From 93fe5894bbf7edd8902a9a3d15916630eb08a15e Mon Sep 17 00:00:00 2001 From: "Lerond, Jeremy" Date: Thu, 4 Apr 2024 15:22:19 -0700 Subject: [PATCH 01/29] Add action and very first draft of the paper. --- .github/workflows/draft-pdf.yml | 23 +++++++++++++++ docs/paper.bib | 34 +++++++++++++++++++++ docs/paper.md | 52 +++++++++++++++++++++++++++++++++ 3 files changed, 109 insertions(+) create mode 100644 .github/workflows/draft-pdf.yml create mode 100644 docs/paper.bib create mode 100644 docs/paper.md diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml new file mode 100644 index 00000000..dab4a823 --- /dev/null +++ b/.github/workflows/draft-pdf.yml @@ -0,0 +1,23 @@ +on: [push] + +jobs: + paper: + runs-on: ubuntu-latest + name: Paper Draft + steps: + - name: Checkout + uses: actions/checkout@v4 + - name: Build draft PDF + uses: openjournals/openjournals-draft-action@master + with: + journal: joss + # This should be the path to the paper within your repo. + paper-path: ./docs/paper.md + - name: Upload + uses: actions/upload-artifact@v1 + with: + name: paper + # This is the output path where Pandoc will write the compiled + # PDF. Note, this should be the same directory as the input + # paper.md + path: ./docs/paper.pdf \ No newline at end of file diff --git a/docs/paper.bib b/docs/paper.bib new file mode 100644 index 00000000..c1c33f54 --- /dev/null +++ b/docs/paper.bib @@ -0,0 +1,34 @@ +@misc {90.1, + title={ANSI/ASHRAE/IES 90.1-2019, Energy Standard for Buildings Except Low-Rise Residential Buildings}, + author={{ASHRAE}}, + organization={ASHRAE}, + institution={ASHRAE}, + address={Atlanta, GA}, + year={2019} +} + +@misc{tspr, + title={TSPR Washington State Analysis Tool}, + author={{Pacific Northwest National Laboratory}}, + howpublished={\url{https://energycode.pnl.gov/HVACSystemPerformance/}}, + note={Accessed: 2024-04-044} +} + +@report{impl_ctrl + title={Implementation of Energy Code Controls Requirements in New Commercial Buildings}, + author={{Rosenberg, M.I., P.R. Hart, M. Hatten, D. Jones, and M. Cooper}}, + year={2017} +} + +@report{impa_ctrl + title={Impacts of commercial building controls on energy savings and peak load reduction}, + author={{Fernandez, Nicholas EP, et al.}}, + year={2017} +} + +@misc{os, + title={OpenStudio}, + author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, + howpublished={\url{https://openstudio.net/}}, + note={Accessed: 2024-04-04} +} \ No newline at end of file diff --git a/docs/paper.md b/docs/paper.md new file mode 100644 index 00000000..292aa413 --- /dev/null +++ b/docs/paper.md @@ -0,0 +1,52 @@ +--- +title: 'Control Strainer (ConStrain): a data-driven control verification framework' +tags: + - python + - energy + - building + - control + - simulation + - hvac +authors: + - name: Xuechen Lei + orcid: 0000-0003-3310-9750 + affiliation: 1 + - name: Jérémy Lerond + orcid: 0000-0002-1630-6886 + affiliation: 1 + - name: Yun Joon Jung + orcid: 0000-0003-1311-8932 + affiliation: 1 + - name: Julian Slane-Holloway + affiliation: 1 + - name: Fan Feng + orcid: 0000-0002-6230-0063 + affiliation: 1 + - name: Yan Chen + orcid: 0000-0002-2988-9136 + affiliation: 1 + +affiliations: + - name: Pacific Northwest National Laboratory, Richland, WA, USA + index: 1 +date: 4 Avril 2024 +bibliography: paper.bib +--- + +# Summary + +The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of three distinct parts: a control verification algorithm library, an automated preparation process and verification case generation, and a standardized performance evaluation and reporting process. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind but it is built such that its library is expandable and can cover any type of customized control verifications. + +# Statement of need + +Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as ASHRAE 90.1 [90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on HVAC system control) [impl_ctrl]. + +However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement, and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. + +`ConStrain` can be used as a standalone tool and can also be integrated into existing workflows. `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [tspr]) to make sure that software code contributions as well as simulation software updates doesn't affect the simulated performance of building system controls. Moreover, a set of `OpenStudio` [os] measures have also been developed to provide enable energy modelers using this platform to have access to perform verification on their models with close to no setup. + +# Acknowledgements + +ConStrain was developed at the Pacific Northwest National Laboratory, and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. + +# References \ No newline at end of file From 0851c9fa10db5d1c67883b1d6a57b90edf82ec71 Mon Sep 17 00:00:00 2001 From: "Lerond, Jeremy" Date: Thu, 4 Apr 2024 15:23:30 -0700 Subject: [PATCH 02/29] Fix typo. --- docs/paper.bib | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index c1c33f54..a5cc7b16 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -14,13 +14,13 @@ @misc{tspr note={Accessed: 2024-04-044} } -@report{impl_ctrl +@report{impl_ctrl, title={Implementation of Energy Code Controls Requirements in New Commercial Buildings}, author={{Rosenberg, M.I., P.R. Hart, M. Hatten, D. Jones, and M. Cooper}}, year={2017} } -@report{impa_ctrl +@report{impa_ctrl, title={Impacts of commercial building controls on energy savings and peak load reduction}, author={{Fernandez, Nicholas EP, et al.}}, year={2017} From 95e88d1289bc8bc36840191419f28afaeb5d56fd Mon Sep 17 00:00:00 2001 From: "Lerond, Jeremy" Date: Thu, 4 Apr 2024 15:26:15 -0700 Subject: [PATCH 03/29] Fix references. --- docs/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 292aa413..2137f181 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -39,11 +39,11 @@ The Control Strainer, or `ConStrain`, is a python-based framework that can be us # Statement of need -Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as ASHRAE 90.1 [90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on HVAC system control) [impl_ctrl]. +Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as ASHRAE 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on HVAC system control) [@impl_ctrl]. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement, and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. -`ConStrain` can be used as a standalone tool and can also be integrated into existing workflows. `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [tspr]) to make sure that software code contributions as well as simulation software updates doesn't affect the simulated performance of building system controls. Moreover, a set of `OpenStudio` [os] measures have also been developed to provide enable energy modelers using this platform to have access to perform verification on their models with close to no setup. +`ConStrain` can be used as a standalone tool and can also be integrated into existing workflows. `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates doesn't affect the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures have also been developed to provide enable energy modelers using this platform to have access to perform verification on their models with close to no setup. # Acknowledgements From fdf851b4b6b06c737dcf80cc4bc16e67b187d4fd Mon Sep 17 00:00:00 2001 From: "Lerond, Jeremy" Date: Thu, 4 Apr 2024 15:33:23 -0700 Subject: [PATCH 04/29] Minor typos. --- docs/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 2137f181..66aa9d76 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -35,7 +35,7 @@ bibliography: paper.bib # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of three distinct parts: a control verification algorithm library, an automated preparation process and verification case generation, and a standardized performance evaluation and reporting process. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind but it is built such that its library is expandable and can cover any type of customized control verifications. +The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of three distinct parts: a control verification algorithm library, an automated preparation process and verification case generation, and a standardized performance evaluation and reporting process. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover any type of customized control verifications. # Statement of need @@ -47,6 +47,6 @@ However, one of the challenges to realizing those savings is the correct impleme # Acknowledgements -ConStrain was developed at the Pacific Northwest National Laboratory, and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. +ConStrain was developed at the Pacific Northwest National Laboratory and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. # References \ No newline at end of file From c83f34179f09a9021711268e8af85cb133aed272 Mon Sep 17 00:00:00 2001 From: "Lerond, Jeremy" Date: Fri, 26 Apr 2024 13:48:25 -0700 Subject: [PATCH 05/29] Fix typo and add Julian's ORCID. --- docs/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/paper.md b/docs/paper.md index 66aa9d76..70e8ce80 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -18,6 +18,7 @@ authors: orcid: 0000-0003-1311-8932 affiliation: 1 - name: Julian Slane-Holloway + orcid: 0009-0008-9572-9123 affiliation: 1 - name: Fan Feng orcid: 0000-0002-6230-0063 @@ -29,7 +30,7 @@ authors: affiliations: - name: Pacific Northwest National Laboratory, Richland, WA, USA index: 1 -date: 4 Avril 2024 +date: 4 April 2024 bibliography: paper.bib --- From ee21b7fff8a3987283cb72741eb9ef6854de8f58 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Tue, 28 May 2024 12:44:13 -0700 Subject: [PATCH 06/29] jxl mods --- docs/paper.bib | 7 +++++++ docs/paper.md | 8 ++++---- 2 files changed, 11 insertions(+), 4 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index a5cc7b16..78d14eb6 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -31,4 +31,11 @@ @misc{os author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, howpublished={\url{https://openstudio.net/}}, note={Accessed: 2024-04-04} +} + +@misc{osm, + title={OpenStudio SDK User Docs: Getting Started - About Measures}, + author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, + howpublished={\url{https://nrel.github.io/OpenStudio-user-documentation/getting_started/about_measures/}}, + note={Accessed: 2024-05-28} } \ No newline at end of file diff --git a/docs/paper.md b/docs/paper.md index 70e8ce80..d161b9e0 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -30,21 +30,21 @@ authors: affiliations: - name: Pacific Northwest National Laboratory, Richland, WA, USA index: 1 -date: 4 April 2024 +date: 28 May 2024 bibliography: paper.bib --- # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of three distinct parts: a control verification algorithm library, an automated preparation process and verification case generation, and a standardized performance evaluation and reporting process. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover any type of customized control verifications. +The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. # Statement of need -Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as ASHRAE 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on HVAC system control) [@impl_ctrl]. +Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement, and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. -`ConStrain` can be used as a standalone tool and can also be integrated into existing workflows. `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates doesn't affect the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures have also been developed to provide enable energy modelers using this platform to have access to perform verification on their models with close to no setup. +`ConStrain` can be used as a standalone tool and, with its Python Application Programming Interface (API), can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. # Acknowledgements From 42cf3e0bbf8d97e12a4006b1f2177effdf016854 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 17 Jun 2024 22:32:27 -0700 Subject: [PATCH 07/29] address comments --- docs/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index d161b9e0..e78a9caa 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -40,9 +40,9 @@ The Control Strainer, or `ConStrain`, is a python-based framework that can be us # Statement of need -Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. +Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. -However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement, and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. +However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctr], and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. `ConStrain` can be used as a standalone tool and, with its Python Application Programming Interface (API), can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. From 33e62a0da1bd83430783713a8e5fc3d5ebedf71d Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 17 Jun 2024 22:38:55 -0700 Subject: [PATCH 08/29] fix ref typo --- docs/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/paper.md b/docs/paper.md index e78a9caa..ad2a3f72 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -42,7 +42,7 @@ The Control Strainer, or `ConStrain`, is a python-based framework that can be us Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. -However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctr], and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. +However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. `ConStrain` can be used as a standalone tool and, with its Python Application Programming Interface (API), can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. From 80e766e51fe5a581a5e42990c472a2fc2a4abc67 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Tue, 6 Aug 2024 22:02:49 -0700 Subject: [PATCH 09/29] paper update --- docs/paper.bib | 17 ++++++++++++++++- docs/paper.md | 16 +++++++++++++--- 2 files changed, 29 insertions(+), 4 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 78d14eb6..f458b51d 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -7,6 +7,15 @@ @misc {90.1 year={2019} } +@misc {g36, + title={Guideline 36-2018. High-Performance Sequences of Operation for HVAC Systems}, + author={{ASHRAE}}, + organization={ASHRAE}, + institution={ASHRAE}, + address={Atlanta, GA}, + year={2021} + } + @misc{tspr, title={TSPR Washington State Analysis Tool}, author={{Pacific Northwest National Laboratory}}, @@ -38,4 +47,10 @@ @misc{osm author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, howpublished={\url{https://nrel.github.io/OpenStudio-user-documentation/getting_started/about_measures/}}, note={Accessed: 2024-05-28} -} \ No newline at end of file +} + +@misc {bto_blueprint, + title={Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, + author={{U.S. Department of Energy}}, + howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}} + note={Accessed:2024-07-30}} diff --git a/docs/paper.md b/docs/paper.md index ad2a3f72..6503ab4a 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -36,15 +36,25 @@ bibliography: paper.bib # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries generated from whole-building energy simulations or from actual building automation system trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. +The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations or from actual building automation system (BAS) trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. # Statement of need +Robust HVAC control is a “no regrets” strategy for building decarbonization, reducing energy use, enabling flexibility and resilience, and supporting the transition to electrified heating, all with low embodied carbon. The Buildings Technology Office (BTO) of the United States Department of Energy’s blueprint has a goal of “more than 50% of all homes and businesses have automated control platforms that reduce energy waste and enable flexibility“ [@bto_blueprint]. + Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. -However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. +However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. + +Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. + +`ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. + +`ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 @[g36]). + +`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. ConStrain has applications to code-compliance building performance standards (BPS), and commissioning. -`ConStrain` can be used as a standalone tool and, with its Python Application Programming Interface (API), can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. +`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. # Acknowledgements From 6e6f846a7b9afbdf6f4dfebcff7ec61794fdd8b8 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Wed, 7 Aug 2024 08:02:09 -0700 Subject: [PATCH 10/29] typo fix --- docs/paper.bib | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/paper.bib b/docs/paper.bib index f458b51d..6c3c2393 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -52,5 +52,5 @@ @misc{osm @misc {bto_blueprint, title={Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, author={{U.S. Department of Energy}}, - howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}} + howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}}, note={Accessed:2024-07-30}} From 2a2da22c57444914889e9d9e6c747963b035b1dd Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 28 Jul 2025 14:25:47 -0700 Subject: [PATCH 11/29] update paper contents based on reviewer comments --- docs/.DS_Store | Bin 0 -> 6148 bytes docs/paper.bib | 42 +++++++++++++++++++++++++++++++++++++++ docs/paper.md | 53 ++++++++++++++++++++----------------------------- 3 files changed, 64 insertions(+), 31 deletions(-) create mode 100644 docs/.DS_Store diff --git a/docs/.DS_Store b/docs/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..25ff79f32453b4a48b73d4e4db85611a40c26d90 GIT binary patch literal 6148 zcmeHK!Ab)$5S?hXyB47b1;xvPSHV`LP`s?Q{(vibP^sN+sY|z;vfJ82E$m&t!$0ug z7kKgPXZQ`yBq>;HMWKk43{2i6nMpctNzwrTR_c0rfGhwQsD!B{Y`zehCmoYHHA0h2 ztkHxDG@uJUcw^prKr^5j_-_o*+0B3p5uVu^d_2E(w->kFfV=4NY;Hca zu$WGp=}h|4x#m5mQ|)x)QZ+iK-U;V{JG86rsbB9^vMYx?>{R`*9*F?otE0=snIC$* zSK{5!i$$y>Crr~YE7|paKfhZnZdrSU++fS<7k6@K?-m9F(^%cy-aoE1gI37zB%chg zA0f*Mhj5R^g!F<&-l_3cd+0jZv&GA0MTGJ8@_75O@qF-|xAzP0_VrJH#f=k%0S_Cv zGiAF7F>t(UBm8VL^QlIX`jjx{tYxYUs6%69rn;(LOf#Svm<0ytey~spZH0+MadluL zN&v(Z4hun>Y6*(56xs?Ci8zD8WGJExWvawrG91S(OF-dYRw3YCQX o5{V)N8}%FugP!6wR3SKLk%4F{OeEq6ivA-YXwZ#j;7=KN2m8;oUjP6A literal 0 HcmV?d00001 diff --git a/docs/paper.bib b/docs/paper.bib index 6c3c2393..58036d82 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -54,3 +54,45 @@ @misc {bto_blueprint author={{U.S. Department of Energy}}, howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}}, note={Accessed:2024-07-30}} + +@misc{skyspark, + author = {SkyFoundry}, + title = {SkySpark Analytics}, + year = {2023}, + note = {\url{https://skyfoundry.com/skyspark}}, +} + +@misc{coppertree, + author = {CopperTree Analytics}, + title = {CopperTree Analytics Platform}, + year = {2023}, + note = {\url{https://www.coppertreeanalytics.com}}, +} + +@article{fdd_review, + author = {Katipamula, Srinivas and Brambley, Michael R.}, + title = {Review of Fault Detection and Diagnostic Methods for Building Systems}, + journal = {HVAC&R Research}, + volume = {11}, + number = {2}, + pages = {169--187}, + year = {2005}, + doi = {10.1080/10789669.2005.10391123} +} + +@inproceedings{brick, + author = {Balaji, Bharathan and Bhattacharya, Arka and Fierro, Gabe and Gao, Jie and Gluck, Josh and Hong, Deokwoo and Johansen, Aslak and Koh, Jihyun and Ploennigs, Joern and Agarwal, Yuvraj and Whitehouse, Kamin and Taneja, Jayant}, + title = {Brick: Metadata Schema for Portable Smart Building Applications}, + booktitle = {Proceedings of the 3rd ACM International Conference on Systems for Energy-Efficient Built Environments}, + year = {2016}, + pages = {41--50}, + publisher = {ACM}, + doi = {10.1145/2993422.2993577} +} + +@manual{energyplus, + title = {EnergyPlus Energy Simulation Software}, + author = {{U.S. Department of Energy}}, + organization = {U.S. Department of Energy}, + url = {https://energyplus.net/} +} \ No newline at end of file diff --git a/docs/paper.md b/docs/paper.md index 6503ab4a..730a4a88 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -7,54 +7,45 @@ tags: - control - simulation - hvac -authors: - - name: Xuechen Lei - orcid: 0000-0003-3310-9750 - affiliation: 1 - - name: Jérémy Lerond - orcid: 0000-0002-1630-6886 - affiliation: 1 - - name: Yun Joon Jung - orcid: 0000-0003-1311-8932 - affiliation: 1 - - name: Julian Slane-Holloway - orcid: 0009-0008-9572-9123 - affiliation: 1 - - name: Fan Feng - orcid: 0000-0002-6230-0063 - affiliation: 1 - - name: Yan Chen - orcid: 0000-0002-2988-9136 - affiliation: 1 - -affiliations: - - name: Pacific Northwest National Laboratory, Richland, WA, USA - index: 1 -date: 28 May 2024 + bibliography: paper.bib --- # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations or from actual building automation system (BAS) trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. +The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations (e.g. EnergyPlus [@energyplus]) or from actual building automation system (BAS) trend data. `ConStrain` is made of three main components: an expandable control verification algorithms library, a streamlined verification case and data preparation process, and a standardized performance evaluation and reporting process. + +At its roots, `ConStrain`'s verification library was developed to check for compliance with control-related requirements in building energy codes—such as scheduling, economizer logic, demand-controlled ventilation, or equipment staging. These requirements specify how Heating, Ventilation, and Air Conditioning (HVAC) systems should behave to ensure energy efficiency. ConStrain formalizes and automates the control verification process, which involves checking time-series sensor and actuator data to determine whether actual system operation aligns with those intended control sequences. Meanwhile, the verification library is implemented in a way such that it is expandable and can cover user-customized control verifications. # Statement of need Robust HVAC control is a “no regrets” strategy for building decarbonization, reducing energy use, enabling flexibility and resilience, and supporting the transition to electrified heating, all with low embodied carbon. The Buildings Technology Office (BTO) of the United States Department of Energy’s blueprint has a goal of “more than 50% of all homes and businesses have automated control platforms that reduce energy waste and enable flexibility“ [@bto_blueprint]. -Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. +Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4–5 quadrillion BTUs (“Quads”), or about 4–5% of total U.S. energy consumption [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, over the course of four successive ASHRAE 90.1 code cycles—from the 2004 edition to the 2016 edition — approximately 30% of the new requirements are related to building control (with most of them focused on HVAC system control) [@impl_ctrl]. This trend reflects the increasing importance of automated control in achieving code-mandated energy performance. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. -Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. +Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. To address this, `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. `ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to building energy code (e.g., ASHRAE 90.1) or to a high-performance building control guideline (e.g., ASHRAE Guideline 36 [@g36]). `ConStrain` is also incorporating semantic modeling [@brick] capabilities to enable automated configuration and deployment of verification. -`ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. +`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. -`ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 @[g36]). -`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. ConStrain has applications to code-compliance building performance standards (BPS), and commissioning. +### Comparison with existing tools and industry practices + +In current industry practice, control verification is often done manually by commissioning agents or energy auditors using general-purpose tools such as spreadsheets, scripting environments (e.g., Excel, MATLAB, or Python), or proprietary solutions bundled with Building Automation Systems (BAS). These approaches are typically ad hoc, time-consuming, and lack reproducibility and standardization across projects. + +A few commercial tools do support some level of automated trend data analysis, such as SkySpark [@skyspark], CopperTree [@coppertree], or Fault Detection and Diagnostics (FDD) modules embedded in modern BAS platforms [@fdd_review]. However, these are typically closed-source, require vendor-specific data formats, and are not tailored for code-compliance or standards-based control verification. + +To our knowledge, ConStrain is the only open-source software framework focused specifically on automated control verification aligned with building energy code and advanced building control guidelines (e.g., ASHRAE 90.1, Guideline 36). It distinguishes itself by offering: + +- A growing library of modular, reusable control logic verification tests +- A flexible API for custom verification logic and report generation +- Integration with semantic models [@brick] to enable automated verification case setup +- Compatibility with both simulated and real BAS data sources +- Seamless use in simulation and CI pipelines (e.g., OpenStudio [@os], TSPR [@tspr]) + +These capabilities enable ConStrain to bridge the gap between simulation-based design intent and real-world implementation, supporting code compliance, model-based commissioning, and continuous performance assurance. -`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. # Acknowledgements From 5335b5ae0c73746b1a794a9e55471a653e61edd9 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 28 Jul 2025 14:26:49 -0700 Subject: [PATCH 12/29] remove mac file --- docs/.DS_Store | Bin 6148 -> 0 bytes 1 file changed, 0 insertions(+), 0 deletions(-) delete mode 100644 docs/.DS_Store diff --git a/docs/.DS_Store b/docs/.DS_Store deleted file mode 100644 index 25ff79f32453b4a48b73d4e4db85611a40c26d90..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 6148 zcmeHK!Ab)$5S?hXyB47b1;xvPSHV`LP`s?Q{(vibP^sN+sY|z;vfJ82E$m&t!$0ug z7kKgPXZQ`yBq>;HMWKk43{2i6nMpctNzwrTR_c0rfGhwQsD!B{Y`zehCmoYHHA0h2 ztkHxDG@uJUcw^prKr^5j_-_o*+0B3p5uVu^d_2E(w->kFfV=4NY;Hca zu$WGp=}h|4x#m5mQ|)x)QZ+iK-U;V{JG86rsbB9^vMYx?>{R`*9*F?otE0=snIC$* zSK{5!i$$y>Crr~YE7|paKfhZnZdrSU++fS<7k6@K?-m9F(^%cy-aoE1gI37zB%chg zA0f*Mhj5R^g!F<&-l_3cd+0jZv&GA0MTGJ8@_75O@qF-|xAzP0_VrJH#f=k%0S_Cv zGiAF7F>t(UBm8VL^QlIX`jjx{tYxYUs6%69rn;(LOf#Svm<0ytey~spZH0+MadluL zN&v(Z4hun>Y6*(56xs?Ci8zD8WGJExWvawrG91S(OF-dYRw3YCQX o5{V)N8}%FugP!6wR3SKLk%4F{OeEq6ivA-YXwZ#j;7=KN2m8;oUjP6A From c80442206e44b9600c4e5f699b00732629afeb4e Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 28 Jul 2025 15:00:23 -0700 Subject: [PATCH 13/29] add back authors --- docs/paper.md | 24 ++++++++++++++++++++++++ 1 file changed, 24 insertions(+) diff --git a/docs/paper.md b/docs/paper.md index 730a4a88..bace8507 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -7,6 +7,30 @@ tags: - control - simulation - hvac +authors: + - name: Xuechen Lei + orcid: 0000-0003-3310-9750 + affiliation: 1 + - name: Jérémy Lerond + orcid: 0000-0002-1630-6886 + affiliation: 1 + - name: Yun Joon Jung + orcid: 0000-0003-1311-8932 + affiliation: 1 + - name: Julian Slane-Holloway + orcid: 0009-0008-9572-9123 + affiliation: 1 + - name: Fan Feng + orcid: 0000-0002-6230-0063 + affiliation: 1 + - name: Yan Chen + orcid: 0000-0002-2988-9136 + affiliation: 1 + +affiliations: + - name: Pacific Northwest National Laboratory, Richland, WA, USA + index: 1 +date: 28 May 2024 bibliography: paper.bib --- From 4e3be026e1fd64488d563ef09222a146c99a468e Mon Sep 17 00:00:00 2001 From: Yan Chen Date: Mon, 28 Jul 2025 21:16:35 -0700 Subject: [PATCH 14/29] Update paper.md Generalized language by removing company-specific tool names and refining wording to focus on industry practices and performance-based control verification --- docs/paper.md | 8 +++----- 1 file changed, 3 insertions(+), 5 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index bace8507..e494102e 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -37,7 +37,7 @@ bibliography: paper.bib # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations (e.g. EnergyPlus [@energyplus]) or from actual building automation system (BAS) trend data. `ConStrain` is made of three main components: an expandable control verification algorithms library, a streamlined verification case and data preparation process, and a standardized performance evaluation and reporting process. +The Control Strainer (ConStrain) is a Python-based, open-source framework that enables commissioning agents, controls engineers, building automation specialists, facility managers, and energy modelers to conduct consistent and automated verification of building system controls. It utilizes real-time Building Automation System (BAS) trend data or time-series data generated from whole-building energy system simulations (e.g., EnergyPlus [@energyplus], Spawn-of-EnergyPlus [@spawn], Modelica [@modelica]). At its roots, `ConStrain`'s verification library was developed to check for compliance with control-related requirements in building energy codes—such as scheduling, economizer logic, demand-controlled ventilation, or equipment staging. These requirements specify how Heating, Ventilation, and Air Conditioning (HVAC) systems should behave to ensure energy efficiency. ConStrain formalizes and automates the control verification process, which involves checking time-series sensor and actuator data to determine whether actual system operation aligns with those intended control sequences. Meanwhile, the verification library is implemented in a way such that it is expandable and can cover user-customized control verifications. @@ -56,9 +56,7 @@ Current control verification is often conducted manually, which is time-consumin ### Comparison with existing tools and industry practices -In current industry practice, control verification is often done manually by commissioning agents or energy auditors using general-purpose tools such as spreadsheets, scripting environments (e.g., Excel, MATLAB, or Python), or proprietary solutions bundled with Building Automation Systems (BAS). These approaches are typically ad hoc, time-consuming, and lack reproducibility and standardization across projects. - -A few commercial tools do support some level of automated trend data analysis, such as SkySpark [@skyspark], CopperTree [@coppertree], or Fault Detection and Diagnostics (FDD) modules embedded in modern BAS platforms [@fdd_review]. However, these are typically closed-source, require vendor-specific data formats, and are not tailored for code-compliance or standards-based control verification. +In current industry practices, HVAC control verification is often conducted manually by commissioning agents or facilities teams, or through proprietary trend data analytics solutions integrated into Building Automation Systems (BAS). These tools, while valuable for fault detection and system monitoring, are generally vendor-specific, offer limited transparency, and are not purpose-built to ensure that control strategies intended to deliver energy savings, such as those specified in energy codes or design standards, are functioning as intended in actual operation. To our knowledge, ConStrain is the only open-source software framework focused specifically on automated control verification aligned with building energy code and advanced building control guidelines (e.g., ASHRAE 90.1, Guideline 36). It distinguishes itself by offering: @@ -75,4 +73,4 @@ These capabilities enable ConStrain to bridge the gap between simulation-based d ConStrain was developed at the Pacific Northwest National Laboratory and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. -# References \ No newline at end of file +# References From 19036aded0af50c1bb15ad45d1f32970010a8a97 Mon Sep 17 00:00:00 2001 From: lymereJ Date: Mon, 28 Jul 2025 21:38:25 -0700 Subject: [PATCH 15/29] Update GH action to create JOSS paper. --- .github/workflows/draft-pdf.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/draft-pdf.yml b/.github/workflows/draft-pdf.yml index dab4a823..3c32720d 100644 --- a/.github/workflows/draft-pdf.yml +++ b/.github/workflows/draft-pdf.yml @@ -1,3 +1,4 @@ +name: Draft PDF on: [push] jobs: @@ -14,7 +15,7 @@ jobs: # This should be the path to the paper within your repo. paper-path: ./docs/paper.md - name: Upload - uses: actions/upload-artifact@v1 + uses: actions/upload-artifact@v4 with: name: paper # This is the output path where Pandoc will write the compiled From 60071640c32d2a4ecfc13ef2c2cefcbd4007c3f6 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Thu, 31 Jul 2025 14:02:34 -0700 Subject: [PATCH 16/29] address jl comments --- docs/paper.bib | 21 +++++++++++++++++++++ docs/paper.md | 8 ++++---- 2 files changed, 25 insertions(+), 4 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 58036d82..22667752 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -95,4 +95,25 @@ @manual{energyplus author = {{U.S. Department of Energy}}, organization = {U.S. Department of Energy}, url = {https://energyplus.net/} +} + +@article{spawn, + title={Spawn: coupling Modelica Buildings Library and EnergyPlus to enable new energy system and control applications}, + author={Wetter, Michael and Benne, Kyle and Tummescheit, Hubertus and Winther, Christian}, + journal={Journal of Building Performance Simulation}, + volume={17}, + number={2}, + pages = {274-292}, + year = {2024}, + publisher = {Taylor \& Francis}, + doi = {10.1080/19401493.2023.2266414}, + url = {https://www.tandfonline.com/doi/full/10.1080/19401493.2023.2266414} +} + +@misc{modelica, + author = {Modelica Association}, + title = {Modelica – A Unified Object-Oriented Language for Physical Systems Modeling}, + year = {2023}, + note = {Modelica Specification Version 3.6}, + url = {https://specification.modelica.org/maint/3.6/MLS.pdf} } \ No newline at end of file diff --git a/docs/paper.md b/docs/paper.md index e494102e..85857225 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -49,14 +49,14 @@ Advances in building control have shown significant potential for improving buil However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. -Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. To address this, `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. `ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to building energy code (e.g., ASHRAE 90.1) or to a high-performance building control guideline (e.g., ASHRAE Guideline 36 [@g36]). `ConStrain` is also incorporating semantic modeling [@brick] capabilities to enable automated configuration and deployment of verification. +Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. To address this, `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. `ConStrain` is an executable control verification knowledge base and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to building energy code (e.g., ASHRAE 90.1) or to a high-performance building control guideline (e.g., ASHRAE Guideline 36 [@g36]). `ConStrain` is also incorporating semantic modeling [@brick] capabilities to enable automated configuration and deployment of verification. -`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. +`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to perform verification on their models with minimal configurations required. ### Comparison with existing tools and industry practices -In current industry practices, HVAC control verification is often conducted manually by commissioning agents or facilities teams, or through proprietary trend data analytics solutions integrated into Building Automation Systems (BAS). These tools, while valuable for fault detection and system monitoring, are generally vendor-specific, offer limited transparency, and are not purpose-built to ensure that control strategies intended to deliver energy savings, such as those specified in energy codes or design standards, are functioning as intended in actual operation. +In current industry practices, HVAC control verification is often conducted manually by commissioning agents or facilities teams, or through proprietary trend data analytics solutions integrated into BAS. These tools, while valuable for fault detection and system monitoring, are generally vendor-specific, offer limited transparency, and are not purpose-built to ensure that control strategies intended to deliver energy savings, such as those specified in energy codes or design standards, are functioning as intended in actual operation. To our knowledge, ConStrain is the only open-source software framework focused specifically on automated control verification aligned with building energy code and advanced building control guidelines (e.g., ASHRAE 90.1, Guideline 36). It distinguishes itself by offering: @@ -66,7 +66,7 @@ To our knowledge, ConStrain is the only open-source software framework focused s - Compatibility with both simulated and real BAS data sources - Seamless use in simulation and CI pipelines (e.g., OpenStudio [@os], TSPR [@tspr]) -These capabilities enable ConStrain to bridge the gap between simulation-based design intent and real-world implementation, supporting code compliance, model-based commissioning, and continuous performance assurance. +These capabilities enable ConStrain to bridge the gap between simulation-based design intent and real-world implementation, supporting code compliance, model-based commissioning, and continuous performance verification. # Acknowledgements From 5ae6b2a0a9a0c272fd948fd3944ca553cf416048 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Thu, 31 Jul 2025 18:03:33 -0700 Subject: [PATCH 17/29] update bib --- docs/paper.bib | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 22667752..a6462e10 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -17,9 +17,10 @@ @misc {g36 } @misc{tspr, - title={TSPR Washington State Analysis Tool}, + title={TSPR Washington State Analysis Tool 2024.1.0}, author={{Pacific Northwest National Laboratory}}, howpublished={\url{https://energycode.pnl.gov/HVACSystemPerformance/}}, + year={2024}, note={Accessed: 2024-04-044} } @@ -36,9 +37,10 @@ @report{impa_ctrl } @misc{os, - title={OpenStudio}, + title={OpenStudio 3.8}, author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, howpublished={\url{https://openstudio.net/}}, + year={2024}, note={Accessed: 2024-04-04} } @@ -46,6 +48,7 @@ @misc{osm title={OpenStudio SDK User Docs: Getting Started - About Measures}, author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, howpublished={\url{https://nrel.github.io/OpenStudio-user-documentation/getting_started/about_measures/}}, + year={2024}, note={Accessed: 2024-05-28} } @@ -53,6 +56,7 @@ @misc {bto_blueprint title={Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, author={{U.S. Department of Energy}}, howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}}, + year={2024}, note={Accessed:2024-07-30}} @misc{skyspark, @@ -91,8 +95,9 @@ @inproceedings{brick } @manual{energyplus, - title = {EnergyPlus Energy Simulation Software}, + title = {EnergyPlus Energy Simulation Software 24.1.0}, author = {{U.S. Department of Energy}}, + year = {2024}, organization = {U.S. Department of Energy}, url = {https://energyplus.net/} } @@ -111,7 +116,7 @@ @article{spawn } @misc{modelica, - author = {Modelica Association}, + author = {{Modelica Association}}, title = {Modelica – A Unified Object-Oriented Language for Physical Systems Modeling}, year = {2023}, note = {Modelica Specification Version 3.6}, From b9a5c1643e6e1388069d5b02593586604e2c14c6 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 2 Feb 2026 09:52:46 -0800 Subject: [PATCH 18/29] paper revision wip --- docs/paper.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 85857225..55922abb 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -49,9 +49,9 @@ Advances in building control have shown significant potential for improving buil However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. -Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. To address this, `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. `ConStrain` is an executable control verification knowledge base and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to building energy code (e.g., ASHRAE 90.1) or to a high-performance building control guideline (e.g., ASHRAE Guideline 36 [@g36]). `ConStrain` is also incorporating semantic modeling [@brick] capabilities to enable automated configuration and deployment of verification. +Current control verification is often conducted manually, which is time-consuming, ad-hoc, incomplete, and error-prone. To address this, `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. `ConStrain` is an executable control verification knowledge base and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to building energy code (e.g., ASHRAE 90.1) or to a high-performance building control guideline (e.g., ASHRAE Guideline 36 [@g36]). Currently, ConStrain's API supports flexible local and programmatic use of various ConStrain components and workflows within users' analysis pipelines and can potentially be wrapped into a network-accessible service API at users' discretion. `ConStrain` is also incorporating semantic modeling [@brick] capabilities to enable automated configuration and deployment of verification. -`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to perform verification on their models with minimal configurations required. +`ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to perform verification on their models with minimal configurations required upon initial implementation of point mapping from simulation model to ConStrain verification cases. ### Comparison with existing tools and industry practices @@ -61,7 +61,7 @@ In current industry practices, HVAC control verification is often conducted manu To our knowledge, ConStrain is the only open-source software framework focused specifically on automated control verification aligned with building energy code and advanced building control guidelines (e.g., ASHRAE 90.1, Guideline 36). It distinguishes itself by offering: - A growing library of modular, reusable control logic verification tests -- A flexible API for custom verification logic and report generation +- A flexible and local API for custom verification logic and report generation - Integration with semantic models [@brick] to enable automated verification case setup - Compatibility with both simulated and real BAS data sources - Seamless use in simulation and CI pipelines (e.g., OpenStudio [@os], TSPR [@tspr]) From bfcc795892877363b8bb782a0fc07accfa60b3e4 Mon Sep 17 00:00:00 2001 From: "Adam R. Jensen" <39184289+AdamRJensen@users.noreply.github.com> Date: Mon, 16 Feb 2026 12:48:21 -0600 Subject: [PATCH 19/29] Fix citation in JOSS paper --- docs/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 6503ab4a..d30d8570 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -50,7 +50,7 @@ Current control verification is often conducted manually, which is time-consumin `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. -`ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 @[g36]). +`ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 [@g36]). `ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. ConStrain has applications to code-compliance building performance standards (BPS), and commissioning. @@ -60,4 +60,4 @@ Current control verification is often conducted manually, which is time-consumin ConStrain was developed at the Pacific Northwest National Laboratory and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. -# References \ No newline at end of file +# References From 2d5fc29adee68c2b70b3c9c12a1bc3a7d0607ed4 Mon Sep 17 00:00:00 2001 From: "Adam R. Jensen" <39184289+AdamRJensen@users.noreply.github.com> Date: Mon, 16 Feb 2026 12:53:30 -0600 Subject: [PATCH 20/29] Add report number and url to and change report to techreport --- docs/paper.bib | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 6c3c2393..b0800eeb 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -23,13 +23,16 @@ @misc{tspr note={Accessed: 2024-04-044} } -@report{impl_ctrl, +@techreport{impl_ctrl, title={Implementation of Energy Code Controls Requirements in New Commercial Buildings}, author={{Rosenberg, M.I., P.R. Hart, M. Hatten, D. Jones, and M. Cooper}}, - year={2017} + year={2017}, + number={PNNL-26348}, + howpublished={\url{https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-26348.pdf}}, + note={Accessed:2024-07-30}} } -@report{impa_ctrl, +@techreport{impa_ctrl, title={Impacts of commercial building controls on energy savings and peak load reduction}, author={{Fernandez, Nicholas EP, et al.}}, year={2017} From e5742ff3a39e0be8d8612694daae90f6c920e52e Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Thu, 19 Feb 2026 16:16:07 -0800 Subject: [PATCH 21/29] revise draft based on comments in https://github.com/openjournals/joss-reviews/issues/8083#issuecomment-2909884205 --- docs/paper.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/paper.md b/docs/paper.md index d30d8570..8792b236 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -50,12 +50,14 @@ Current control verification is often conducted manually, which is time-consumin `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. -`ConStrain` is an open-source library and application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 [@g36]). +`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 [@g36]). Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. `ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. ConStrain has applications to code-compliance building performance standards (BPS), and commissioning. `ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. +At present, `ConStrain` expects pre-harmonized input units for each verification case that align with expected data points units defined in its corresponding verification item; automatic unit conversion is not in the core workflow and needs to be handled before feeding data into `ConStrain`. + # Acknowledgements ConStrain was developed at the Pacific Northwest National Laboratory and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. From 530f20b7f509a50234235fe3c5ef0667d009e61e Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Thu, 19 Feb 2026 16:20:43 -0800 Subject: [PATCH 22/29] add contract no in aknowledgement --- docs/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/paper.md b/docs/paper.md index 8792b236..5d338a36 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -60,6 +60,6 @@ At present, `ConStrain` expects pre-harmonized input units for each verification # Acknowledgements -ConStrain was developed at the Pacific Northwest National Laboratory and was funded under contract with the U.S. Department of Energy (DOE). It is actively being developed as an open-source project. +ConStrain is developed at the Pacific Northwest National Laboratory and is funded by the U.S. Department of Energy (DOE) under Contract DE-AC05-76RL01830. It is actively being developed as an open-source project. # References From 51f5e4debc6e0b5881cb7c404a69a3dc6ad52751 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Tue, 24 Feb 2026 13:31:26 -0800 Subject: [PATCH 23/29] add doi per request --- docs/paper.bib | 38 +++++++++++++++++++++++++++----------- 1 file changed, 27 insertions(+), 11 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index b0800eeb..ed5c3eae 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -24,18 +24,28 @@ @misc{tspr } @techreport{impl_ctrl, - title={Implementation of Energy Code Controls Requirements in New Commercial Buildings}, - author={{Rosenberg, M.I., P.R. Hart, M. Hatten, D. Jones, and M. Cooper}}, - year={2017}, - number={PNNL-26348}, - howpublished={\url{https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-26348.pdf}}, + author = {Rosenberg, Michael I. and Hart, Philip R. and Hatten, Mike and Jones, Dennis and Cooper, Matthew}, + title = {Implementation of Energy Code Controls Requirements in New Commercial Buildings}, + institution = {Pacific Northwest National Lab. (PNNL), Richland, WA (United States)}, + annote = {Most state energy codes in the United States are based on one of two national model codes; ANSI/ASHRAE/IES 90.1 (Standard 90.1) or the International Code Council (ICC) International Energy Conservation Code (IECC). Since 2004, covering the last four cycles of Standard 90.1 updates, about 30% of all new requirements have been related to building controls. These requirements can be difficult to implement and verification is beyond the expertise of most building code officials, yet the assumption in studies that measure the savings from energy codes is that they are implemented and working correctly. The objective of the current research is to evaluate the degree to which high impact controls requirements included in commercial energy codes are properly designed, commissioned and implemented in new buildings. This study also evaluates the degree to which these control requirements are realizing their savings potential. This was done using a three-step process. The first step involved interviewing commissioning agents to get a better understanding of their activities as they relate to energy code required controls measures. The second involved field audits of a sample of commercial buildings to determine whether the code required control measures are being designed, commissioned and correctly implemented and functioning in new buildings. The third step includes compilation and analysis of the information gather during the first two steps. Information gathered during these activities could be valuable to code developers, energy planners, designers, building owners, and building officials.}, + doi = {10.2172/1349983}, + url = {https://www.osti.gov/biblio/1349983}, + place = {United States}, + year = {2017}, + month = {03}, note={Accessed:2024-07-30}} } @techreport{impa_ctrl, - title={Impacts of commercial building controls on energy savings and peak load reduction}, - author={{Fernandez, Nicholas EP, et al.}}, - year={2017} + author = {Fernandez, Nicholas E.P. and Katipamula, Srinivas and Wang, Weimin and Xie, YuLong and Zhao, Mingjie and Corbin, Charles D.}, + title = {Impacts of Commercial Building Controls on Energy Savings and Peak Load Reduction}, + institution = {Pacific Northwest National Lab. (PNNL), Richland, WA (United States)}, + annote = {Commercial buildings in the United States use about 18 Quadrillion British thermal units (Quads) of primary energy annually . Studies have shown that as much as 30% of building energy consumption can be avoided by using more accurate sensing, using existing controls better, and deploying advanced controls; hence, the motivation for the work described in this report. Studies also have shown that 10% to 20% of the commercial building peak load can be temporarily managed/curtailed to provide grid services. Although many studies have indicated significant potential for reducing the energy consumption in commercial buildings, very few have documented the actual savings. The studies that did so only provided savings at the whole building level, which makes it difficult to assess the savings potential of each individual measure deployed.}, + doi = {10.2172/1400347}, + url = {https://www.osti.gov/biblio/1400347}, + place = {United States}, + year = {2017}, + month = {05}} } @misc{os, @@ -53,7 +63,13 @@ @misc{osm } @misc {bto_blueprint, - title={Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, - author={{U.S. Department of Energy}}, - howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}}, + author = {Langevin, Jared and Wilson, Eric and Snyder, Carolyn and Narayanamurthy, Ram and Miller, Julia and Kaplan, Katharine and Reiner, Michael and Risser, Roland and Mahoney, Mandy and Geyer, Josh and others}, + title = {Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, + institution = {Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)}, + annote = {Residential and commercial buildings are among the largest sources of carbon dioxide and other greenhouse gas (GHG) emissions in the United States, responsible for more than one-third of total U.S. GHG emissions. There are nearly 130 million existing buildings in the United States, with 40 million new homes and 60 billion square feet of commercial floorspace expected to be constructed between now and 2050. Today, most buildings consume large amounts of energy and cause significant climate pollution to meet our basic needs. Buildings account for 74% of U.S. electricity use and building heating and cooling drives peak electricity demand. Moreover, buildings are where electric vehicles (EVs), solar, storage, heat pumps, water heaters, and other distributed energy resources integrate with the electricity system. Consequently, the buildings sector will play a key role in achieving economywide net-zero emissions by 2050.}, + doi = {10.2172/2338089}, + url = {https://www.osti.gov/biblio/2338089}, + place = {United States}, + year = {2024}, + month = {04}, note={Accessed:2024-07-30}} From 7b7ec019b779b3caa2579e005c2f769dc51e2d5b Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Tue, 24 Feb 2026 13:43:11 -0800 Subject: [PATCH 24/29] add doi for openstudio --- docs/paper.bib | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index ed5c3eae..105a05c9 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -49,9 +49,14 @@ @techreport{impa_ctrl } @misc{os, - title={OpenStudio}, - author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, - howpublished={\url{https://openstudio.net/}}, + author = {Ball, Brian and Long, Nicholas and Macumber, Dan and Benne, Kyle and Robertson, Joe and Weaver, Evan and Turner, Jason and Swindler, Alex and Hale, Elaine and DeGraw, Jason and others}, + title = {OPENSTUDIO® [SWR-07-40]}, + annote = {OpenStudio® is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models. OPENSTUDIO® IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.}, + doi = {10.11578/dc.20171025.1817}, + url = {https://www.osti.gov/biblio/code-4561}, + place = {United States}, + year = {2016}, + month = {08}, note={Accessed: 2024-04-04} } From 9fb0fb4aba166ccb939443c452d11afae888ade0 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 30 Mar 2026 23:00:48 -0700 Subject: [PATCH 25/29] add footnote for Fan --- docs/paper.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/paper.md b/docs/paper.md index 0350f8c2..699a221c 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -20,7 +20,7 @@ authors: - name: Julian Slane-Holloway orcid: 0009-0008-9572-9123 affiliation: 1 - - name: Fan Feng + - name: Fan Feng[^1] orcid: 0000-0002-6230-0063 affiliation: 1 - name: Yan Chen @@ -34,6 +34,8 @@ date: 28 May 2024 bibliography: paper.bib --- +[^1]: Fan Feng contributed to this work while affiliated with Pacific Northwest National Laboratory (PNNL). He is no longer affiliated with PNNL at the time of publication. + # Summary The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations or from actual building automation system (BAS) trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. From 6b86e388b72d9b82725f91f15135e70bf4438246 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 30 Mar 2026 23:03:52 -0700 Subject: [PATCH 26/29] save bib --- docs/paper.bib | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 72e39d3c..6c0f9f5e 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -50,7 +50,6 @@ @techreport{impa_ctrl } @misc{os, -<<<<<<< HEAD author = {Ball, Brian and Long, Nicholas and Macumber, Dan and Benne, Kyle and Robertson, Joe and Weaver, Evan and Turner, Jason and Swindler, Alex and Hale, Elaine and DeGraw, Jason and others}, title = {OPENSTUDIO® [SWR-07-40]}, annote = {OpenStudio® is a cross-platform (Windows, Mac, and Linux) collection of software tools to support whole building energy modeling using EnergyPlus and advanced daylight analysis using Radiance. OpenStudio is an open source (LGPL) project to facilitate community development, extension, and private sector adoption. OpenStudio includes graphical interfaces along with a Software Development Kit (SDK). In addition to the graphical interface, OpenStudio allows building researchers and software developers to quickly get started through its multiple entry levels, including access through C++, Ruby, and C#. Users can leverage the Ruby interface to create OpenStudio Measures that can be easily shared and applied to OpenStudio Models. OPENSTUDIO® IS A REGISTERED TRADEMARK OF ALLIANCE FOR SUSTAINABLE ENERGY, LLC, THE MANAGER AND OPERATOR OF THE NATIONAL RENEWABLE ENERGY LABORATORY.}, @@ -59,12 +58,6 @@ @misc{os place = {United States}, year = {2016}, month = {08}, -======= - title={OpenStudio 3.8}, - author={{National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory}}, - howpublished={\url{https://openstudio.net/}}, - year={2024}, ->>>>>>> joss_paper_rev note={Accessed: 2024-04-04} } @@ -77,7 +70,6 @@ @misc{osm } @misc {bto_blueprint, -<<<<<<< HEAD author = {Langevin, Jared and Wilson, Eric and Snyder, Carolyn and Narayanamurthy, Ram and Miller, Julia and Kaplan, Katharine and Reiner, Michael and Risser, Roland and Mahoney, Mandy and Geyer, Josh and others}, title = {Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, institution = {Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)}, @@ -87,12 +79,6 @@ @misc {bto_blueprint place = {United States}, year = {2024}, month = {04}, -======= - title={Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, - author={{U.S. Department of Energy}}, - howpublished={\url{https://www.energy.gov/eere/articles/decarbonizing-us-economy-2050}}, - year={2024}, ->>>>>>> joss_paper_rev note={Accessed:2024-07-30}} @misc{skyspark, From 149204e7090be8872dfb75caf521942df4df7517 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Mon, 6 Apr 2026 23:57:03 -0700 Subject: [PATCH 27/29] update paper after int review --- docs/paper.bib | 97 -------------------------------------------------- docs/paper.md | 16 ++++----- 2 files changed, 6 insertions(+), 107 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index 6c0f9f5e..bc70a9e1 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -1,21 +1,3 @@ -@misc {90.1, - title={ANSI/ASHRAE/IES 90.1-2019, Energy Standard for Buildings Except Low-Rise Residential Buildings}, - author={{ASHRAE}}, - organization={ASHRAE}, - institution={ASHRAE}, - address={Atlanta, GA}, - year={2019} -} - -@misc {g36, - title={Guideline 36-2018. High-Performance Sequences of Operation for HVAC Systems}, - author={{ASHRAE}}, - organization={ASHRAE}, - institution={ASHRAE}, - address={Atlanta, GA}, - year={2021} - } - @misc{tspr, title={TSPR Washington State Analysis Tool 2024.1.0}, author={{Pacific Northwest National Laboratory}}, @@ -24,19 +6,6 @@ @misc{tspr note={Accessed: 2024-04-044} } -@techreport{impl_ctrl, - author = {Rosenberg, Michael I. and Hart, Philip R. and Hatten, Mike and Jones, Dennis and Cooper, Matthew}, - title = {Implementation of Energy Code Controls Requirements in New Commercial Buildings}, - institution = {Pacific Northwest National Lab. (PNNL), Richland, WA (United States)}, - annote = {Most state energy codes in the United States are based on one of two national model codes; ANSI/ASHRAE/IES 90.1 (Standard 90.1) or the International Code Council (ICC) International Energy Conservation Code (IECC). Since 2004, covering the last four cycles of Standard 90.1 updates, about 30% of all new requirements have been related to building controls. These requirements can be difficult to implement and verification is beyond the expertise of most building code officials, yet the assumption in studies that measure the savings from energy codes is that they are implemented and working correctly. The objective of the current research is to evaluate the degree to which high impact controls requirements included in commercial energy codes are properly designed, commissioned and implemented in new buildings. This study also evaluates the degree to which these control requirements are realizing their savings potential. This was done using a three-step process. The first step involved interviewing commissioning agents to get a better understanding of their activities as they relate to energy code required controls measures. The second involved field audits of a sample of commercial buildings to determine whether the code required control measures are being designed, commissioned and correctly implemented and functioning in new buildings. The third step includes compilation and analysis of the information gather during the first two steps. Information gathered during these activities could be valuable to code developers, energy planners, designers, building owners, and building officials.}, - doi = {10.2172/1349983}, - url = {https://www.osti.gov/biblio/1349983}, - place = {United States}, - year = {2017}, - month = {03}, - note={Accessed:2024-07-30}} -} - @techreport{impa_ctrl, author = {Fernandez, Nicholas E.P. and Katipamula, Srinivas and Wang, Weimin and Xie, YuLong and Zhao, Mingjie and Corbin, Charles D.}, title = {Impacts of Commercial Building Controls on Energy Savings and Peak Load Reduction}, @@ -69,43 +38,6 @@ @misc{osm note={Accessed: 2024-05-28} } -@misc {bto_blueprint, - author = {Langevin, Jared and Wilson, Eric and Snyder, Carolyn and Narayanamurthy, Ram and Miller, Julia and Kaplan, Katharine and Reiner, Michael and Risser, Roland and Mahoney, Mandy and Geyer, Josh and others}, - title = {Decarbonizing the U.S. Economy by 2050: A National Blueprint for the Buildings Sector}, - institution = {Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)}, - annote = {Residential and commercial buildings are among the largest sources of carbon dioxide and other greenhouse gas (GHG) emissions in the United States, responsible for more than one-third of total U.S. GHG emissions. There are nearly 130 million existing buildings in the United States, with 40 million new homes and 60 billion square feet of commercial floorspace expected to be constructed between now and 2050. Today, most buildings consume large amounts of energy and cause significant climate pollution to meet our basic needs. Buildings account for 74% of U.S. electricity use and building heating and cooling drives peak electricity demand. Moreover, buildings are where electric vehicles (EVs), solar, storage, heat pumps, water heaters, and other distributed energy resources integrate with the electricity system. Consequently, the buildings sector will play a key role in achieving economywide net-zero emissions by 2050.}, - doi = {10.2172/2338089}, - url = {https://www.osti.gov/biblio/2338089}, - place = {United States}, - year = {2024}, - month = {04}, - note={Accessed:2024-07-30}} - -@misc{skyspark, - author = {SkyFoundry}, - title = {SkySpark Analytics}, - year = {2023}, - note = {\url{https://skyfoundry.com/skyspark}}, -} - -@misc{coppertree, - author = {CopperTree Analytics}, - title = {CopperTree Analytics Platform}, - year = {2023}, - note = {\url{https://www.coppertreeanalytics.com}}, -} - -@article{fdd_review, - author = {Katipamula, Srinivas and Brambley, Michael R.}, - title = {Review of Fault Detection and Diagnostic Methods for Building Systems}, - journal = {HVAC&R Research}, - volume = {11}, - number = {2}, - pages = {169--187}, - year = {2005}, - doi = {10.1080/10789669.2005.10391123} -} - @inproceedings{brick, author = {Balaji, Bharathan and Bhattacharya, Arka and Fierro, Gabe and Gao, Jie and Gluck, Josh and Hong, Deokwoo and Johansen, Aslak and Koh, Jihyun and Ploennigs, Joern and Agarwal, Yuvraj and Whitehouse, Kamin and Taneja, Jayant}, title = {Brick: Metadata Schema for Portable Smart Building Applications}, @@ -114,33 +46,4 @@ @inproceedings{brick pages = {41--50}, publisher = {ACM}, doi = {10.1145/2993422.2993577} -} - -@manual{energyplus, - title = {EnergyPlus Energy Simulation Software 24.1.0}, - author = {{U.S. Department of Energy}}, - year = {2024}, - organization = {U.S. Department of Energy}, - url = {https://energyplus.net/} -} - -@article{spawn, - title={Spawn: coupling Modelica Buildings Library and EnergyPlus to enable new energy system and control applications}, - author={Wetter, Michael and Benne, Kyle and Tummescheit, Hubertus and Winther, Christian}, - journal={Journal of Building Performance Simulation}, - volume={17}, - number={2}, - pages = {274-292}, - year = {2024}, - publisher = {Taylor \& Francis}, - doi = {10.1080/19401493.2023.2266414}, - url = {https://www.tandfonline.com/doi/full/10.1080/19401493.2023.2266414} -} - -@misc{modelica, - author = {{Modelica Association}}, - title = {Modelica – A Unified Object-Oriented Language for Physical Systems Modeling}, - year = {2023}, - note = {Modelica Specification Version 3.6}, - url = {https://specification.modelica.org/maint/3.6/MLS.pdf} } \ No newline at end of file diff --git a/docs/paper.md b/docs/paper.md index 699a221c..6e6ab9c8 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -38,21 +38,17 @@ bibliography: paper.bib # Summary -The Control Strainer, or `ConStrain`, is a python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations or from actual building automation system (BAS) trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a standardized performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. +The Control Strainer, or `ConStrain`, is a Python-based framework that can be used by energy modelers, building engineers, and researchers to conduct consistent and automated verification of building system controls using either timeseries data generated from whole-building energy simulations or from actual building automation system (BAS) trend data. `ConStrain` is made of two distinct components: an expandable control verification algorithms library, and a consistent performance evaluation and reporting workflow framework. At its roots, `ConStrain`'s verification library was developed with the verification of control related building energy code requirements in mind, but it is built such that its library is expandable and can cover user-customized control verifications. # Statement of need -Robust HVAC control is a “no regrets” strategy for building decarbonization, reducing energy use, enabling flexibility and resilience, and supporting the transition to electrified heating, all with low embodied carbon. The Buildings Technology Office (BTO) of the United States Department of Energy’s blueprint has a goal of “more than 50% of all homes and businesses have automated control platforms that reduce energy waste and enable flexibility“ [@bto_blueprint]. - -Advances in building control have shown significant potential for improving building energy performance and decarbonization. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. Driven by the significant control-related energy-saving potential, commercial building energy codes and standards (such as American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1 [@90.1]) have progressed with many control-related addenda. For example, from the publication of 90.1-2004 to 90.1-2016 (four code cycles), 30% of the new requirements are related to building control (with most of them focused on Heating, Ventilation, and Air Conditioning (HVAC) system control) [@impl_ctrl]. - -However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured to meet the energy codes requirement [@impl_ctrl], and control-related compliance verification is typically not included in the commissioning scope. +Advances in building control have shown significant potential for reducing the cost of utility bills and improving building energy performance. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured, and control-related compliance verification is typically not currently included in the commissioning scope. `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. -`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to code (e.g., ASHRAE 90.1) or to a high-performance control guideline (e.g., ASHRAE Guideline 36 [@g36]). Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. +`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to the building and building owner's needs. Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. -`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. `ConStrain` has applications to code-compliance building performance standards (BPS), and commissioning. +`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. `ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. @@ -60,9 +56,9 @@ At present, `ConStrain` expects pre-harmonized input units for each verification ## Comparison with existing tools and industry practices -In current industry practices, HVAC control verification is often conducted manually by commissioning agents or facilities teams, or through proprietary trend data analytics solutions integrated into BAS. These tools, while valuable for fault detection and system monitoring, are generally vendor-specific, offer limited transparency, and are not purpose-built to ensure that control strategies intended to deliver energy savings, such as those specified in energy codes or design standards, are functioning as intended in actual operation. +In current industry practices, HVAC control verification is often conducted manually by commissioning agents or facilities teams, or through proprietary trend data analytics solutions integrated into BAS. These tools, while valuable for fault detection and system monitoring, are generally vendor-specific, offer limited transparency, and are not purpose-built to ensure that control strategies intended to deliver energy savings are functioning as intended in actual operation. -To our knowledge, `ConStrain` is the only open-source software framework focused specifically on automated control verification aligned with building energy code and advanced building control guidelines (e.g., ASHRAE 90.1, Guideline 36). It distinguishes itself by offering: +`ConStrain` distinguishes itself by offering: - A growing library of modular, reusable control logic verification tests - A flexible and local API for custom verification logic and report generation From 9c5b6ff44ecd881a2e2ecfd81f8a408d7ee81c74 Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Tue, 7 Apr 2026 00:25:09 -0700 Subject: [PATCH 28/29] update refs --- docs/paper.bib | 53 ++++++++++++++++++++++++++++++++++++++++++++++++++ docs/paper.md | 8 ++++---- 2 files changed, 57 insertions(+), 4 deletions(-) diff --git a/docs/paper.bib b/docs/paper.bib index bc70a9e1..dbd57ffd 100644 --- a/docs/paper.bib +++ b/docs/paper.bib @@ -1,3 +1,56 @@ +@inproceedings{bs2023_1660, + doi = {10.26868/25222708.2023.1660}, + url = {https://publications.ibpsa.org/conference/paper/?id=bs2023_1660}, + year = {2023}, + month = {September}, + publisher = {IBPSA}, + author = {Chen, Yan and Wetter, Michael and Lei, Xuechen and Lerond, Jeremy and Prakash, Anand K. and Jung, Yun Joon and Ehrlich, Paul and Vrabie, Draguna}, + title = {Control Performance Verification -- The Hidden Opportunity of Ensuring High Performance of Building Control System}, + booktitle = {Proceedings of Building Simulation 2023: 18th Conference of IBPSA}, + volume = {18}, + address = {Shanghai, China}, + series = {Building Simulation}, + pages = {3848--3855}, + issn = {2522-2708} +} + +@inproceedings{lei2023ashrae, + author = {Lei, Xuechen and Lerond, Jeremy and Jung, Yun Joon and Chen, Yan}, + title = {Development of an Application Programming Interface for a Building Systems Control Performance Verification Framework}, + booktitle = {2023 ASHRAE Annual Conference}, + year = {2023}, + doi = {10.63044/s23lei50}, + url = {https://doi.org/10.63044/s23lei50} +} + +@inproceedings{bs2021_30725, + doi = {10.26868/25222708.2021.30725}, + url = {https://publications.ibpsa.org/conference/paper/?id=bs2021_30725}, + year = {2021}, + month = {September}, + publisher = {IBPSA}, + author = {Chen, Yan and Lerond, Jeremy and Lei, Xuechen and Rosenberg, Michael and Vrabie, Draguna}, + title = {A knowledge-based framework for building model performance verification}, + booktitle = {Proceedings of Building Simulation 2021: 17th Conference of IBPSA}, + volume = {17}, + isbn = {978-1-7750520-2-9}, + address = {Bruges, Belgium}, + series = {Building Simulation}, + pages = {1943--1950}, + issn = {2522-2708} +} + +@article{lei2021, + author = {Lei, Xuechen and Chen, Yan and Berg\'{e}s, Mario and Akinci, Burcu}, + title = {Formalized control logic fault definition with ontological reasoning for air handling units}, + journal = {Automation in Construction}, + volume = {129}, + pages = {103781}, + year = {2021}, + issn = {0926-5805}, + doi = {10.1016/j.autcon.2021.103781} +} + @misc{tspr, title={TSPR Washington State Analysis Tool 2024.1.0}, author={{Pacific Northwest National Laboratory}}, diff --git a/docs/paper.md b/docs/paper.md index 6e6ab9c8..77efc182 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -42,13 +42,13 @@ The Control Strainer, or `ConStrain`, is a Python-based framework that can be us # Statement of need -Advances in building control have shown significant potential for reducing the cost of utility bills and improving building energy performance. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance. A field study found that only 50% of systems observed have their control system correctly configured, and control-related compliance verification is typically not currently included in the commissioning scope. +Advances in building control have shown significant potential for reducing the cost of utility bills and improving building energy performance. Studies show that designs utilizing optimized controls that are properly tuned could cut commercial building energy consumption by approximately 29% - equivalent to 4-5 Quads, or 4-5% of the energy consumed in the United States [@impa_ctrl]. However, one of the challenges to realizing those savings is the correct implementation of such advanced control strategies and regularly verifying their actual operational performance [@lei2021]. A field study found that only 50% of systems observed have their control system correctly configured, and control-related compliance verification is typically not currently included in the commissioning scope. -`ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems. +`ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems [@bs2021_30725]. -`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to the building and building owner's needs. Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. +`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to the building and building owner's needs [@lei2023ashrae]. Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. -`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification. +`ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification [@bs2023_1660]. `ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. From 6ad222e828086780d7197ce478d0ccef8b8b0a1e Mon Sep 17 00:00:00 2001 From: "Xuechen (Jerry) Lei" Date: Thu, 9 Apr 2026 00:18:16 -0700 Subject: [PATCH 29/29] modify based on Jeremy feedback --- docs/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/paper.md b/docs/paper.md index 77efc182..56e049ba 100644 --- a/docs/paper.md +++ b/docs/paper.md @@ -46,13 +46,13 @@ Advances in building control have shown significant potential for reducing the c `ConStrain` focuses on formalizing and automating verification of HVAC controls by analyzing sensor and actuator data streams from building control systems [@bs2021_30725]. -`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing BAS data streams for adherence to an operational specification, which can correspond to the building and building owner's needs [@lei2023ashrae]. Note that this API, at its current form, provides a software interface for other Python programs, not a web REST API service. +`ConStrain` is an open-source library and a Python application programming interface (API) for analyzing building automation system (BAS) data streams for adherence to an operational specification, which can correspond to the building and building owner's needs [@lei2023ashrae]. Note that this API, in its current form, provides a software interface for other Python programs, not a web REST API service. `ConStrain` is also incorporating semantic modeling capabilities to enable automated configuration and deployment of verification [@bs2023_1660]. `ConStrain` can be used as a standalone tool and can also be integrated into established workflows of third-party tools and practices. For instance, `ConStrain` has been successfully integrated as part of the continuous integration software development process of whole-building energy simulation-based software tool (e.g., Washington State's Total System Performance Ratio Analysis Tool [@tspr]) to make sure that software code contributions as well as simulation software updates do not have unexpected impacts on the simulated performance of building system controls. Moreover, a set of `OpenStudio` [@os] measures [@osm] have also been developed to enable building energy modelers using `OpenStudio` to have access to perform verification on their models with minimal configurations required. -At present, `ConStrain` expects pre-harmonized input units for each verification case that align with expected data points units defined in its corresponding verification item; automatic unit conversion is not in the core workflow and needs to be handled before feeding data into `ConStrain`. +Currently, `ConStrain` requires each verification case to provide inputs in the same units as the expected data points defined for its verification item. Automatic unit conversion is not in the core workflow of `ConStrain`, so inputs shall be converted to the required units before being passed to `ConStrain`. ## Comparison with existing tools and industry practices