{"id":24529,"date":"2022-12-13T10:39:23","date_gmt":"2022-12-13T09:39:23","guid":{"rendered":"https:\/\/www.modelical.com\/?p=24529"},"modified":"2024-04-24T18:10:35","modified_gmt":"2024-04-24T16:10:35","slug":"digitalisation-for-building-energy-simulation","status":"publish","type":"post","link":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/","title":{"rendered":"Digitalisation for building energy simulation"},"content":{"rendered":"
\"\"<\/div>\n

 <\/p>\n

BIM technology can help us reduce the energy we consume, manage and pay for, and, at the end, make our built environment more sustainable. So far, this isn\u2019t breaking news. What\u2019s the state of the art in this field? Are we ready to set our engines at full speed to make cities more livable? What are our capabilities and limitations?<\/span><\/p>\n

To answer those questions we joined the BuildSim Nordic 2022 international convention, hosted by the International Building Performance Simulation Association, more precisely its Scandinavian delegation IBPSA-Nordic. IBPSA is a non-profit international society of <\/span>building performance simulation<\/span><\/a> researchers, developers and practitioners. It has been improving the built environment since 1987. In this article we\u2019ll share with you our findings.<\/span><\/p>\n

This document covers: general introduction to Building Energy Modeling (BEM), connection between BIM and BEM, types of BEMs with regard to their connection to BIM, a general comment about energy data authoring and transfer, the capabilities and limitations of the process and a conclusion. Spoiler alert: energy assessment can and should be considered a BIM use. Let\u2019s go for it!<\/span><\/p>\n

Building Energy Modeling<\/h3>\n

Building performance simulations run upon Building Energy Models (BEM). Let\u2019s explain this key concept: a BEM is a digital representation of the energy of our asset, which can be a building, a district or a whole city. It might refer to energy that was already consumed, and it might as well refer to a forecast of supplies or consumptions. Surprisingly, the BEM size won\u2019t condition the tools used to manage it, technology won\u2019t differ whether it deals with a building, a neighborhood or a city, but we\u2019ll come to that later.<\/span><\/p>\n

Albeit BEM definition focuses on energy, practitioners also use this term to refer to models that represent other resources such as water or gas. BEMs can be as simple as schedules or diagrams without geometrical information, and as complex as digital twins that get involved in GMAO systems.<\/span><\/p>\n

Historically, BEMs have been developed without connection to BIM technology, only in recent years the industry has started to couple them.<\/span><\/p>\n

Connection between BIM and BEM<\/h3>\n

In regard to the connection between BIM and BEM technologies, we can differentiate two main types of BEMs: low precision and high precision BEMs. It\u2019s important to distinguish them because each of them will have very different requirements, tools, capabilities and limitations.<\/span><\/p>\n

Low precision BEMs<\/h4>\n

They usually get involved during concept design and they require very little information, general volumetry of our building can be enough to set them running. They help us answer general questions such as: \u201cIs this design more efficient than the previous, qualitatively talking?\u201d \u201cHow should my windows be distributed to minimize artificial lighting consumption?\u201d \u201cIs this the optimal volumetric distribution if I want to minimize climatization energy?\u201d. This BEMs are easy to produce with BIM models at early design stages. Practitioners usually rely on them to run yearly estimations, rather than monthly, daily or hourly estimations. In this field, the use of Rhino and Grasshopper is widely extended to host energy simulations, both with Ladybug plugin as well as custom Grasshopper based tools.<\/span><\/p>\n

\"\"<\/p>\n

District scale daylight simulation. How can generative design impact daylight design? Jakob Str\u00f8mann-Andersen<\/span><\/em><\/h5>\n

Ladybug is a plugin for Grasshopper, it is very user friendly and it allows us to: analyze climate data, run several energy simulations and optimisations or compute fluid dynamics, among others. Many architectural offices use Ladybug to analyze the energy behavior of their projects at a concept design stage, it\u2019s the case of danish Henning Larsen.<\/span><\/p>\n

This article won\u2019t dive into the procedures that connect Rhino with BIM tools, as they are widely documented elsewhere, from simple export-import procedures to the use or RhinoInside. Once on the Rhino – Grasshopper environment, we can use Ladybug or develop other automatisms ourselves. <\/span><\/p>\n

High precision BEMs<\/h4>\n

They usually get involved from detailed design to operational stage. They require substantially more information than low precision BEMs and provide more advanced results. They are commonly used to create monthly, daily or hourly simulations. In this field, EnergyPlus based tools are predominantly used.<\/p>\n

\"\"<\/p>\n

\u00a0IDA ICE 5: Plant modeling and other usability features. Equa.<\/span><\/em><\/h5>\n

Let\u2019s take as an example the case of study of Lise Slama: \u201cA BEE process for BIM energy-environment\u201d. He built a BIM model with basic architectural elements: floors, walls, doors, windows, roofs, fa\u00e7ades. He exported it to IFC and used it to build an energy model with ClimAUDIT. In such BEM he declared energetic spaces, thermal bounding elements and climate conditions. Then he detected thermal bridges along the fa\u00e7ade. As we can see, it\u2019s more complex to generate a high precision BEM than a low precision one. It requires more effort and more data and it provides more advanced results.<\/span><\/p>\n

Today it\u2019s clear that there\u2019s no fluent interoperability between BIM and BEM tools, the industry uses very limited export-import workflows to connect them. These workflows are characterized by:<\/span><\/p>\n

    \n
  • – They can rely on two file formats: .ifc (mostly used in Europe) or .gbxml (mostly used in EEUU).<\/li>\n
  • – Geometry is usually the key data to transfer.<\/li>\n
  • – They are unidirectional: there\u2019s a way BIM > BEM, there\u2019s no way back BEM > BIM.<\/li>\n<\/ul>\n

    \"\"<\/p>\n

    \u00a0The energy performance gap revisited. Pieter the Wilde.<\/span><\/em><\/p>\n

    Who authors energetic data?<\/h3>\n

    As we talk about BIM>BEM data transfering we face this question: who authors energetic data? We find it pertinent as it impacts very delicate issues: data responsibility and adequacy. It\u2019s common to use BIM models to generate volumetric shells, such volumetric shells can be the starting point of BEMs. No doubt in that regard, nonetheless\u2026 let\u2019s ask ourselves: could BIM provide more than geometry? It could, BIM could also fed occupational schedules and material thermal or luminous properties, for instance. For those who are not familiar with the term, an occupational schedule is a forecast of spaces habitation. For example: a bedroom of a house could have an occupation schedule that states: there will be people in this room from 22h to 08h during working days in winter. This information is used to estimate the climatisation loads that a certain space will need, and it can, as a matter of fact, be declared at the BIM model and transferred to the BEM. The same happens to thermal transmittance coefficients, reflectivity ratios or illuminance factors.<\/p>\n

    So far so good, we know that BIM can provide more than volumetric shells, the question is: should BIM provide more than geometry? In this regard, energy simulation experts provide clear advise: it\u2019s better not to transfer semantic data from architects to energy experts, as it creates issues with adequacy and responsibility. In other words: they advise us to import just geometry, unless semantic data is properly cared for. BIM users are usually architectural designers without a deep knowledge of the energy simulation field. If energy information is fed by a non expert it\u2019s very likely that it won\u2019t be reliable. Energy simulation experts shouldn\u2019t rely on data fed by non experts, such data is commonly based on default assumptions, which most of the times won\u2019t correspond to the specific case. Energy simulation experts should be in charge of characterizing such information, in order for them to guard its adequacy. At the end it all comes down to a matter of common sense: if you cannot backup data, don\u2019t write it.<\/p>\n

    What happens at the BEM side?<\/h3>\n

    Ok bimers, now we know how to reach BEM from BIM. We have crossed the bridge between technologies and we\u2019re on the other side. It\u2019s time to introduce the queen tool of high precision BEMs: EnergyPlus. <\/span><\/p>\n

    EnergyPlus is the most used and powerful tool to host building energy simulations. It accepts inputs such as geometry or weather data. It reports outputs such as: electric consumptions, heat loads or lighting demands. EnergyPlus was developed by the United States Department of Energy in 1996 for internal use, since then it has been publicly updated as a free and open source software. EnergyPlus is not a user friendly tool, that\u2019s why many other tools provide a friendly interface while running EnergyPlus as a background engine, that\u2019s why we call them EnergyPlus based tools. IDA ACE, OpenStudio or Design Builder are among the most used ones, but there are many more, each with its strengths and limitations.<\/span><\/p>\n

    As a matter of fact, Ladybug also uses EnergyPlus to compute, because it runs OpenStudio in the background. Why don\u2019t we explain it as an EnergyPlus based tool? because the user experience is almost blind to this fact. Anyone familiar with visual programming can get familiar with Ladybug easily, without even noticing that EnergyPlus exists. That\u2019s the situation of many BIM practitioners. On the other side, we call \u201cEnergyPlus based tools\u201d to those which will sooner or later require us to get deeper in the logics and requirements of EnergyPlus ins and outs.<\/span><\/p>\n

    Capabilities<\/h4>\n

    Cheers for us! We start to know how life looks like at the BEM side. Let\u2019s say we want to extract the geometry of our asset from our BIM model and feed it to an EnergyPlus based tool. Which are our capabilities? As we have stated, we can rely on .ifc or .gbxml formats. Both have in common:<\/p>\n

      \n
    1. Geometry can be updated in the energy simulation tool. We might have to update manually the part that changed in the BEM, as BEM tools are not that smart when working with external references, but we won\u2019t have to start from scratch.<\/span><\/li>\n
    2. Optimization can happen. EnergyPlus based tools are susceptible of coupling with optimization engines, therefore allowing to: find the best solution considering several variables, prioritizing: investment cost, cooling power or openings size. For example, energy modeling software IDA ICE can couple with optimizing engines AutoMOO or GenOpt.<\/span><\/li>\n
    3. At an operational stage, can digitalisation help me analyze the consumptions of my building? Yes, we can install smart energy metering devices, and process the data based on statistics. Researcher Tilman Gauer developed an algorithm to:<\/span>
      \n<\/span>– Measure the total energy use of a building.<\/span>
      \n<\/span>– Disaggregate such measurement into: energy for space heating and energy for hot domestic water. This step was developed following a top-down approach, which bases its assumptions on statistics.\u00a0<\/span><\/li>\n
    4. At the BEM side there is no scale limitation. Energy simulation engines are more than capable of handling simulations at a district or city scale, both at a concept design stage (Rhino based tools) as in a detailed design or operational stage (EnergyPlus based tools). Our limit will depend on the size of the .ifc or .gbxml file that we can produce.\u00a0<\/span><\/li>\n
    5. Can energy simulation engines help us obtain sustainability certificates? Yes, they can. For instance, IDA ICE and Scene software can help us justify BREEAM and Leed requirements in regard to thermal behavior or daylight simulation.<\/span><\/li>\n
    6. Are there any standards that could help us develop district scale energy models? Yes, indeed. ASHRAE has developed the DESTEST standard (District Energy Simulation Test), which provides good practices to model district energy models. It applies both to building scale and district scale energy networks.<\/span><\/li>\n
    7. Is the IFC standard becoming energy simulation aware? Yes, it is. For instance, the last IFC standard: IFC4 has improved the entity IfcRelSpaceBoundary, which will help us deal with relations between spaces and elements. The improvement is only available in IFC4,\u00a0 practitioners rarely take advantage of it. The configuration of this entity in the IFC will be key to enable energy simulation.<\/span><\/li>\n<\/ol>\n

      Limitations<\/h4>\n

      This all sounds great, we\u2019re eager to use BIM for BEM, now let\u2019s face the bad news, what are our limitations?<\/p>\n

        \n
      1. Let\u2019s say that we have developed a BIM model for uses different than energy simulation, can we use it now for energy simulation? In most cases the answer will be no. Models have to fulfill particular requirements to enable energy simulation, if this was not considered from the beginning we\u2019ll hardly be able to use them.<\/span><\/li>\n
      2. Can any .ifc or .gbxml enable energy simulation? No. Elements must be organized in a specific structure of hierarchy. For example, in the case of an IFC file, a window must be saved below: IfcSite – IfcFloor – IfcSpace – IfcWall – IfcWindow. Otherwise, the software won\u2019t be able to consider it for, let\u2019s say, daylight simulation or thermal behavior simulation.<\/span><\/li>\n
      3. Geometry must be clean. This is simple to say albeit it\u2019s the main headache of the process. Lise Slama explained a case study with ClimaBIM, an EnergyPlus based tool. The exercise used an IFC file to report thermal bridges of a 3 storeys residential unit. He recognised that processing geometry was the biggest challenge when using BIM models for energy simulations. Geometry issues consumed more than half the time of development.<\/span><\/li>\n
      4. BIM model would better have energy spaces declared and they might be different than architectural ones. The space is the elementary entity that enables energy simulation. In the field of energy simulation, spaces are delineated with different criteria than architectural ones. Picture yourself setting the boundary lines of such spaces, then think of questions such as: \u201cShould this wall be splitted between spaces?\u201d, \u201cShould this fa\u00e7ade be included in a certain space?\u201d, \u201cShould this terrace be considered part of the dwelling?\u201d When delineating the space, the answers will differ from architectural spaces to energetic ones, as architectural spaces are declared for surface management, and energy spaces are declared for energy simulation. From a surface management point of view we would never split spaces based on the thermal properties of a wall, while such decision could make complete sense when declaring spaces for energy simulation. Therefore, we might need to declare different spaces for each discipline.<\/span><\/li>\n
      5. About the gap between simulation and reality: can we expect exact correspondence between simulated results and reality? No. This gap is a complete field of research in the academia. There are several uncertainties that impact that gap: weather, use of the building, occupation behavior, final constructive solutions. There are even aspects that cannot be foreseen when simulating, such as the deterioration of elements. These are the reasons why simulations will differ from reality most of the times. Can we expect this gap to narrow in the future? Research gives us no reason to expect so, not in the short term nor in the long term future.<\/span><\/li>\n
      6. Can Machine learning help us reduce the gap? According to expert Pieter the Wilde this cannot be taken for granted. Machine learning must be handled with care, we have to guard where the tool is trained, as we cannot extrapolate energy simulations across building sizes.<\/span><\/li>\n
      7. It\u2019s clear that we have workflows BIM > BEM, is there a way back BEM > BIM? The industry is not mature in this regard, few tailor made processes have been tested but they are fragile and non-transferable along projects or practitioners. Nonetheless, we expect this topic to evolve in the following years.<\/span><\/li>\n<\/ol>\n

        Conclusion<\/h3>\n

        To conclude we can state that BIM models can enable energy simulation. Despite its limitations, it can be a profitable exercise. We already look after information for uses we normalize, let\u2019s use it! It\u2019s time to recognise that our energy behavior is relevant enough to place it on the table as any other discipline. It\u2019s time to add energy assessment to the list of our default BIM uses. It\u2019s time to integrate energy practitioners in our workflows. It\u2019s time to reduce the resources we consume, manage and pay. Digitalisation can ease us the way. We have today the ability of evaluating the energetic repercussion of our decisions, the tools to align with a less consumerist built environment, and the social responsibility of doing so. Today, taking care of our energy is a matter of choice.<\/p>\n","protected":false},"excerpt":{"rendered":"

          BIM technology can help us reduce the energy we consume, manage and pay for, and, at the end, make our built environment more sustainable. So far, this isn\u2019t breaking news. What\u2019s the state of the art in this field? Are we ready to set our engines at full speed to make cities more livable? […]<\/p>\n","protected":false},"author":64,"featured_media":26862,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[707],"tags":[518,471,658,411],"class_list":["post-24529","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cases","tag-blog-congress","tag-blog-news","tag-industry-energy","tag-technology-revit"],"acf":[],"yoast_head":"\nDigitalisation for building energy simulation - Modelical<\/title>\n<meta name=\"description\" content=\"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Digitalisation for building energy simulation - Modelical\" \/>\n<meta property=\"og:description\" content=\"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/\" \/>\n<meta property=\"og:site_name\" content=\"Modelical\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/Modelical\/\" \/>\n<meta property=\"article:published_time\" content=\"2022-12-13T09:39:23+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-04-24T16:10:35+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"400\" \/>\n\t<meta property=\"og:image:height\" content=\"250\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Roberto Molinos\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@modelical\" \/>\n<meta name=\"twitter:site\" content=\"@modelical\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Roberto Molinos\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"13 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/\"},\"author\":{\"name\":\"Roberto Molinos\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/#\\\/schema\\\/person\\\/3ad52fd99e6b5b98a59ef24c76a7c2d5\"},\"headline\":\"Digitalisation for building energy simulation\",\"datePublished\":\"2022-12-13T09:39:23+00:00\",\"dateModified\":\"2024-04-24T16:10:35+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/\"},\"wordCount\":2649,\"commentCount\":0,\"image\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.modelical.com\\\/wp-content\\\/uploads\\\/2022\\\/12\\\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png\",\"keywords\":[\"Blg Congress\",\"Blg News\",\"Ind Energy\",\"Tec Revit\"],\"articleSection\":[\"Case studies\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/\",\"url\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/\",\"name\":\"Digitalisation for building energy simulation - Modelical\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.modelical.com\\\/wp-content\\\/uploads\\\/2022\\\/12\\\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png\",\"datePublished\":\"2022-12-13T09:39:23+00:00\",\"dateModified\":\"2024-04-24T16:10:35+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/#\\\/schema\\\/person\\\/3ad52fd99e6b5b98a59ef24c76a7c2d5\"},\"description\":\"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset\",\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/digitalisation-for-building-energy-simulation\\\/#primaryimage\",\"url\":\"https:\\\/\\\/www.modelical.com\\\/wp-content\\\/uploads\\\/2022\\\/12\\\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png\",\"contentUrl\":\"https:\\\/\\\/www.modelical.com\\\/wp-content\\\/uploads\\\/2022\\\/12\\\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png\",\"width\":400,\"height\":250,\"caption\":\"Digitalisation for building energy simulation\"},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/#website\",\"url\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/\",\"name\":\"Modelical\",\"description\":\"We build information\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/#\\\/schema\\\/person\\\/3ad52fd99e6b5b98a59ef24c76a7c2d5\",\"name\":\"Roberto Molinos\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro\",\"caption\":\"Roberto Molinos\"},\"sameAs\":[\"https:\\\/\\\/www.modelical.com\"],\"url\":\"https:\\\/\\\/www.modelical.com\\\/en\\\/author\\\/roberto\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Digitalisation for building energy simulation - Modelical","description":"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/","og_locale":"en_US","og_type":"article","og_title":"Digitalisation for building energy simulation - Modelical","og_description":"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset","og_url":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/","og_site_name":"Modelical","article_publisher":"https:\/\/www.facebook.com\/Modelical\/","article_published_time":"2022-12-13T09:39:23+00:00","article_modified_time":"2024-04-24T16:10:35+00:00","og_image":[{"width":400,"height":250,"url":"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png","type":"image\/png"}],"author":"Roberto Molinos","twitter_card":"summary_large_image","twitter_creator":"@modelical","twitter_site":"@modelical","twitter_misc":{"Written by":"Roberto Molinos","Est. reading time":"13 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#article","isPartOf":{"@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/"},"author":{"name":"Roberto Molinos","@id":"https:\/\/www.modelical.com\/en\/#\/schema\/person\/3ad52fd99e6b5b98a59ef24c76a7c2d5"},"headline":"Digitalisation for building energy simulation","datePublished":"2022-12-13T09:39:23+00:00","dateModified":"2024-04-24T16:10:35+00:00","mainEntityOfPage":{"@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/"},"wordCount":2649,"commentCount":0,"image":{"@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#primaryimage"},"thumbnailUrl":"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png","keywords":["Blg Congress","Blg News","Ind Energy","Tec Revit"],"articleSection":["Case studies"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/","url":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/","name":"Digitalisation for building energy simulation - Modelical","isPartOf":{"@id":"https:\/\/www.modelical.com\/en\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#primaryimage"},"image":{"@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#primaryimage"},"thumbnailUrl":"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png","datePublished":"2022-12-13T09:39:23+00:00","dateModified":"2024-04-24T16:10:35+00:00","author":{"@id":"https:\/\/www.modelical.com\/en\/#\/schema\/person\/3ad52fd99e6b5b98a59ef24c76a7c2d5"},"description":"Building performance simulations run upon Building Energy Models (BEM). A BEM is a digital representation of the energy of our asset","inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.modelical.com\/en\/digitalisation-for-building-energy-simulation\/#primaryimage","url":"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png","contentUrl":"https:\/\/www.modelical.com\/wp-content\/uploads\/2022\/12\/DigitalizationForBuildingEnergySimulation_EN_web-400x250-1.png","width":400,"height":250,"caption":"Digitalisation for building energy simulation"},{"@type":"WebSite","@id":"https:\/\/www.modelical.com\/en\/#website","url":"https:\/\/www.modelical.com\/en\/","name":"Modelical","description":"We build information","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.modelical.com\/en\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/www.modelical.com\/en\/#\/schema\/person\/3ad52fd99e6b5b98a59ef24c76a7c2d5","name":"Roberto Molinos","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro","url":"https:\/\/secure.gravatar.com\/avatar\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/9346c12c96cb942be9bb8b2454e296662a1baa0b4cd461ab315ae9a5185b0db6?s=96&d=initials&r=g&initials=ro","caption":"Roberto Molinos"},"sameAs":["https:\/\/www.modelical.com"],"url":"https:\/\/www.modelical.com\/en\/author\/roberto\/"}]}},"_links":{"self":[{"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/posts\/24529","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/users\/64"}],"replies":[{"embeddable":true,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/comments?post=24529"}],"version-history":[{"count":0,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/posts\/24529\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/media\/26862"}],"wp:attachment":[{"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/media?parent=24529"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/categories?post=24529"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.modelical.com\/en\/wp-json\/wp\/v2\/tags?post=24529"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}