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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-CUBoulder-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, University of Colorado Boulder.
X. Han 2020. "Holistic Optimization of Data Center Cooling Systems and Airflow Management." Ph.D. Thesis, Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder.

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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BIGDATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities

Anonymous — Thu, 01 Sep 2016 06:00:00 +0000

BIGDATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities Anonymous (not verified) Thu, 09/01/2016 - 00:00

The goal of this project is to develop a new planning framework for smart, connected and sustainable communities that allows meeting such zero energy, zero outage, and zero congestions goals by optimally deciding on how, when, and where to deploy or upgrade a community's infrastructure. By bringing together interdisciplinary domain experts from data science, electrical engineering, and civil and architectural engineering, this research will yield several innovations:

Novel big data techniques for faithfully creating spatiotemporal models for smart communities that integrate data from heterogeneous sources and shed light on the composition and operation of a given smart community;
Novel, data driven performance metrics that advance powerful mathematical tools from stochastic geometry to explicitly quantify the health of smart communities via tractable notions of zero energy, zero outage, and zero congestion;
Advanced analytical tools that bring forward novel ideas from optimization theory to devise the most effective strategies for deploying, upgrading, and operating various community infrastructure nodes, given the scale, dynamics, and structure of both the data and the community;
A virtual smart community testbed that can accurately reconstruct, simulate, and evaluate the theoretical framework by leveraging open nonproprietary real world big data sets.

Go to project website to read more

Project Team

Faculty:

Wangda Zuo, Ph.D.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
wangda.zuo@colorado.edu

Graduate �鶹��Ժ:

Jing Wang, M.S.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
jing.wang@colorado.edu

Katy Hinkelman, M.S., EIT
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
kathryn.hinkelman@colorado.edu

Saranya Anbarasu, M.S.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
saan1256@colorado.edu

Mingzhe Liu, Ph.D.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
mingzhe.liu@colorado.edu

Chengnan Shi, M.S.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
chengnan.shi@colorado.edu

Yingli Lou, M.S.
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
yingli.lou@colorado.edu

Yizhi Yang, M.S,
Department of Civil, Environmental and Architectural Engineering, University of Colorado Boulder
yizhi.yang@colorado.edu

Collaborators

Resulted Open Source Libraries

This project has developed two open source Modelica libraries:

Press Release

Publications

Journal articles

J. Wang, S. Huang, W. Zuo, D. Vrabie 2021. “Occupant Preference-Aware Load Scheduling for Resilient Communities.” Energy and Buildings, 252, pp. 111399.
S. Huang, J. Wang, Y. Fu, W. Zuo, K. Hinkelman, R. M. Kaiser, D. He, D. Vrabie 2021. “An Open-source Virtual Testbed for a Real Net-Zero Energy Community”. Sustainable Cities and Society, 75, pp. 103255.
Y. Ye, K. Hinkelman, Y. Lou, W. Zuo, G. Wang, G., J. Zhang 2021. "Evaluating the Energy Impact Potential of Energy Efficiency Measures for Retrofit Applications: A Case Study with US Medium Office Buildings." Building Simulation, pp. 1-17.
S, Huang, Y. Ye, Di. Wu, W. Zuo 2021. “An Assessment of Power Flexibility from Commercial Building Cooling Systems in the United States.” Energy, 221, pp. 119571.
Y. Ye, Y. Lou, W. Zuo, E. Franconi, G. Wang 2020. "How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings." Energy and Buildings, 224, pp. 110267.
YY. Ye, Y. Lou, M. Strong, S. Upadhyaya, W. Zuo, G. Wang 2020. "Development of New Baseline Models for U.S. Medium Office Buildings Based on Commercial Buildings Energy Consumption Survey Data." Science and Technology for the Built Environment, 26 (9), pp. 1321-1336.
W. Tian, X. Han, W. Zuo, Q. Wang, Y. Fu, M. Jin 2019. “An Optimization Platform Based on Coupled Indoor Environment and HVAC Simulation and Its Application in Optimal Thermostat Placement.” Energy and Buildings, 199, pp. 342-251.
S. Huang, X. Lu, W. Zuo, X. Zhang, C. Liang 2019. "Model-Based Optimal Operation of Heating Tower Heat Pump Systems." Building and Environment, 160, pp. 106199.
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.
X. Lu, K. Hinkelman, Y. Fu, J. Wang, W. Zuo, Q. Zhang, W. Saad 2019. “An Open Source Modeling Framework for Interdependent Energy-Transportation-Communication Infrastructure in Smart and Connected Communities.” IEEE Access, 7, pp. 55458-55476.
S. Huang, Y. Ye, X. Han, W. Zuo, X. Zhang, L. Jiang 2019. “Performance Evaluation of Heating Tower Heat Pump Systems over the World.” Energy Conversion and Management, 186, pp. 500-515.
S. Huang, W. Zuo, H. Lu, C. Liang, X. Zhang 2019. “Performance Comparison of a Heating Tower Heat Pump and an Air-Source Heat Pump: A Comprehensive Modeling and Simulation Study.” Energy Conversion and Management, 180, pp. 1039-1054.
G. Zhou, Y. Ye, W. Zuo, X. Zhou, X. Xu 2018. “Fast and Efficient Prediction of Finned-Tube Heat Exchanger Performance Using Wet-Dry Transformation Method with Nominal Data.” Applied Thermal Engineering, 145, pp. 133-146.
G. Zhou, Y. Ye, J. Wang, W. Zuo, Y. Fu, X. Zhou 2018. “Modeling Air-to-Air Plate-Fin Heat Exchanger Without Dehumidification.” Applied Thermal Engineering, 143, pp. 137-148.

Conference Proceedings

S. Anbarasu, K. Hinkelman, W. Zuo. 2022. “Tracing the Dependency of Water and Energy in Smart and Connected Communities through a Multi-Domain Modeling Framework.” The 5th International Conference on Building Energy and Environment (COBEE 2022). July 25-29, Montreal, Canada.
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.
J. Wang, K.N. Garifi, K.A. Baker, W. Zuo, Y. Zhang 2020. “Optimal Operation for Resilient Communities Through A Hierarchical Load Scheduling Framework.” 2020 Building Performance Modeling Conference and SimBuild, Virtual Conference, September 29-October 1.
K. Hinkelman, S. Huang, J. Wang, J. Lian, W. Zuo 2019. “Enhancing the Implementation of a First-order Equivalent Thermal Parameter Model to Enable Accurate and Robust Building Thermal Response Prediction.” 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.
Q. Wang, Y. Pan, Z. Huang, W. Zuo, P. Xu 2018. “A Case Study of Simulation-Based PID Tuning Method for a Room Temperature Controller Using Uncertainty Analysis.” The 4^th Asia Conference of International Building Performance Simulation Association - ASim2018, December 3-5, Hong Kong.
X. Lu, Y. Fu, W. Zuo 2018. “Modeling of Smart Community Infrastructure Accounting for the Interdependencies among Energy, Transportation and Communication Networks.” 2018 ASHRAE Building Performance Analysis Conference and SimBuild (BPACS 2018), pp. 250-257, September 26-28, Chicago, IL.

Presentations

K. Hinkelman 2020 "A Modeling Framework to Evaluate Energy, Transportation, and Communication Interdependence in Smart and Connected Communities", American Modelica Conference 2020, September.

Workshop

J. Wang, S. Huang, W. Zuo 2020 "Cyber-Physical System Modeling using Modelica for Smart and Sustainable Communities", the free workshop on "Cyber-physical System Modeling using Modelica for Smart and Sustainable Communities" on September 18.

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Energy Modeling of Typical Commercial Buildings in Support of ASHRAE Building Energy Quotient Energy Rating Program

Anonymous — Fri, 01 Apr 2016 06:00:00 +0000

Energy Modeling of Typical Commercial Buildings in Support of ASHRAE Building Energy Quotient Energy Rating Program Anonymous (not verified) Fri, 04/01/2016 - 00:00

The objective of this research is to reconcile the differences between the empirical and modeled baselines for energy performance comparison for new and existing commercial buildings, allowing seamless translation of building energy performance metrics among LEED, Standard 90.1, Standard 189.1, Standard 100, and the bEQ As Designed and In Operation ratings. This research is to:

Evaluate and characterize the variability of EUI with building characteristics for standard building types using both statistical analysis of CBECS data and parametric variation of prototype energy models.
Develop a set of modeling assumptions and correction procedures that provide consistent baselines for energy performance metrics for new and existing commercial buildings based on measured EUI of existing buildings.
Validate the modeling assumptions and correction procedures by demonstrating that energy models of buildings with average construction characteristics predict median energy performance.
Using the methods developed above, develop a procedure to relate the EUI of an ASHRAE Standard 90.1-2004 compliant building to the median EUI of existing buildings of the same type and in the same climate.

Collaborators

University of Miami

Open Source Release

During the project, we have develop new prototype building energy models based on the CBECS data. Those models have been open source released at Building Energy Models for Commercial Buildings Based on CBECS Data

Press Release

UM COE News "Dr. Zuo's proposal of ASHRAE1771-TRP fully funded"

Publications

Ph.D. Thesis:

Y. Ye 2019. "Standardized Computational Framework for Prototypical Building Energy Model Creation and Building Energy Analyses." Department of Civil, Environmental, and Architectural Engineering, University of Colorado Boulder.

Journal Articles

Y., Ye, K. Hinkelman, Y. Lou, W. Zuo, G. Wang, G., J. Zhang 2021. "Evaluating the Energy Impact Potential of Energy Efficiency Measures for Retrofit Applications: A Case Study with US Medium Office Buildings." Building Simulation, pp. 1-17.
Y. Ye, Y. Lou, W. Zuo, E. Franconi, G. Wang 2020. "How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings." Energy and Buildings, 224, pp. 110267.
Y. Ye, Y. Lou, M. Strong, S. Upadhyaya, W. Zuo, G. Wang 2020. "Development of New Baseline Models for U.S. Medium Office Buildings Based on Commercial Buildings Energy Consumption Survey Data." Science and Technology for the Built Environment, 26 (9), pp. 1321-1336.
Y. Ye, K. Hinkelman, J. Zhang, W. Zuo, G. Wang 2019. “A Methodology to Create Prototypical Building Energy Models for Existing Buildings: A Case Study on U.S. Religious Worship Buildings.” Energy and Buildings, 194, pp. 351-365.
Y. Ye, W. Zuo, G. Wang 2019. “A Comprehensive Review of Energy-Related Data for U.S. Commercial Buildings.” Energy and Buildings, 186, pp. 126-137.

Conference Proceedings

Y. Ye, K. Hinkelman, J. Zhang, Y. Xie, W. Zuo 2019. “A Methodology to Quantify the Impact of Building Energy Code Upgrades on Building Energy Savings: A Case Study on Small Offices.” Proceeding of the 16th Conference of International Building Performance Simulation Association (Building Simulation 2019), September 2-4, Rome, Italy.
Y. Ye, K. Hinkelman, W. Zuo, G. Wang 2019. “ASHRAE TRP-1771: Methodology to Evaluate Sensitive Levels of Inputs for US Commercial Building Models.” ASHRAE 2019 Annual Conference, June 22-26, Kansas City, MO.
Y. Ye, G. Wang, W. Zuo, P. Yang, K. Joshi 2018. “Development of a Baseline Building Model of Auto Service and Repair Shop.” 2018 ASHRAE Building Performance Analysis Conference and SimBuild (BPACS 2018), pp. 573-580, September 26-28, Chicago, IL.
Y. Ye, G. Wang, W. Zuo 2018. “Creation of a Prototype Building Model of College and University Building.” Proceedings of the 4th International Conference on Building Energy and Environment (COBEE2018), pp. 373-378, February 5-9, Melbourne, Australia.

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