | Calculation of the thermal loads of a sample building through a BIM-based energy model. |
| Montiel-Santiago et al. [50] | 2020 | Spain | MDPI | Scopus | Building information modeling; BIM-6D; energy e efficiency; green buildings; hospitals; emissions; sustainability; energy simulation; energetic certification; decarbonization | Original research article | BIM–BEM interoperability | Creation of the energy model of a building using the BIM methodology. |
| Forastiere et al. [51] | 2023 | Italy | MDPI | Scopus | energy efficiency; building information modeling; building energy modeling; dynamic multi-parameter analysis; energy retrofit; thermal comfort; carbon footprint; economic assessment; dynamic simulation; thermal bath building | Original research article | BIM–BEM interoperability | Integration of dynamic multi-data and parameter analysis with advanced building information modeling (BIM) techniques to evaluate the energy performance of existing buildings and determine the most effective retrofit strategies. |
| Amoruso et al. [52] | 2019 | Korea, Germany | MDPI | Scopus | daylight analysis; visual comfort; BIM-parametric refurbishment workflow | Original research article | BIM–BEM interoperability | Analysis of the improvement in visual comfort for the renovation of an exemplary apartment unit in Seoul using building information modeling (BIM) and parametric environmental analysis tools. |
| Elnabawi [53] | 2020 | Bahrain, Egypt | Frontiers in Built Environment | Scopus | interoperability; building information modeling (BIM); building energy modeling (BEM); building and sustaining a research program; energy consumption (EC) | Original research article | BIM–BEM interoperability | Test on the interoperability between Autodesk’s Revit (BIM) and DesignBuilder and IES-ve (BEM). |
| Sultanguzin et al. [54] | 2019 | Russia | Conference | Scopus | Original research article | BIM–BEM interoperability | Presentation of the concept and the process of integrated design and construction of energy-efficient house during the lifecycle based on the use of BIM (building information modeling), BEM (building energy modeling) and CFD (computational fluid dynamics) technologies. | |
| Maglad et al. [59] | 2023 | Saudi Arabia, Pakistan, Kuwait | Elsevier | Scopus | BIM; MEP; BIM adoption; energy consumption; green buildings | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—real-time connection | Orientation analysis using Autodesk Insight 360 and Green Building Studio. |
| Sanhudo et al. [60] | 2018 | Portugal | Elsevier | Scopus | energy retrofit; building information modeling; data acquisition methods; authoring and energy analysis software; interoperability | Review article | BIM for energy retrofitting | BIM for energy efficiency; exploration of data acquisition solutions such as laser scanning and infrared thermography. |
| Yarramsetty et al. [61] | 2019 | India | Springer | Scopus | building information modelling (BIM); energy simulations; multi-family residential house; building orientation; sustainability | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—real-time connection | Use of BIM for orientation analysis on a building case study. |
| Ciccozzi et al. [63] | 2023 | Italy | Conference | Google Scholar | building information modelling (BIM); energy efficiency; sustainable building; incident solar radiation; energy simulation | Original research article | BIM for energy studies | Use of BIM for the analysis of shading and incident solar radiation on a sample building. |
| Reeves et al. [79] | 2015 | USA | MDPI | Scopus | building information modeling (BIM); building energy modeling (BEM); simulation; energy consumption; daylighting; natural ventilation | Original research article | Evaluation of BEM tools | Evaluation of twelve BEM tools using four criteria: interoperability, usability, available inputs and available outputs. Application of the first three BEM tools on a case study. |
| Pereira et al. [80] | 2021 | Portugal, USA | Elsevier | Google scholar | architecture; construction; design; energy performance; building performance; engineering; environment; operations; sustainability | Review article | BIM and BEM review | Identification of areas where BIM can improve building efficiency. Review of the BIM and BEM software currently present and identification of the most used ones. |
| Kim et al. [81] | 2011 | USA | Conference | Original research article | BIM–BEM interoperability | Identification of the differences in energy simulation results between detailed simulation method (DOE 2.2 simulation engine) and BIM-based simulation method. | ||
| Trani et al. [82] | 2021 | Italy | Conference | Scopus | BIM cross information; IFC Model View Definition; BIM interoperability; from BIM to BEM | Original research article | BIM–BEM interoperability | Creation of a tool able to collect and import information in the BIM model in order to be exported using the IFC standard and read using energy analysis software. |
| Kenley et al. [83] | 2016 | Australia, New Zealand | Conference | Scopus | Original research article | BIM–BEM interoperability | Presentation of two interoperability issues for construction of rail infrastructure. | |
| Porsani et al. [84] | 2021 | Spain | MDPI | Scopus | building information modelling (BIM); building energy model (BEM); Green Building extensible markup language (gbXML); Industry Foundation Classes (IFC); interoperability; digital twin; sustainable construction; intelligent buildings assessment; sustainability performance; simulation tools for building | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—standardized exchange formats | Comparison between ogbXML and IFC exchange formats through the modeling of two sample buildings, namely, a residence and an industrial warehouse. |
| Chen et al. [85] | 2018 | Singapore, UK | Conference | building information modelling (BIM); building energy simulation (BES); interoperability; sustainable design; Green Building XML schema (gbXML) | Original research article | Interoperability between building Information modeling (BIM) and building energy modeling (BEM)—standardized exchange formats | Test on BIM–BEM interoperability by exporting a residential building model to four different energy software (Ecotect, EQUEST, Design Builder and IES-VE) using gbXML format. | |
| Osello et al. [86] | 2011 | Italy | Conference | Review article | BIM–BEM interoperability | Definition of a preliminary set of possible standards for general architectural data (e.g., orientation, surfaces, volumes, dimensions) and detailed material data (e.g., texture, thickness, stratigraphy, reflection and roughness) targeted to optimize the interoperability among architectural and energetic software in a BIM process. | ||
| Boloorchi [87] | 2023 | Iran | Sciendo | Google Scholar | window size; window material, window shadings, window position, BIM, The Autodesk Insight 360 | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—real-time connection | Using Insight 360 for energy analysis of a sample building: potential and limitations. Dimensions, position, material and shading of the windows were studied with Insight 360 to identify the best solutions for energy savings in the building. |
| Gonzàlez et al. [88] | 2021 | Brazil | MDPI | Google Scholar | energy efficiency; experimental design; building appliances; energy performance; BIM and BEM | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—real-time connection | Energy simulation of a hypothetical two-story single-family home selecting five different locations, using Insight 360. |
| de Lima Montenegro Duarte et al. [89] | 2021 | Brazil | Elsevier | Scopus | energy efficiency; thermal comfort; visual comfort; daylight; building information modeling | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—real-time connection | Using Autodesk Insight 360 for a school lighting study in Brazil. |
| Dong et al. [90] | 2007 | USA | Conference | IFC; gbXML; common data exchange; lighting simulation | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—standardized exchange formats | Detailed investigation and comparative study of the differences between IFC and gbXML in terms of their data representations, data structures and applications. | |
| Gourlis et al. [91] | 2017 | Austria | Elsevier | Scopus | BIM; BEM; industrial construction; thermal simulation | Original research article | Interoperability between building Information modeling (BIM) and building energy modeling (BEM)—standardized exchange formats | Test on the gbXML format through the export to OpenStudio of the models of two industrial plants. |
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| Ham et al. [93] | 2015 | USA | Elsevier | building information models (BIM); Green Building XML (gbXML); building energy performance modeling; thermography; image-based 3D reconstruction; thermal resistances; building retrofits | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—standardized exchange formats | Presentation of an automated method for assigning thermal properties to BIM building components in gbXML format through a thermographic survey. | |
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| Benjanac [116] | 2008 | USA | Lawrence Berkeley National Laboratory | simulation; simulation input; IFC-based BIM; interoperable software; data transformation; rules; methodology; semi-automated process | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—middleware corrective tool | Illustration of a methodology to semi-automate building energy performance (BEP) simulation preparation and execution makes this process much more effective. | |
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| Yan et al. [131] | 2013 | USA, South Korea | Conference | Scopus | Original research article | Interoperability between building information modeling (BIM) and building energy modeling (BEM)—proprietary tool-chain | Explore the benefits of using application programming interface (API) instead of interchangeable BIM data format—Industry Foundation Classes (IFC). | |
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Figure 1.
Flowchart of the methodology used for article screening and review [25].
Figure 1.
Flowchart of the methodology used for article screening and review [25].
Figure 2.
Geographic distribution of the publications.
Figure 3.
Most used keywords in the collected articles.
Figure 4.
BIM support during the various phases of the construction process.
Figure 5.
An example of solar analysis with Revit. Adapted from [63].
Figure 5.
An example of solar analysis with Revit. Adapted from [63].
Figure 6.
Creating the energy model using Autodesk Insight 360. Adapted from [59].
Figure 6.
Creating the energy model using Autodesk Insight 360. Adapted from [59].
Figure 7.
Comparison between the standardized exchange formats. In red are the models exported in gbXML; in yellow are the models exported in IFC. (a) Residence (simple geometry well recognized). (b) Industrial warehouse (complex geometry, with information loss). Adapted from [84].
Figure 7.
Comparison between the standardized exchange formats. In red are the models exported in gbXML; in yellow are the models exported in IFC. (a) Residence (simple geometry well recognized). (b) Industrial warehouse (complex geometry, with information loss). Adapted from [84].
Figure 8.
Comparison of three different gbXML exports. (a) Using the workflow developed in the work [104]. (b) Using “Room Volumes” in Revit. (c) Using “Energy Model” in Revit. Adapted from [104].
Figure 9.
Process of simplifying the BIM model. Adapted from [107].
Figure 9.
Process of simplifying the BIM model. Adapted from [107].
Figure 10.
The methodology used for the development of the MVD, extracting the information necessary for the BEM software from eight use cases. Adapted from [126].
Figure 10.
The methodology used for the development of the MVD, extracting the information necessary for the BEM software from eight use cases. Adapted from [126].
Figure 11.
Comparison of different BIM–BEM interoperability strategies.
Figure 12.
Percentage spread of interoperability strategies in the papers analyzed in this review.
Figure 13.
Comparison between interoperability strategies pros and cons.
Figure 14.
Summary of the main advantages and disadvantages of each interoperability strategy.
Table 1.
Keywords used for the literature research.
| Main Keywords | Other Keywords | |||||
|---|---|---|---|---|---|---|
| BIM-BEM | AND | Interoperability | OR | Integration | ||
| BIM-BEM | AND | Model export | OR | Model translation | ||
| BIM | AND | BEM | AND | Interoperability | OR | Integration |
| BEM | AND | BIM-based analysis | ||||
| BIM | AND | BEPS | ||||
| BIM | AND | Thermal simulation | AND | Interoperability | ||
| BIM | AND | Dynamic simulation | AND | Building retrofit | ||
Table 2.
Inclusionary and exclusionary criteria used for the second screening.
| Criteria | |
|---|---|
| Inclusionary | Exclusionary |
| Scientific articles | Not scientific articles |
| International articles published in English | Articles published in other languages |
| - | Duplicated papers |
| Paper available (papers that provide the online version of full-text content) | Papers not available (papers that cannot provide the online version of full-text content) |
| Articles pertinent to the topic under study | Articles not pertinent to the topic under study |
Table 3.
Case studies on the use of middleware tools.
| References | Middleware Tool | Tool Functionality | Case Study |
|---|---|---|---|
| Cemesova et al. [100] | PassivBIM Java (for IFC) | Insertion of material properties and characteristics of the plant system | Energy analysis of single-family and terraced buildings |
| Gupta et al. [101] | RENEWBIM (for IFC) | Introduction of climate data and PV module and inverter specifications | Analysis of a photovoltaic system for domestic use |
| Carvalho et al. [102] | IFC Builder (for IFC) | Correction of geometric errors | Energy analysis of an existing building and a new building project |
| Karola et al. [103] | BSPro COM-Server (for IFC) | Geometric simplification of the model | Building energy analysis |
| Yang et al. [104] | gbXML corrective tool (for gbXML) | Correction of geometric errors | Importing models of a technical school and an academic building to BEM |
| Bracht et al. [105] | gbXML corrective tool (for gbXML) | Insertion of the thermal properties of the materials and information related to the operation of the windows, such as the opening factor for ventilation | Thermal load prediction of a single-family residential building |
| Chiaia et al. [106] | Space Boundary Tool (SBT) (for IFC) | Correction of the geometric errors and insertion of the material properties | Energy analysis of a sample building |
| Wang et al. [107] | Automated HVAC design tool (for gbXML) | Geometric simplification of the model and HVAC system topology generation | HVAC system analysis of an eight-stories office building |
| Chen et al. [108] | AutoBPS-BIM (for IFC) | Introduction of the HVAC system information | Load calculation and chiller design optimization of an office building |
| Kamel et al. [109] | Automated Building Energy Modeling and Assessment Tool (ABEMAT) (for gbXML) | Correction of the geometric errors | Energy analysis of a one-story building |
| Kim et al. [110] | IFC corrective tool (for IFC) | Automatic mapping of building materials | Energy analysis of an office building |
| Ahn et al. [111] | IFC–IDF interface (for IFC) | Automated conversion of geometric information | Energy analysis of a library building |
| Spiridigliozzi et al. [112] | SIMPLEBIM (for IFC) | Correction of the geometric errors | Energy analysis of a single dwelling of two floors |
| Kim et al. [113] | IDF converter (for IFC) | Insertion of the material properties | Energy analysis of a five-story building |
| Choi et al. [114] | IFC-IDF converter (for IFC) | Definition of internal loads, equipment systems and weather data | Energy analysis of sample building |
| Heffernan et al. [115] | Solibri Model Checker (for gbXML/IFC) | Geometric error identification | Energy analysis of a residential building |
| Benjanac [116] | Geometry Simplification Tool (GST) | Geometric simplification of the model | Building energy analysis |
| Benjanac et al. [117] | IFC HVAC interface to EnergyPlus | Defining HVAC equipment and system data | Building energy analysis |
| Barone et al. [118] | gbXML corrective tool (for gbXML) | Inclusion of custom simulation settings and collection of specific outputs | Energy analysis of a maritime passenger station |
| Guzmán Garcia et al. [119] | gbXML corrective tool (for gbXML) | Correction of the geometric, material and/or location mismatches | Energy analysis of sample buildings |
| Ramaji et al. [120] | BIMserver serializer | Correction of the geometric errors | Energy analysis of an office building |
| Kamel et al. [121] | gbXML corrective tool (for gbXML) | Correction of the geometric errors and insertion of the material properties | Energy analysis of sample buildings |
| Welle et al. [122] | ThermalSim (for IFC) | Correction of the geometric errors | Thermal simulation of two industrial case studies |
| O’Donnell et al. [123] | Solibri Model Checker (for gbXML/IFC) | Geometric error identification | Energy analysis of NASA Ames Sustainability Base |
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MDPI and ACS Style
Ciccozzi, A.; de Rubeis, T.; Paoletti, D.; Ambrosini, D. BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies. Energies 2023, 16, 7845. https://doi.org/10.3390/en16237845
AMA Style
Ciccozzi A, de Rubeis T, Paoletti D, Ambrosini D. BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies. Energies. 2023; 16(23):7845. https://doi.org/10.3390/en16237845
Chicago/Turabian StyleCiccozzi, Annamaria, Tullio de Rubeis, Domenica Paoletti, and Dario Ambrosini. 2023. "BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies" Energies 16, no. 23: 7845. https://doi.org/10.3390/en16237845
APA StyleCiccozzi, A., de Rubeis, T., Paoletti, D., & Ambrosini, D. (2023). BIM to BEM for Building Energy Analysis: A Review of Interoperability Strategies. Energies, 16(23), 7845. https://doi.org/10.3390/en16237845
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