A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems

Hall, Joni; Starke, Michael; Munk, Jeffrey; Zandi, Helia; Chinthavali, Supriya; Tansakul, Varisara; Kuruganti, Teja; Buckberry, Heather; Leverette, Jim

doi:10.1109/ISGT49243.2021.9372238

Title: A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems

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Abstract

The prevalence of the loT (Internet of Things) is fostering the development of new control options and decision making that was not previously available. This is creating a wealth of opportunities for real-time control approaches and systems that can optimize for a common goal. This paper presents a smart residential neighborhood with optimization at the residential level utilizing a system of agents. The optimization utilizes information and modeling to optimize variable speed HVAC real-time operation in actual residential buildings. Data is presented showing the performance of the optimization and conclusions are drawn on next steps for development.

Authors:

^[1];

^[1]; Tansakul, Varisara ^[1];

^[1];

^[1]; Leverette, Jim ^[2]

ORNL
Southern Company Services, Inc.

Publication Date:: 2021-03-01

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

OSTI Identifier:: 1782053

DOE Contract Number:: AC05-00OR22725

Resource Type:: Conference

Resource Relation:: Conference: IEEE PES Innovative Smart Grid Technologies Conference (ISGT) - Washington DC, District of Columbia, United States of America - 2/15/2021 3:00:00 PM-2/18/2021 3:00:00 PM

Country of Publication:: United States

Language:: English

Citation Formats


                    Hall, Joni, Starke, Michael, Munk, Jeffrey, Zandi, Helia, Chinthavali, Supriya, Tansakul, Varisara, Kuruganti, Teja, Buckberry, Heather, and Leverette, Jim. A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems.  United States: N. p., 2021. 
        Web.  doi:10.1109/ISGT49243.2021.9372238.

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                    Hall, Joni, Starke, Michael, Munk, Jeffrey, Zandi, Helia, Chinthavali, Supriya, Tansakul, Varisara, Kuruganti, Teja, Buckberry, Heather, & Leverette, Jim. A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems.  United States.  https://doi.org/10.1109/ISGT49243.2021.9372238

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                    Hall, Joni, Starke, Michael, Munk, Jeffrey, Zandi, Helia, Chinthavali, Supriya, Tansakul, Varisara, Kuruganti, Teja, Buckberry, Heather, and Leverette, Jim. 2021.  
        "A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems".  United States.  https://doi.org/10.1109/ISGT49243.2021.9372238.  https://www.osti.gov/servlets/purl/1782053.

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@article{osti_1782053,

  title        = {A Real-time Agent Based Optimization and Control Approach for Residential Building Heating Ventilation and Air Conditioning Systems},

  author       = {Hall, Joni and Starke, Michael and Munk, Jeffrey and Zandi, Helia and Chinthavali, Supriya and Tansakul, Varisara and Kuruganti, Teja and Buckberry, Heather and Leverette, Jim},

  abstractNote = {The prevalence of the loT (Internet of Things) is fostering the development of new control options and decision making that was not previously available. This is creating a wealth of opportunities for real-time control approaches and systems that can optimize for a common goal. This paper presents a smart residential neighborhood with optimization at the residential level utilizing a system of agents. The optimization utilizes information and modeling to optimize variable speed HVAC real-time operation in actual residential buildings. Data is presented showing the performance of the optimization and conclusions are drawn on next steps for development.},

  doi          = {10.1109/ISGT49243.2021.9372238},

  url          = {https://www.osti.gov/biblio/1782053},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2021},

  month        = {3}

}

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