Building Energy Modeling - OpenStudio SDK Development and Management

Anonymous — Thu, 14 Feb 2019 18:47:50 +0000

Building Energy Modeling - OpenStudio SDK Development and Management Anonymous (not verified) Thu, 02/14/2019 - 11:47

Angelique Fathy

In support of DOE’s Building Energy Codes Program, Pacific Northwest National Laboratory (PNNL) developed a suite of prototype building models representing newly constructed commercial buildings that comply with ASHRAE Standard 90.1 and IECC requirements. In this project, we will collaborate with PNNL on developing and improving the OpenStudio versions of the prototype building models.

Collaborator

Pacific Northwest National Laboratory

Publications

Conference Proceedings

1. Y. Lou, Y. Ye, W. Zuo, J. Zhang 2021. "Energy Prediction Impact of the Space Level Occupancy Schedule for a Primary School." Proceeding of the 17th Conference of International Building Performance Simulation Association (Building Simulation 2021), September 1-3, Bruges, Belgium.

Presentation

Y. Lou 2021 "Energy Prediction Impact of the Space Level Occupancy Schedule for a Primary School", Building Simulation 2021 Conference, September.

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New research project "Comprehensive Pliant Permissive Priority Optimization" funded by DOE

Anonymous — Mon, 14 Jan 2019 00:53:31 +0000

New research project "Comprehensive Pliant Permissive Priority Optimization" funded by DOE Anonymous (not verified) Sun, 01/13/2019 - 17:53

Jing Wang

Recently, our lab received a new funded project studying “Comprehensive Pliant Permissive Priority Optimization”. The project is funded by Department of Energy and it is a joint project with Pacific Northwest National Laboratory and Oak Ridge National Laboratory.

The project goal is to develop a framework to prioritize behind-the-meter end-use resources, and a prototype tool that offers assessment of end-use load-utilization patterns and provides real-time dynamic prioritization of the energy-consuming loads based on end-use functional utility to satisfy occupant activity requirements. The project period is 01/2019-09/2020.

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Improving Data Center Energy Efficiency through End-to-End Cooling Modeling and Optimization

Anonymous — Sat, 01 Oct 2016 06:00:00 +0000

Improving Data Center Energy Efficiency through End-to-End Cooling Modeling and Optimization Anonymous (not verified) Sat, 10/01/2016 - 00:00

Led by Dr. Zuo, this is a joint research project with Lawrence Berkeley National Laboratory and Schneider Electric. We have developed an open-source, free software package (see the following links) which provides practical, end-to-end (from the IT equipment to heat rejection to the ambient) modeling and optimization for data center cooling. It can be used as a stand-alone tool by data center designers, service consultants and facility managers, or be integrated into existing data center management software for autonomous optimal operation. It is the first practical tool that couples the modeling of airflow-management and cooling systems to enable a global data center cooling optimization. Its self-learning regression model enabled by an in situ adaptive tabulation algorithm and a fast fluid dynamics model can predict the critical airflow information under various operational conditions within a few milliseconds. The equation-based modeling language allows a fast and flexible modeling of various cooling system configurations. We have demonstrated the usage of our tool and identified 53% energy saving potentials in a Florida data center and 74% in the Massachusetts data center.

Open Source Models for Data Center Cooling

This project has resulted in open source Modelica models for the data center cooling system. The models haven been released as a part of the DOE's open source Modelica Buildings library: http://simulationresearch.lbl.gov/modelica/releases/latest/help/Buildings_Applications.html#Buildings.Applications.

The model development branch is at https://github.com/lbl-srg/modelica-buildings/tree/master/Buildings/Applications.

This project has also developed a reduced order model “ISAT-FFD” trained by simulations in Fast Fluid Dynamics to predict airflow in data centers: https://github.com/doetools/isat_ffd.

See this page for more information on FFD.

The development site of the ISAT module in Modelica Buildings library is at: https://bitbucket.org/sbslab-zuo/datacenter-mblisat.

The ISAT data center case can be found at: https://bitbucket.org/sbslab-zuo/datacenter-isat-examples/src/master/.

Please see this page for more information on tools related to this project.

Commerical Tool

Based on our open source FFD models, Schneider Electric developed a commerial software "EcoStruxure IT Advisor CFD", which is a cloud-based data center CFD design software.

Technical Advisory Group

Name	Institution
Amistadi, Henry R.	MITRE Corporation
Cleaver, Donald	Keystone Critical Systems & Advisors
Doppelhammer, F. James	University of Miami
Geraghty, Edward P.	CEC Group, LLC
Groenewold, John	JPMorgan Chase & Co.
Herrlin, Magnus	Lawrence Berkeley National Laboratory
Kaiser, Raymond	Amzur Technologies
Meneghan, Brian W.	Carrier Corporation
Plamondon, David	University of Massachusetts Medical School
Sartor, Dale	Lawrence Berkeley National Laboratory
Sorell, Vali	Syska Hennessy Group, Inc.

Collaborators

Press Release

Publications

Project Report

W. Zuo, M. Wetter, J. VanGilder, X. Han, Y. Fu, C. Faulkner, J. Hu, W. Tian, M. Condor 2021. “Improving Data Center Energy Efficiency through End-to-End Cooling Modeling and Optimization.” pp. 1-109, Report for US Department of Energy, DOE-CU�鶹ӰԺ-07688.

Recorded Presentations

W. Zuo 2020 "Open Source Modelica Models for Data Center Cooling", American Modelica Conference 2020, September.

Ph.D. Theses

Y. Fu 2020. "Modeling and Control for Grid-interactive Efficient Data Centers." Ph.D. Thesis, Department of Civil, Environmental, and Architectural Engineering, �鶹ӰԺ.
X. Han 2020. "Holistic Optimization of Data Center Cooling Systems and Airflow Management." Ph.D. Thesis, Department of Civil, Environmental, and Architectural Engineering, �鶹ӰԺ.

Journal Articles

X. Han, W. Tian, J. VanGilder, W. Zuo, C. Faulkner 2021. "An Open Source Fast Fluid Dynamics Model for Data Center Thermal Management." Energy and Buildings, 230, pp 110599.
Y. Fu, X. Han, K. Baker, W. Zuo 2020. “Assessments of Data Centers for Provision of Frequency Regulation.” Applied Energy, 277, pp 115621.
Y. Fu, W. Zuo, M. Wetter, J. W. VanGilder, P. Yang 2019. "Equation-Based Object-Oriented Modeling and Simulation of Data Center Cooling Systems." Energy and Buildings, 198, pp. 503-519.
W. Tian, J.W. VanGilder, X. Han, C.M. Healey, M.B. Condor, W. Zuo 2019. “A New Fast Fluid Dynamics Model for Data-Center Floor Plenums.” ASHRAE Transactions, 125, pp. 141-148.
Y. Fu, W. Zuo, M. Wetter, J. W. VanGilder, X. Han, D. Plamondon 2019. “Equation-Based Object-Oriented Modeling and Simulation for Data Center Cooling: A Case Study.” Energy and Buildings,186, pp. 108-125.
W. Tian, X. Han, W. Zuo, M. Sohn 2018. "Building Energy Simulation Coupled with CFD for Indoor Environment: A Critical Review and Recent Applications." Energy and Buildings, 165, pp.184-199.
W. Tian, T. A. Sevilla, D. Li, W. Zuo, M. Wetter 2018. "Fast and Self-Learning Indoor Airflow Simulation Based on In Situ Adaptive Tabulation." Journal of Building Performance Simulation, 11(1), pp. 99-112.
W. Tian, T. A. Sevilla, W. Zuo, M. Sohn 2017. "Coupling Fast Fluid Dynamics and Multizone Airflow Models in Modelica Buildings Library to Simulate the Dynamics of HVAC System." Building and Environment, 122, pp. 269-286.

Conference Proceedings

X. Han, W. Tian, W. Zuo, J.W. VanGilder 2019. “Optimization of Workload Distribution of Data Centers Based on a Self-Learning In Situ Adaptive Tabulation Model.” Proceeding of the 16th Conference of International Building Performance Simulation Association (Building Simulation 2019), September 2-4, Rome, Italy.
W. Tian, J.W. VanGilder, M.B. Condor, X. Han, W. Zuo 2019. “An Accurate Fast Fluid Dynamics Model for Data Center Applications.” The Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm 2019), May 28-31, Las Vegas, NV.
Y. Fu, M. Wetter, W. Zuo 2018. “Modelica Models for Data Center Cooling Systems.” 2018 ASHRAE Building Performance Analysis Conference and SimBuild (BPACS 2018), pp. 438-445, September 26-28, Chicago, IL.
W. Tian, W. Zuo, T. A. Sevilla, M. Sohn 2017. “Coupled Simulation Between CFD and Multizone Models Based on Modelica Buildings Library to Study Indoor Environment Control.” Proceedings of the 12th International Modelica Conference, pp. 55-61, May 15-17, Prague, Czech Republic.

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Dr. Zuo received research grant from Department of Energy

Anonymous — Wed, 20 Jul 2016 20:46:46 +0000

Dr. Zuo received research grant from Department of Energy Anonymous (not verified) Wed, 07/20/2016 - 14:46

Jing Wang

Dr. Zuo received a research grant from the US Department of Energy for his proposal titled "Improving Data Center Energy Efficiency through End-to-End Cooling Modeling and Optimization". Led by Dr. Zuo, this is a joint research project with Lawrence Berkeley National Laboratory and Schneider Electric. Congratulations!

For the official DOE announcement, click here.

Go to our research page to learn more.

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Department of Energy Press Release "Energy Department invests $19 million to improve efficiency of nation’s buildings"

Anonymous — Fri, 15 Jul 2016 15:17:38 +0000

Department of Energy Press Release "Energy Department invests $19 million to improve efficiency of nation’s buildings" Anonymous (not verified) Fri, 07/15/2016 - 09:17

Jing Wang

Department of Energy reported their investment of $19 million to improve efficiency of the nation's buildings. Our group's data center project was involved.

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