Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI

Lee, Jessica; McMillen, Adam

doi:10.15121/2448525

Title: Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI

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Abstract

This data includes results on an analysis of existing and projected energy, cost, and carbon for the City of Ann Arbor - District Geothermal Design and Deployment to Equitably Decarbonize Low Income Neighborhoods in Ann Arbor project. The scope of the project includes designing and implementing a geothermal district heating and cooling system that reduces thermal heating and cooling load by 75% and greenhouse gas emissions by 40% in the project area (262 households, 6 commercial buildings). The existing neighborhood was modeled using Design Builder, an EnergyPlus software, to understand the current energy load. The energy model was then flipped to reflect the designed district geothermal heating and cooling system to project the effect on energy, carbon, and cost. This dataset includes the analysis files utilized and created for this study. There are 3 categories of data: 1) existing/benchmarking, 2) energy modeling, and 3) post processed calculations. This follows the methodology and process of the project team, which is fully explained in file 00_Technical Economic Environmental Assessment. All uses of data are referenced throughout this assessment to their respective files included below.

Authors:

Lee, Jessica; McMillen, Adam

IMEG Corp

Publication Date:: Sun Dec 31 23:00:00 EST 2023

Other Number(s):: 1594

DOE Contract Number:: EE0010665

Research Org.:: DOE Geothermal Data Repository; IMEG Corp

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)

Collaborations:: IMEG Corp

Subject:: 15 GEOTHERMAL ENERGY; Ann Arbor; Design Builder; Energy Plus; Michigan; ResStock; assessment; benchmarking; building modeling; carbon; commGeo; community geothermal; cost; development; district geothermal; economic; energy; energy audit; energy load; energy model; environmental; geothermal; heating and cooling; load timeseries; model; processed data

OSTI Identifier:: 2448525

DOI:: https://doi.org/10.15121/2448525

Citation Formats


                    Lee, Jessica, and McMillen, Adam. Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI.  United States: N. p., 2023. 
        Web.  doi:10.15121/2448525.

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                    Lee, Jessica, & McMillen, Adam. Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI.  United States.  doi:https://doi.org/10.15121/2448525

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                    Lee, Jessica, and McMillen, Adam. 2023.  
"Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI".  United States.  doi:https://doi.org/10.15121/2448525.  https://www.osti.gov/servlets/purl/2448525. Pub date:Sun Dec 31 23:00:00 EST 2023

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@article{osti_2448525,

  title        = {Community Geothermal: Energy, Cost, and Carbon Modeling for District Design - Ann Arbor, MI},

  author       = {Lee, Jessica and McMillen, Adam},

  abstractNote = {This data includes results on an analysis of existing and projected energy, cost, and carbon for the City of Ann Arbor - District Geothermal Design and Deployment to Equitably Decarbonize Low Income Neighborhoods in Ann Arbor project. The scope of the project includes designing and implementing a geothermal district heating and cooling system that reduces thermal heating and cooling load by 75% and greenhouse gas emissions by 40% in the project area (262 households, 6 commercial buildings). The existing neighborhood was modeled using Design Builder, an EnergyPlus software, to understand the current energy load. The energy model was then flipped to reflect the designed district geothermal heating and cooling system to project the effect on energy, carbon, and cost. This dataset includes the analysis files utilized and created for this study. There are 3 categories of data: 1) existing/benchmarking, 2) energy modeling, and 3) post processed calculations. This follows the methodology and process of the project team, which is fully explained in file 00_Technical Economic Environmental Assessment. All uses of data are referenced throughout this assessment to their respective files included below.},

  doi          = {10.15121/2448525},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Dec 31 23:00:00 EST 2023},

  month        = {Sun Dec 31 23:00:00 EST 2023}

}

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DOI: https://doi.org/10.15121/2448525

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