Urban scale modeling

Virtual Electric Power Board (EPB)

Anonymous — Tue, 11 Jun 2019 23:36:28 +0000

Virtual Electric Power Board (EPB) Anonymous (not verified) Tue, 06/11/2019 - 17:36

The goal of this collaborative research, with ORNL (who is the overall project lead) and the Electric Power Board (EPB) of Chattanooga, is to create calibrated virtual models of buildings within a utility’s service area to enable advanced grid modeling research (AGMR) integration with utility business systems. This will be achieved by making use of DOE’s suite of prototypical buildings, integrating available data sources for buildings with properties extracted from image processing of satellite and aerial imagery, developing leadership-class high performance computing capabilities for large-scale building simulations, and extracting relevant 15-minute utility data from advanced metering infrastructure (AMI) deployed for 176,579 buildings in EPB’s utility district.

Collaborator: Oak Ridge National Laboratory

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An Innovative Computational Platform for Robust and Optimal Operation of Renewable Energy Cities

Anonymous — Sat, 24 Nov 2018 18:04:00 +0000

An Innovative Computational Platform for Robust and Optimal Operation of Renewable Energy Cities Anonymous (not verified) Sat, 11/24/2018 - 11:04

As international sustainability goals and U.S. sustainability initiatives increase, sustainable energy applications are evolving from the conventional single building to the entire city. A 100% renewable energy city (REC) will undoubtedly play a pivotal role in this progression. The energy system of a REC will integrate many subsystems including renewable energy generation, distribution networks, building energy consumption, electric and thermal storage, and interaction with the power grid.

This proposed project is to create the scientific foundation of an innovative computational platform that will enable robust and optimal operation of future renewable energy cities.

Collaborator: National Renewable Energy Laboratory, Boulder Housing Partners, Amzur Technologies

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CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities

Anonymous — Sun, 01 Jan 2017 07:00:00 +0000

CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities Anonymous (not verified) Sun, 01/01/2017 - 00:00

The goal of this research is to create new paradigms for the resilient design of urban communities, and uniquely tailored toward the design of coastal cities, thus contributing to NSF's science and engineering mission. By bringing together an interdisciplinary set of collaborators from engineering, architecture, and social sciences, this research will yield several key innovations:

a holistic human-centered computational framework for the design of resilient cities;
identification of key typologies, morphologies and their interdependencies by analyzing the urban design and its infrastructure networks;
an innovative flexible modeling and computational framework that integrate socioeconomic characteristics for simulation and resilience optimization (damage tolerance) of the critical infrastructure;
a novel optimization framework that will facilitate making damage tolerance decisions that can achieve anticipatory resilience in face of disaster uncertainty;
new identified interdependences, trends, and typologies of socioeconomic system of highly urbanized coastal communities based on the cities of Miami and Miami Beach in Florida.

In summary, this research will lay the scientific foundation for envisioning and redesigning resilient coastal cities making them ready to meet anticipated future challenges.

Go to the project website to learn more

Collaborators

City of Miami
City of Miami Beach
Unversity of Miami
Virginia Polytechnic Institute and State University

Press Release

Journal Publications

J. Wang, W. Zuo, L. Rhode-Barbarigos, X. Lu, J. Wang, Y. Lin 2019. “Literature Review on Modeling and Simulation of Energy Infrastructures from a Resilience Perspective.” Reliability Engineering and System Safety, 183, pp. 360-373.

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Veritas News "College of Engineering, School of Architecture receive NSF grant to study resiliency of coastal cities"

Anonymous — Wed, 05 Oct 2016 22:52:17 +0000

Veritas News "College of Engineering, School of Architecture receive NSF grant to study resiliency of coastal cities" Anonymous (not verified) Wed, 10/05/2016 - 16:52

Jing Wang

University of Miami Veritas News reported our new grant to study resiliency of coastal cities as part of the CRISP project.

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National Science Foundation News Release 16-119 "NSF awards $22.7 million to strengthen nation's infrastructure"

Anonymous — Wed, 05 Oct 2016 22:44:40 +0000

National Science Foundation News Release 16-119 "NSF awards $22.7 million to strengthen nation's infrastructure" Anonymous (not verified) Wed, 10/05/2016 - 16:44

Jing Wang

National Science Foundation released our new grant for the CRISP project. This project aims to strengthen the nation's critical infrastructures with a holistic numerical framework.

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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, �鶹��Ƶ
wangda.zuo@colorado.edu

Graduate Students:

Jing Wang, M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
jing.wang@colorado.edu

Katy Hinkelman, M.S., EIT
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
kathryn.hinkelman@colorado.edu

Saranya Anbarasu, M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
saan1256@colorado.edu

Mingzhe Liu, Ph.D.
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
mingzhe.liu@colorado.edu

Chengnan Shi, M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
chengnan.shi@colorado.edu

Yingli Lou, M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
yingli.lou@colorado.edu

Yizhi Yang, M.S,
Department of Civil, Environmental and Architectural Engineering, �鶹��Ƶ
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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National Science Foundation Award Announcement "A human-centered computational framework for urban and community design of resilient coastal cities"

Anonymous — Mon, 29 Aug 2016 15:06:33 +0000

National Science Foundation Award Announcement "A human-centered computational framework for urban and community design of resilient coastal cities" Anonymous (not verified) Mon, 08/29/2016 - 09:06

Jing Wang

The National Science Foundation awarded our new research grant "CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities".

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Design “ZenCiti” Smart City in the Yucatán

Anonymous — Mon, 01 Aug 2016 06:00:00 +0000

Design “ZenCiti” Smart City in the Yucatán Anonymous (not verified) Mon, 08/01/2016 - 00:00

[video:https://youtu.be/36rWLXS8Lo4]

The SBS lab is working with School of Architecture, Center of Computaitional Science to create ZenCiti, a “smart city” expected to revolutionize the IT world with its integration of technology into everyday life. The project will be built next to the Yucatán Science and Technology Park (YSTP). The SBS Lab is working on the renewable energy generation and energy infrastructure of ZenCiti. Conventional and innovative technologies will be used. Conventional technologies are overhangs and landscaping, thermal insulation, rooftop PV, green roof, etc. Innovative technologies are automatic shading, distributed energy resources, building integrated photovoltaics, photonic radiatve cooler, etc. The SBS lab aims to make ZenCiti more energy efficient, convenient, and comfortable.

Press release

UM News "UM to Design Smart City in the Yucatan"

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