Smart & Resilient Communities/Cities

Optimal Co-Design of Integrated Thermal-Electrical Networks and Control Systems for Grid-interactive Efficient District (GED) Energy Systems

Anonymous — Wed, 14 Oct 2020 20:44:01 +0000

Optimal Co-Design of Integrated Thermal-Electrical Networks and Control Systems for Grid-interactive Efficient District (GED) Energy Systems Anonymous (not verified) Wed, 10/14/2020 - 14:44

Cary Faulkner

Sponsored by U.S. Department of Energy (DOE)

The coordination of thermal-electrical-control networks is essential for the optimal design of grid-interactive efficient district (GED) energy systems, particularly when renewable energy sources are integrated. Led by Dr. Zuo, this $4.16M joint research is to create a holistic open-source modeling and optimization platform for the optimal design and retrofit of GED energy systems. Based on National Renewable Energy Laboratory's URBANopt and Lawrence Berkeley National Laboratory's Modelica Buildings library, this platform can be used to increase system efficiency and resilience of our communities.

Technical Advisory Group

Name	Institution
Ben Ealey	Electric Power Research Institute
Caitlin Holley	ENGIE
Henry Johnstone	GLHN
John Camilleri	PSC
Peter Lilienthal	HOMER Energy by UL
Shalom Flank	Pareto Energy

Team Members:

�鶹ӰԺ:

Wangda Zuo, Associate Professor, Ph.D.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
wangda.zuo@colorado.edu

Kyri Baker, Assistant Professor, Ph.D.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
Kyri.Baker@colorado.edu

Bryan Birosak, Director
Utility and Energy Services, �鶹ӰԺ
bryan.birosak@colorado.edu

Ellen Edwards, Energy Manager
Utility and Energy Services, �鶹ӰԺ
ellen.edwards@colorado.edu

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

Cary Faulkner
Department of Mechanical Engineering, �鶹ӰԺ
cary.faulkner@colorado.edu

Aisling Pigott
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
Aisling.Pigott@colorado.edu

Saranya Anbarasu, M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
saranya.anbarasu@colorado.edu

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

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

Rensselaer Polytechnic Institute:

Luigi Vanfretti, Associate Professor, Ph.D.
Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute
luigi.vanfretti@gmail.com

Tetiana Bogodorova, Research Scientist, Ph.D.
Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute
tetiana.bogodorova@gmail.com

Fernando Fachini
Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute
emaildofachini@gmail.com

University of Texas Austin:

Atila Novoselac, Professor, Ph.D.
Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin
atila@mail.utexas.edu

Ardeshir Moftakhari
Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin
ardeshir.moftakhari@gmail.com

Mengjia Tang
Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin
m.tang@utexas.edu

Lawrence Berkeley National Laboratory:

Michael Wetter, Staff Scientist, Ph.D.
Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory
mwetter@lbl.gov

Jianjun Hu, Principal Scientific Engineering Associate, Ph.D.
Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory
jianjunhu@lbl.gov

National Renewable Energy Laboratory:

Kyle Benne, Researcher, M.S.
National Renewable Energy Laboratory
Kyle.Benne@nrel.gov

Nicholas Long, Senior Engineer, P.E., M.S.
Commercial Buildings Research Group, National Renewable Energy Laboratory
nicholas.long@nrel.gov

Amy Allen, Researcher, M.S.
National Renewable Energy Laboratory
Amy.Allen@nrel.gov

Lauren Klun, Project Manager
National Renewable Energy Laboratory
Lauren.Klun@nrel.gov

Amzur technologies:

Raymond Kaiser, Director of Energy Management Systems
Amzur Technologies
raymond.kaiser@amzur.com

Media Reports

Open source tool aims to improve electric grid efficiency, resiliency

Resulted Open Source Libraries

Journal Publications

K. Hinkelman, S. Anbarasu, M. Wetter, A. Gautier, W. Zuo. 2022. "A Fast and Accurate Modeling Approach for Water and Steam Thermodynamics with Practical Applications in District Heating System Simulation," Energy, 254(4), pp. 124227.

K. Hinkelman, J. Wang, W. Zuo, A. Gautier, M. Wetter, C. Fan, N. Long. 2022. "Modelica-Based Modeling and Simulation of District Cooling Systems: A Case Study." Applied Energy, 311, pp.118654.

Conference Proceedings

F. Fachini, M. d. Castro, M. Liu, T. Bogodorova, L. Vanfretti, W. Zuo. 2022. “Multi-Domain Power and Thermo-Fluid System Stability Modeling using OpenIPSL Library”, 2022 IEEE Power & Energy Society General Meeting (PESGM), July 17-21, Denver, CO.

K. Hinkelman, S. Anbarasu, M. Wetter, A. Gautier, B. Ravache, W. Zuo 2022. "Towards Open-Source Modelica Models For Steam-Based District Heating Systems." Proceedings of the 1st International Workshop On Open Source Modelling And Simulation Of Energy Systems (OSMSES 2022), Aachen, German, April 4-5, 2022.

F. Fachini, L. Vanfretti, M. C. Fernandes, T. Bogodorova, G. Laera 2021. “Modeling and Validation of Renewable Energy Sources in the OpenIPSL Modelica Library.” Proceeding of the 47th Annual Conference of the IEEE Industrial Electronics Society (IECON 2021). October 13-16, Toronto, Canada.

A. Pigott, K. Baker, S. A. Dorado-Rojas, L. Vanfretti 2022. “Dymola-Enabled Reinforcement Learning for Real-time Generator Set-point Optimization.” Proceeding of the 13th Conference on Innovative Smart Grid Technologies (ISGT 2022). February 21-24, Washington, D.C., USA.

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Modernizing Cities via Smart Garden Alleys with Application in Makassar City

Anonymous — Fri, 17 Jul 2020 17:34:44 +0000

Modernizing Cities via Smart Garden Alleys with Application in Makassar City Anonymous (not verified) Fri, 07/17/2020 - 11:34

Cary Faulkner

Sponsored by National Science Foundation

This project is sponsored by the National Science Foundation and is in collaboration with the US Department of State. This project will work to integrate innovations in smart and connected communities to improve garden alleys within the City of Makassar, Indonesia via a synergistic collaboration between US and Indonesian teams and a close partnership with Makassar City. Makassar is striving to become a livable world-class city for a fast-growing, diverse population of 1.7 million people. The ongoing Garden Alley project in the city aims to improve the livability of the city, measured by factors including air-quality, heat index, food security, and social interactions. There are 7520 alleys in Makassar City. To date, Makassar has implemented 40 gardens within 15 of the city's sub-districts, covering a sizable portion of the city's alleys. The goal of this research is to catalyze the transformation of Makassar City's garden alleys into smart environments by deploying a sensor network at representative green allies and conventional allies to collect data related to air quality, microclimates, and other factors, to analyze the heterogeneous data using machine learning techniques, and to then share the data and its insights with city representatives and specific communities within the city.

Project Team

�鶹ӰԺ

Wangda Zuo, Ph.D.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
wangda.zuo@colorado.edu

John Zhai, Ph.D.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
john.zhai@colorado.edu

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

Yizhi Yang , M.S.
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
yizhi.yang@colorado.edu

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

Chris Payne
Fairview High School
ninjakiwi1224@gmail.com

Virginia Polytechnic Institute and State University

Walid Saad, Ph.D.
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University
walids@vt.edu

Alexander DeRieux
Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University
acd1797@vt.edu

Universitas Gadjah Mada

Rachmawan Budiarto, Ph.D., G.P.
Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Indonesia
Centre for Development of Sustainable Region (CDSR)
rachmawan@ugm.ac.id

Irawan Eko Prabowo, M.Eng.
Center for Energy Studies, Universitas Gadjah Mada, Indonesia
irawanekop@ugm.ac.id

Dwi Novitasari, M.Sc.
Department of Electrical and Information Engineering, Universitas Gadjah Mada,
dwi.novitasari@mail.ugm.ac.id

Institut Teknologi Bandung

M Donny Koerniawan, Dr. Eng.
Department of Architecture, Institut Teknologi Bandung, Indonesia
donny@ar.itb.ac.id

Lily Tambunan, Dr.Ir.
Department of Architecture, Institut Teknologi Bandung, Indonesia
lilyrosalina@yahoo.com

Nissa Aulia Ardiani S.T., M.Sc
Department of Architecture, Institut Teknologi Bandung, Indonesia
nissaardiani@gmail.com

Makassar City

Ferdi Mochtar SPt, M.Sc, PhD
Food Security Service, Makassar Government, Indonesia
Ferdy_mochtar@yahoo.com

Universitas Hasanuddin

Edward Syarif, Dr. Ir.
Department of Architecture, Universitas Hasanuddin, Indonesia
edosyarif@yahoo.com

Press Release

Project Updates

Publication

Z. Mahrez, E. Sabir, E. Badidi, W Saad, M Sadik 2021. "Smart Urban Mobility: When Mobility Systems Meet Smart Data." IEEE transactions on intelligent transportation systems.

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Support for District Energy Simulation with Modelica

Anonymous — Wed, 12 Jun 2019 22:21:23 +0000

Support for District Energy Simulation with Modelica Anonymous (not verified) Wed, 06/12/2019 - 16:21

Sponsored by U.S. Department of Energy (DOE)

CU East District Energy Plant

District heating and cooling (DHC) systems commonly involve a central plant that distributes steam, hot water, or chilled water to buildings by means of insulated pipes. This is a promising and long-established solution for community sustainability, yet it remains underutilized, particularly in the United States. By sharing thermal resources, DHC can reduce the carbon intensity of heating and cooling in buildings, reduce energy costs, improve air quality, allow high penetration of renewable energy sources, recycle waste heat from industrial and commercial activities, and improve the resiliency of communities. In collaboration with the National Renewable Energy Laboratory (NREL) and Lawrence Berkeley National Laboratory (LBNL), the goal of this project is to create a new software analysis platform that leverages the Modelica language in order to enable developers of community-scale construction projects to effectively evaluate and optimize DHC systems. The models will be publicly released in LBNL's Modelica Buildings Library and used by NREL's URBANopt.

Collaborators:

Journal Publications

K. Hinkelman, J. Wang, W. Zuo, A. Gautier, M. Wetter, C. Fan, N. Long. 2022. "Modelica-Based Modeling and Simulation of District Cooling Systems: A Case Study." Applied Energy, 311, pp.118654.

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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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Comprehensive Pliant Permissive Priority Optimization

Anonymous — Mon, 14 Jan 2019 01:10:12 +0000

Comprehensive Pliant Permissive Priority Optimization Anonymous (not verified) Sun, 01/13/2019 - 18:10

This project is funded by Department of Energy and 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.

Collaborators

Journal publications

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.
J. Wang, S. Huang, W. Zuo, D. Vrabie 2021. “Occupant Preference-Aware Load Scheduling for Resilient Communities.” Energy and Buildings, 252, pp. 111399.
J. Wang, K. Garifi, K. Baker, W. Zuo, Y. Zhang, S. Huang, D. Vrabie 2020. "Optimal Renewable Resource Allocation and Load Scheduling of Resilient Communities." Energies, 13, pp. 5683.

Conference Proceedings

J. Wang, W. Zuo, S. Huang, D. Vrabie 2020. “Data-driven Prediction of Occupant Presence and Lighting Power: A Case Study for Small Commercial Buildings.” American Modelica Conference 2020, Virtual Conference, September 22-24.
Y. Fu, S. Huang, Y. Liu, T. McDermott, D. Vrabie, W. Zuo 2019. “A Multidisciplinary Model to Couple Power System Dynamics and Building Dynamics to Enable Building-to-Grid Integration.” Proceeding of the 16th Conference of International Building Performance Simulation Association (Building Simulation 2019), September 2-4, Rome, Italy.
Y. Fu, S. Huang, D. Vrabie, W. Zuo 2019. “Coupling Power System Dynamics and Building Dynamics to Enabling Building-to-Grid Integration.” Proceedings of the 13th International Modelica Conference, pp. 561-566, March 4-6, Regensburg, Germany.

Open Source Model Release

A open source Modelica library for the net zero energy community (NZEC) is built to facilitate the design and operation of a real NZEC. The models and related training materials are available at Net Zero Energy Community (NZEC) Library.

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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, �鶹ӰԺ 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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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ӰԺ
wangda.zuo@colorado.edu

Graduate Students:

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

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

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

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

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

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

Yizhi Yang, M.S,
Department of Civil, Environmental and Architectural Engineering, �鶹ӰԺ
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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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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