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OpenStudio is a cross-platform collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. This disclosure includes two OpenStudio measures: (1) data center prototype models, and (2) occupant schedule generator. The data center models cover two sizes (small computer server rooms, stand-alone large data centers) and two IT load densities (average and high).
The Legacy OpenStudio® SketchUp Plug-in makes it easy to create and edit the building geometry in EnergyPlus® input files. This free plug-in also allows you to launch EnergyPlus simulations and view the results without leaving the SketchUp 3D drawing program. Note that active OpenStudio development has moved from the Legacy OpenStudio Plug-in to the more comprehensive OpenStudio suite of tools and libraries found here: https://github.com/NREL/OpenStudio. More information can be found at http://openstudio.net. The OpenStudio Legacy Plug-in has been relaunched as Euclid by Big Ladder Software, the project's new homepage is http://bigladdersoftware.com/projects/euclid/. The Legacy OpenStudio Plug-in was created by the National Renewable Energy Laboratory for the U.S. Department of Energy as an interface to the EnergyPlus simulation engine. Refer to the EnergyPlus webpage at energyplus.gov for an overview of the concept and features. User support is available via the community moderated question and answer resource unmethours.com.
OpenStudio-HPXML allows running residential EnergyPlus™ simulations using an HPXML file for the building description. It is intended to be used by user interfaces or other automated software workflows that automatically produce the HPXML file. OpenStudio-HPXML can accommodate a wide range of different building technologies and geometries. End-to-end simulations typically run in 3-10 seconds, depending on complexity, computer platform and speed, etc. For more information on running simulations, generating HPXML files with the appropriate inputs to run EnergyPlus, etc., please visit the documentation linked below. https://openstudio-hpxml.readthedocs.io/en/latest
OpenStudio’s performance has not historically been an area of much work, but as it has successfully replaced ad hoc model generation solutions, the performance of the software is more and more central to continuing success. This report describes an initial effort to profile OpenStudio, describes the problems encountered, the solutions to those problems, and some early recommendations for further work should funding become available. The approach taken here is to use special software, referred to as profilers, to assess the code and how it executes. This approach is more appropriate for this kind of software than the checkpoint-style timing that is often done with numerical codes. Profiling was most successful on the MacOS platform, where Apple’s Instruments software was able to decipher the complexities of OpenStudio’s command line execution of a workflow. Even with the limited exploration of performance done here, the team quickly ran into limitations imposed on the code by the stateless architecture, and the team recommends an evaluation of this architecture as a good next step to improve performance.
BRICR is software for translating NREL's BuildingSync™ XML (BSXML) to OpenStudio® Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format. BRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation "Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)": https://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits
BRICR is software for translating NREL's BuildingSync™ XML (BSXML) to OpenStudio® Workflow (OSW) files for simulation. Each BSXML contains information about a building as well as multiple possible energy efficiency upgrade options. An OSW file is created and run for each possible efficiency upgrade, the results of all simulations are stored in BSXML format. BRICR was jointly developed by NREL and LBNL for the San Francisco BayREN: Integrated Commercial Retrofits (BRICR) project funded under the DOE solicitation "Solutions to Improve the Energy Efficiency of U.S. Small and Medium Commercial Buildings (DE-FOA-0001385)": https://www.energy.gov/eere/buildings/downloads/san-francisco-bayren-integrated-commercial-retrofits
'simuwatt Energy Auditor' (TM) is a new tablet-based electronic auditing tool that is designed to dramatically reduce the time and cost to perform investment-grade audits and improve quality and consistency. The tool uses the U.S. Department of Energy's OpenStudio modeling platform and integrated Building Component Library to automate modeling and analysis. simuwatt's software-guided workflow helps users gather required data, and provides the data in a standard electronic format that is automatically converted to a baseline OpenStudio model for energy analysis. The baseline energy model is calibrated against actual monthly energy use to ASHRAE Standard 14 guidelines. Energy conservation measures from the Building Component Library are then evaluated using OpenStudio's parametric analysis capability. Automated reporting creates audit documents that describe recommended packages of energy conservation measures. The development of this tool was partially funded by the U.S. Department of Defense's Environmental Security Technology Certification Program. As part of this program, the tool is being tested at 13 buildings on 5 Department of Defense sites across the United States. Results of the first simuwatt audit tool demonstration are presented in this paper.
The National Renewable Energy Laboratory (NREL) and Wrightsoft Corporation will advance commercialization of a residential building energy software product that uses DOE's flagship open-source OpenStudio and EnergyPlus simulation ecosystem for calculation of the Energy Rating Index (ERI).
Alfalfa is a web based software service that implements a virtual building control system using the EnergyPlus simulation as a backend. Conventional building energy simulation is non interactive, meaning that a simulation is started and run to completion without any user input during the simulation. Alfalfa allows a client to start a building simulation, then interactively read sensor locations and dynamically command actuators in realtime. The Alfalfa web service conforms to the Project Haystack standard, which is a specification adopted by many building control system vendors. The service enables Haystack compliant control system vendors to test their control modules and algorithms without the need for a physical building or modifying their hardware and software, enabling faster and cheaper development cycles. Alfalfa has use cases beyond control system testing. One example is building fault detection, where physical building performance can be compared to simulated values in realtime, indicating where there may be a problem in the building. Another use case is informing predictive control systems, where near future events are simulated to premptively guide control decisions in the real building. This software is web based and designed to be self service. Users of Alfalfa can upload an OpenStudio building model and begin communicating with the simulated building without any advanced setup or configuration, as if they were communicating a real building control system. Behind the scenes, Alfalfa makes extensive use of Amazon Web Services, in order to scale from a very small number of users and buildings, to extremely large numbers in a cost effective way.
This project proposes to integrate the NREL-developed OpenStudio (OS) and its accompanying Analytical Framework (OSAF) into Autodesk’s (ADSK’s) market leading suite of building information modeling (BIM) tools. As a result, BIM users will gain access to advanced (but user-friendly) building energy modeling (BEM), calibration, and design optimization capabilities. Following integration, the BIM software will automatically generate a consistent OS-based BEM model, allowing users to develop projects in an integrated manner, moving back and forth between architectural and engineering perspectives without redundancy or data loss, saving time and effort.
Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.
ComStock™ is an NREL model of the U.S. commercial building stock. The model takes some building characteristics from the U.S. Department of Energy's (DOE's) Commercial Prototype Building Models and Commercial Reference Building. However, unlike many other building stock models, ComStock also combines these with a variety of additional public- and private-sector data sets. Collectively, this information provides high-fidelity building stock representation with a realistic diversity of building characteristics. This repository contains the source code used to build and execute ComStock models, including upgrade scenarios. In addition, the sampling of buildings characteristics used for the initial ComStock (V1.0) release is provided. The ComStock model is under active calibration and development, which is publicly visible on this repository. Execution of the ComStock workflow is managed through the buildstockbatch repository, a shared asset of ResStock™ and ComStock™ , specifically developed to scale to execution of tens of millions of simulations through multiple infrastructure providers. The dataset output from the initial ComStock (V1.0) release can be found at the accompanying ComStock data viewer website and additional information about ComStock found on the NREL Buildings Website. For more details about ongoing model development please consult the End Use Load Profiles website. ComStock is a direct result of the NREL residential stock modeling tool ResStock™ (recipient of a R&D100 award) and was inspired by the high-fidelity solar & storage adoption model dGen™. Additionally, this tool would not be possible without the decades of work undertaken by the OpenStudio® and EnergyPlus® visionaries and contributors, significant funding, feedback and support from the Los Angeles Department of Water and Power, and the Department of Energy's Building Technology Office ongoing support of and investment in building energy modeling software. is an analytic methodology for modeling the energy usage of the commercial building stock within the United States of America. The commercial building stock is represented through a sampling of complex probabilistic distributions of various features of interest for modeling energy usage within commercial buildings. Each sample from these distributions is converted into a building energy model based on the features of that specific sample. Each building energy model can be simulated as is, but additional changes can be made to the model through addition of energy conservation measures, component faults, or other desired alterations. The results of the simulations are then processed to provide insights for various stakeholders, including but not limited to policy makers, engineers, and marketers.
BayREN Integrated Commercial Retrofits (BRICR) is a DOE-funded project which aims to enhance the capacity of energy efficiency programs to recruit participants, develop retrofits, and measure outcomes in small and medium-sized commercial buildings, a sector notoriously hard to reach and expensive to serve, that accounts for 2/3 of US commercial floor space. To address these barriers, BRICR leverages existing incentives, financing, data, and open source software to facilitate two paths for comprehensive improvements: a deep energy retrofit, or serial upgrades integrated into capital improvement and maintenance cycles. BRICR is developing an integrated workflow for iterative energy modeling of commercial buildings for city energy program managers and auditors - starting with mass building-scale simulation based on public records and proceeding through audit, retrofit, and measurement and verification stages. BRICR builds on existing tools including LBNL’s CBES, NREL’s OpenStudio, PNNL’s Audit Template, and DOE’s BuildingSync and SEED PlatformTM. At each stage, BRICR uses available information to inform simulations (starting with public records but iteratively augmented with observations from energy program staff) to improve the quality of the models that inform decision making. This paper presents initial results from energy models of 1699 office and retail buildings in San Francisco. Building stock data from public records were translated to create a BuildingSync file for each building which was stored in SEED. Each BuildingSync file was then translated to multiple OpenStudio Workflow files for EnergyPlus simulation to estimate energy savings of energy conservation measures (ECM). Energy savings predictions for each ECM were written back to an updated BuildingSync file for each building and re-uploaded to SEED. The distribution of baseline energy simulations was calibrated against the publicly disclosed distribution of energy benchmarking data to increase confidence in results.
Interoperability is a particular challenge in building energy auditing, in which tools and data requirements may vary widely depending upon locale or intended use of the audit result. There are, however, many reasons to represent the data in a common format. BuildingSync (R) is such an effort to develop a standardized language to flexibly represent and exchange building energy auditing data between software tools. The schema has been developed with extensive collaboration between the United States Department of Energy (DOE) and industry experts. BuildingSync facilitates a consistent history of energy audit data across the life of a building or a group of buildings, and thus enables lower costs and higher energy performance results. It also facilitates easier aggregation and analysis of audits conducted by different companies using different software. This paper presents two examples of building energy analysis efforts that are utilizing BuildingSync - (1) BayREN Integrated Commercial Retrofits (BRICR), a utility custom incentive program at the Bay Area Regional Energy Network (BayREN) that uses BuildingSync to exchange building data, and (2) New York City's ordinance on benchmarking and auditing data. These efforts utilize BuildingSync in conjunction with other DOE-sponsored tools, such as the Asset Score Reporting Platform, SEED Platform, and OpenStudio. Using the lessons learned from these efforts, the paper also makes recommendations for applicability to future projects that may benefit from BuildingSync.
Floorspace.js is a 2D geometry editor. Users can define an explicit floor plan for each story of a building. A story-by-story interface makes it easy to develop space geometry and assign properties. Referencing satellite imagery or floor plan images, when available, speeds up geometry entry. Conversion of 2D to 3D geometry is currently out of scope for Floorspace.js, a reference implementation is available in the OpenStudio® SDK. Explicit floor plans allow more building-specific information than parameterized shoe-boxes but less information than a full 3D BIM model. Sloped walls, complex roofs, detailed shading structures, and other complex 3D structures are out of FloorspaceJS's scope. In general, if users have a 3D BIM model in a tool that can export a useful BEM representation then it is better to use that export than to recreate a new model using FloorspaceJS. Re-usability and minimal dependencies were key design considerations for software developers. Web technologies can be used in both online and desktop applications. The editor was written in pure JavaScript for maximum portability and re-usability. A custom JavaScript Object Notation (JSON) file format was developed to ease integration with other applications. Custom JSON schema design was a key part of FloorspaceJS development.
The 5-year goal of the 'Model America' concept was to generate a model of every building in the United States. This data repository delivers on that goal. Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,714,640 buildings detected in the United States and this dataset contains 122,930,327 (97.8%) buildings which resulted in a successful simulation. Future, annual updates have been proposed that may include additional buildings, data improvements, or other algorithmic enhancements. This dataset of 122.9 million buildings includes: Models (state_county.zip) - OpenStudio (v3.1.0) and EnergyPlus (v9.4) building energy models. Please note that the download requires the free Globus Connect Personal (https://www.globus.org/globus-connect-personal); Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus(v9.4) 2,784-page Input/Output Reference Guide (https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf) for everything that can be retrieved or simulated from these models. These models were derived from the following metadata, which is not included in this dataset: 1. ID - unique building ID 2. County - county name 3. State - state name 4. CZ - ASHRAE Climate Zone designation 5. Clim_Zone - text label of climate zone 6. est_year - estimated year of construction 7. est_commercial - estimated building type (0=residential, 1=commercial) 8. Centroid - building center location in latitude/longitude (from Footprint2D) 9. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 10. Height - building height (meters) 11. Area2D - footprint area (ft2) 12. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 13. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 14. NumFloors - number of floors (above-grade) 15. Area - estimate of total conditioned floor area (ft2) 16. Standard - building vintage. These models are made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy's (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. Please cite as: New, Joshua R., Adams, Mark, Bass, Brett, Berres, Anne, and Clinton, Nicholas (2021). 'Model America - data and models of every U.S. building. [Data set].' Constellation, doi.ccs.ornl.gov/ui/doi/339, April 14, 2021
The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.
Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM).Two sets of sample data are provided for 2,555,152 buildings located within the boundary of Arizona in the United States:Data (846.3MB *.csv) - minimalist list of each building (rows) for the following fields (columns) • ID - unique building ID • Centroid - building center location in latitude/longitude (from Footprint2D) • Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) • State_abbr - state name • Area - estimate of total conditioned floor area (ft2) • Area2D - footprint area (ft2) • Height - building height (ft) • NumFloors - number of floors (above-grade) • WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) • CZ - ASHRAE Climate Zone designation • BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards • Standard - building vintage • Sample Models (114GB*.zip by county) - OpenStudio and EnergyPlus building energy models named according to IDThis data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).