TY - JOUR
T1 - An optimization framework for the network design of advanced district thermal energy systems
AU - Allen, Amy
AU - Henze, Gregor
AU - Baker, Kyri
AU - Pavlak, Gregory
AU - Murphy, Michael
N1 - Funding Information:
This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Building Technologies Office. The views expressed herein do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.
Funding Information:
A portion of the research was performed using computational resources sponsored by the Department of Energy's Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. This work was also supported in part by the USA-Ireland Fulbright Scholarship Award. This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Building Technologies Office. The views expressed herein do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.
Funding Information:
A portion of the research was performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. This work was also supported in part by the USA-Ireland Fulbright Scholarship Award.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/8/15
Y1 - 2022/8/15
N2 - In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, “What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?” A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21–25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.
AB - In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, “What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?” A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21–25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.
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U2 - 10.1016/j.enconman.2022.115839
DO - 10.1016/j.enconman.2022.115839
M3 - Article
AN - SCOPUS:85131921449
SN - 0196-8904
VL - 266
JO - Energy Conversion and Management
JF - Energy Conversion and Management
M1 - 115839
ER -