Sponsored by National Science Foundation

This is a 3-year international collaborative research project among 糖心Vlog破解版,  and  in United Kingdom. Residential buildings account for 14%-27% of greenhouse gas (GHG) emissions in the three jurisdictions and cause significant negative impact on the environment. Supported by  in the United States, the in the Republic of Ireland (RoI), and the  (NI), this joint research aims to reduce residential building energy consumption and related GHG emissions and environmental impacts across the three jurisdictions. The research will create decision support tools to inform policy makers, planners, and other stakeholders about the most beneficial residential retrofitting solutions at multiple scales (local to national). The methodology employed will lie at the confluence of various expertise, including green engineering of the NI team, building energy modeling and machine learning of the U.S. team, and information theory of the RoI team. The aim is to transform diverse public datasets in the three jurisdictions into actionable information. Empowered by this information, the anticipation is that better decisions can guide modern societies towards transformative green solutions for the built environment that leverage sustainable engineering systems and enable the creation of energy-efficient, healthy, and comfortable buildings for a nation's citizens. The approach is cognizant of society's need to provide ecological protection while maintaining favorable economic conditions.

This joint research seeks to provide the foundational science needed to design, optimize, and deploy green engineering approaches that reduce residential building energy consumption and related GHG emissions. The interdisciplinary research targets to yield three results: 1) A methodology for data ingestion and an ontology and associated server that provides both a means of accessing and subsequently homogenizing data for both the data enrichment and the modeling processes. The intent is to enable previously unused data sources to be utilized as a whole to significantly improve the accuracy of modeling processes; 2) An advanced automated building energy model generation method powered by physics-informed machine learning, which can improve the efficiency of model generation, significantly reduce computing demand for large scale building energy prediction and protect building users' privacy. Algorithms will also be created to enable robust prediction with incomplete datasets; 3) A new complementary solution for predicting the GHG emissions reduction potential for stakeholders will be created to analyze near/zero GHG buildings in terms of energy performance. It is anticipated that these results will be beneficial both in terms of making buildings greener by reducing GHG emissions and energy consumption as well as decreasing operational costs. The plan is to seek the U.S. Department of Energy's Pacific Northwest National Laboratory to adopt the research results in their national building energy policy analysis for 139 million homes. The Northern Ireland Housing Executive will utilize this work to help predict decarbonization pathways for their housing stock of nearly 86,000 homes (10% of the housing stock in NI). The research will also assist the Sustainable Energy Authority of Ireland for its retrofit plan of 500,000 homes in the Republic of Ireland.

Project Team

糖心Vlog破解版

Wangda Zuo, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版, United States
wangda.zuo@colorado.edu 

Yingli Lou
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版, United States
yingli.lou@colorado.edu

Yizhi Yang
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版, United States
yizhi.yang@colorado.edu

Ulster University

Belfast School of Architecture and the Built Environment, Ulster University, Northern Ireland
nj.hewitt@ulster.ac.uk

University College Dublin

School of Mechanical and Materials Engineering and UCD Energy Institute, University College Dublin, Ireland 
james.odonnell@ucd.ie

School of Mechanical and Materials Engineering and UCD Energy Institute, University College Dublin, Ireland 
cathal.hoare@ucd.ie

School of Mechanical and Materials Engineering and UCD Energy Institute, University College Dublin, Ireland 
usman.ali@ucd.ie

Collaborators

• United States
• Ireland
• Northern Ireland

Publications

Journal Article

Y. Lou, Y. Ye, Y. Yang, W. Zuo 2022. 鈥溾�� Building and Environment, 210, pp. 108683.

Y. Lou, Y. Yang, Y. Ye, W. Zuo, J. Wang 2021. 鈥溾�� Energy and Buildings, 253, pp. 111514.

J. Neale, M. H. Shamsi, E. Mangina, D. Finn, J. O鈥橠onnell 2022. "" Applied Energy, 315, pp. 118956.

Press Release

•  (01/22-08/24)
•  (09/21-12/2021)
• "International research partnership aims to reduce residential energy consumption" by College of Engineering at the 糖心Vlog破解版
• "" by UCD Energy Institute

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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 and Lawrence Berkeley National Laboratory's , this platform can be used to increase system efficiency and resilience of our communities.

Technical Advisory Group

Team Members:

糖心Vlog破解版: 

Wangda Zuo, Associate Professor, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
wangda.zuo@colorado.edu

 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
Kyri.Baker@colorado.edu

Bryan Birosak, Director
Utility and Energy Services, 糖心Vlog破解版
bryan.birosak@colorado.edu

Ellen Edwards, Energy Manager
Utility and Energy Services, 糖心Vlog破解版
ellen.edwards@colorado.edu

Katy Hinkelman, M.S., EIT 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
kathryn.hinkelman@colorado.edu

Cary Faulkner 
Department of Mechanical Engineering, 糖心Vlog破解版
cary.faulkner@colorado.edu

Aisling Pigott 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
Aisling.Pigott@colorado.edu

Saranya Anbarasu, M.S. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
saranya.anbarasu@colorado.edu

Mingzhe Liu, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
mingzhe.liu@colorado.edu

Chengnan Shi, M.S. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
chengnan.shi@colorado.edu

Rensselaer Polytechnic Institute: 

Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute
luigi.vanfretti@gmail.com

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:

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:

Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory
mwetter@lbl.gov

Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory
jianjunhu@lbl.gov

National Renewable Energy Laboratory:

National Renewable Energy Laboratory
Kyle.Benne@nrel.gov

Commercial Buildings Research Group, National Renewable Energy Laboratory
nicholas.long@nrel.gov

National Renewable Energy Laboratory
Amy.Allen@nrel.gov

National Renewable Energy Laboratory
Lauren.Klun@nrel.gov

Amzur technologies:

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. "," Energy, 254(4), pp. 124227.

K. Hinkelman, J. Wang, W. Zuo, A. Gautier, M. Wetter, C. Fan, N. Long. 2022. "" Applied Energy, 311, pp.118654.

Conference Proceedings

F. Fachini, M. d. Castro, M. Liu, T. Bogodorova, L. Vanfretti, W. Zuo. 2022. 鈥溾��, 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. "" 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. 鈥溾�� 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. 鈥�Dymola-Enabled Reinforcement Learning for Real-time Generator Set-point Optimization.鈥� Proceeding of the 13th Conference on Innovative Smart Grid Technologies (ISGT 2022). February 21-24, Washington, D.C., USA.

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Sponsored by Defense Threat Reduction Agency

This five-year project aims to model the transport of harmful biological and chemical compounds in urban environment using different modeling techniques, such as computational fluid dynamics and multizone modeling for indoor airflow, Modelica-based modeling for HVAC system and control. The project is led by Lawrence Berkeley National Laboratory and in collaboration with many federal research laboratories and industry partners. In response to the COVID pandemic, our team has investigated various mitigation strategies, including 1) placement of portable air cleaners in a conference room; 2) HVAC operation strategies for office buildings during COVID and their energy consumptions. 

Comparison of the streamlines, colored by the local velocity magnitude, coming from the portable air cleaner (PAC) inlet in (a) the fully occupied (F) and (b) the socially distanced (D) room setups for the PAC setting 1BL. (Castellini et al. 2021)

Project Team

Wangda Zuo, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
wangda.zuo@colorado.edu

Jake Castellini, M.S.
Department of Mechanical Engineering, 糖心Vlog破解版
jaca6283@colorado.edu

Cary Faulkner 
Department of Mechanical Engineering, 糖心Vlog破解版
cary.faulkner@colorado.edu

Publications

Journal Articles

• C. A. Faulkner, J. E. Castellini, W. Zuo, D. M. Lorenzetti, M. D. Sohn 2022. 鈥溾�� Building and Environment, 207 (B), pp. 108519.  
• J. E. Castellini, C. A. Faulkner, W. Zuo, D. M. Lorenzetti, M. D. Sohn 2022. 鈥溾�� Building and Environment, 207 (B), pp. 108441.

Conference Proceedings

• C. A. Faulkner, J. E. Castellini Jr., W. Zuo, D. M. Lorenzetti, M. D. Sohn 2021. "" Proceedings of the 12th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2021), Seoul, South Korea (Virtual Conference), November 24-26, 2021.
• C. A. Faulkner, D. S. Jankowski, W. Zuo, P. Epple, M. D. Sohn 2021. "" Proceedings of the 12th International Symposium on Heating, Ventilation and Air Conditioning (ISHVAC 2021), Seoul, South Korea (Virtual Conference), November 24-26, 2021.

Presentations

• C. A. Faulkner 2021 "", ISHVAC 2021 Conference, November.
• C. A. Faulkner 2021 "", ISHVAC 2021 Conference, November.

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Sponsored by National Science Foundation

This project is sponsored by the and is in collaboration with the . 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

糖心Vlog破解版

Wangda Zuo, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
wangda.zuo@colorado.edu
 

John Zhai, Ph.D. 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
john.zhai@colorado.edu
 

Katy Hinkelman, M.S., EIT 
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
kathryn.hinkelman@colorado.edu
 

Yizhi Yang
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
yizhi.yang@colorado.edu
 

Yingli Lou
Department of Civil, Environmental and Architectural Engineering, 糖心Vlog破解版
yingli.lou@colorado.edu
 

Chris Payne
Fairview High School
ninjakiwi1224@gmail.com
 

Virginia Polytechnic Institute and State University

 
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

 
Department of Nuclear Engineering and Engineering Physics, Universitas Gadjah Mada, Indonesia
 
rachmawan@ugm.ac.id

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

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

Institut Teknologi Bandung

 
Department of Architecture, Institut Teknologi Bandung, Indonesia
donny@ar.itb.ac.id
 

 
Department of Architecture, Institut Teknologi Bandung, Indonesia
lilyrosalina@yahoo.com
 

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

Department of Architecture, Universitas Hasanuddin, Indonesia
edosyarif@yahoo.com
 

Press Release

Project Updates

• 11/23/2021: The Smart Garden Alley project received additional financial support from Bank of Indonesia.

Publication

• Z. Mahrez, E. Sabir, E. Badidi, W Saad, M Sadik 2021. "" IEEE transactions on intelligent transportation systems.

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

CU East District Energy Plant

Collaborators: 

Journal Publications

K. Hinkelman, J. Wang, W. Zuo, A. Gautier, M. Wetter, C. Fan, N. Long. 2022. "" Applied Energy, 311, pp.118654.

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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鈥檚 service area to enable advanced grid modeling research (AGMR) integration with utility business systems. This will be achieved by making use of DOE鈥檚 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鈥檚 utility district.

Collaborator:

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In support of DOE鈥檚 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

Publications

Conference Proceedings

1. Y. Lou, Y. Ye, W. Zuo, J. Zhang 2021. "." Proceeding of the 17th Conference of International Building Performance Simulation Association (Building Simulation 2021), September 1-3, Bruges, Belgium.

Presentation

• Y. Lou 2021 "", Building Simulation 2021 Conference, September.

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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. 鈥溾��. Sustainable Cities and Society, 75, pp. 103255.
• J. Wang, S. Huang, W. Zuo, D. Vrabie 2021. 鈥�.鈥� Energy and Buildings, 252, pp. 111399.
• J. Wang, K. Garifi, K. Baker, W. Zuo, Y. Zhang, S. Huang, D. Vrabie 2020. "" Energies, 13, pp. 5683.

Conference Proceedings

• J. Wang, W. Zuo, S. Huang, D. Vrabie 2020. 鈥溾��&苍产蝉辫;American Modelica Conference 2020, Virtual Conference, September 22-24.
• Y. Fu, S. Huang, Y. Liu, T. McDermott, D. Vrabie, W. Zuo 2019. 鈥溾�� 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. 鈥�.鈥�&苍产蝉辫;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鈥�.

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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: , ,

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A water-side economizer (WSE) is a cooling system by which the chilled water is cooled by the cooling tower directly/indirectly without the use of mechanical cooling. Employing WSEs can decrease the building energy consumption by reducing the chiller operating time or increasing the chiller efficiency. WSEs, however, may pose challenges to the operation of chiller plants. For example, using WSE may result in chiller short cycling and temporary loss of chilled water supply temperature control. Moreover, having cold condenser water may cause the chillers trip on low head pressure, i.e., a lower pressure difference between the condenser and the evaporator. The above challenges can be addressed by adopting certain control sequences and there have been several control sequences successfully demonstrated in real-world applications. However, they are not intensively evaluated against all plant configurations, under all possible weather conditions. It is necessary to consider the effects for all plant configurations and all weather conditions when developing and evaluating a near-optimal WSE control sequence for large-scale applications.

Therefore, the objectives of the proposed research is to:

• evaluate state-of-art control sequences for water side economizer (WSE) and develop a near-optimal sequence based on the comparison;
• develop open-source dynamic models for controls evaluation of the chilled water plants with WSEs;
• demonstrate the value of using a multidisciplinary modeling and analysis environment for integrating and sharing research among different TCs.

To achieve the above objectives, researchers in our lab will

• conduct a comprehensive review on the state-of-the-art control sequences for WSEs. 
• develop Dynamic Models for Different Configurations of Chiller Plants with WSEs. 
• evaluate Strategies for WSE Sequencing. 
• develop a Near-Optimal Control Sequence for WSEs. 

Publications

• C. Fan, K. Hinkelman, Y. Fu, W. Zuo, S. Huang, C. Shi, N. Mamaghani, C. Faulkner, X. Zhou 2021. "Open-source Modelica Models for the Control Performance Simulation of Chiller Plants with Water-side Economizer." Applied Energy. 299, pp. 117337.
• Y. Fu, X. Lu, W. Zuo 2019. 鈥�Modelica Models for the Control Evaluations of Chilled Water System with Waterside Economizer.鈥�&苍产蝉辫;Proceedings of the 13th International Modelica Conference, pp. 811-818, March 4-6, Regensburg, Germany. 

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