TY - JOUR
T1 - A hetero-functional graph structural analysis of the American Multi-Modal Energy System
AU - Thompson, Dakota J.
AU - Farid, Amro M.
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/6
Y1 - 2024/6
N2 - As one of the most pressing challenges of the 21st century, global climate change demands a host of changes across four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system. Unfortunately, these four systems are often studied individually, and rarely together as integrated systems. Instead, holistic multi-energy system models can serve to improve the understanding of these interdependent systems and guide policies that shape the systems as they evolve into the future. The NSF project entitled “American Multi-Modal Energy System Synthetic & Simulated Data (AMES-3D)” seeks to fill this void with an open-source, physically-informed, structural, and behavioral machine-learning model of the AMES. To that end, this paper uses a GIS-data-driven, model-based system engineering approach to develop structural models of the American Multi-Modal Energy System (AMES). This paper produces and reports the hetero-functional incidence tensor, hetero-functional adjacency matrix, and the formal graph adjacency matrix in terms of their statistics. This work compares these four hetero-functional graph models across the states of New York (NY), California (CA), Texas (TX), and the United States of America (USA) as a whole. From the reported statistics, the paper finds that the geography and the sustainable energy policies of these states are deeply reflected in the structure of their multi-energy infrastructure systems and impact the full USA structure.
AB - As one of the most pressing challenges of the 21st century, global climate change demands a host of changes across four critical energy infrastructures: the electric grid, the natural gas system, the oil system, and the coal system. Unfortunately, these four systems are often studied individually, and rarely together as integrated systems. Instead, holistic multi-energy system models can serve to improve the understanding of these interdependent systems and guide policies that shape the systems as they evolve into the future. The NSF project entitled “American Multi-Modal Energy System Synthetic & Simulated Data (AMES-3D)” seeks to fill this void with an open-source, physically-informed, structural, and behavioral machine-learning model of the AMES. To that end, this paper uses a GIS-data-driven, model-based system engineering approach to develop structural models of the American Multi-Modal Energy System (AMES). This paper produces and reports the hetero-functional incidence tensor, hetero-functional adjacency matrix, and the formal graph adjacency matrix in terms of their statistics. This work compares these four hetero-functional graph models across the states of New York (NY), California (CA), Texas (TX), and the United States of America (USA) as a whole. From the reported statistics, the paper finds that the geography and the sustainable energy policies of these states are deeply reflected in the structure of their multi-energy infrastructure systems and impact the full USA structure.
KW - American multi-modal energy system
KW - Hetero-functional graph theory
KW - Model based systems engineering
KW - Sustainability
KW - Sustainable energy transition
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U2 - 10.1016/j.segan.2023.101254
DO - 10.1016/j.segan.2023.101254
M3 - Article
AN - SCOPUS:85185284666
VL - 38
JO - Sustainable Energy, Grids and Networks
JF - Sustainable Energy, Grids and Networks
M1 - 101254
ER -