Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example (2024)

Schoonenberg, W. C. H. (2022). Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example. Sustainable Energy, Grids and Networks, 31, Article 100749. https://doi.org/10.1016/j.segan.2022.100749

Schoonenberg, Wester C.H. ; Farid, Amro M. / Hetero-functional network minimum cost flow optimization : A hydrogen–natural gas network example. In: Sustainable Energy, Grids and Networks. 2022 ; Vol. 31.

@article{dc9465e86f3e48b19a8654e80a69c4e3,

title = "Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example",

abstract = "Sustainable energy grids and networks are converging. In recent decades, cost, sustainability, and digitization drivers have caused engineering systems to evolve into systems-of-systems that deliver multiple services across multiple application domains. These engineering systems include electrified-transportation systems, the energy–water nexus, and multi-modal energy systems. The rather complex and heterogeneous interdependencies between engineering system services necessitates a precise informatic representation that ultimately supports optimized management of the holistic dynamics and tradeoffs. Consequently, ontologically-robust, quantitative modeling tools are needed to represent the heterogeneity of the modeled system-of-systems while still remaining generic and extensible to a diversity of application domains. Hetero-functional graph theory has demonstrated itself as a such modeling tool. This work now builds upon this foundation to develop a dynamic hetero-functional network minimum cost flow optimization that meets the requirements of these emerging systems-of-systems. It optimizes the supply, demand, transportation, storage, transformation, assembly, and disassembly of multiple operands in distinct locations over time in a systems-of-systems of arbitrary number, function, and topology. First, the paper introduces a general approach to define a dynamic system-of-system model that integrates customizable dynamic device models into a hetero-functional graph theory structural model. To this end, the work leverages Petri net dynamics and the hetero-functional incidence tensor. The Petri net based models are then translated into a quadratic program in canonical form. The hetero-functional network minimum cost flow optimization is demonstrated on a hydrogen–natural gas infrastructure test case. Four distinct scenarios are studied to demonstrate potential synergies and cascading network effects of policy across multiple infrastructures.",

keywords = "Colored Petri nets, Energy systems, Hetero-functional graph Theory, Hetero-functional network cost flow, Hydrogen economy, Multi-energy systems, Natural gas system, Petri nets",

author = "Schoonenberg, {Wester C.H.} and Farid, {Amro M.}",

note = "Publisher Copyright: {\textcopyright} 2022",

year = "2022",

month = sep,

doi = "10.1016/j.segan.2022.100749",

language = "English",

volume = "31",

}

Schoonenberg, WCH 2022, 'Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example', Sustainable Energy, Grids and Networks, vol. 31, 100749. https://doi.org/10.1016/j.segan.2022.100749

Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example. / Schoonenberg, Wester C.H.; Farid, Amro M.
In: Sustainable Energy, Grids and Networks, Vol. 31, 100749, 09.2022.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Hetero-functional network minimum cost flow optimization

T2 - A hydrogen–natural gas network example

AU - Schoonenberg, Wester C.H.

AU - Farid, Amro M.

N1 - Publisher Copyright:© 2022

PY - 2022/9

Y1 - 2022/9

N2 - Sustainable energy grids and networks are converging. In recent decades, cost, sustainability, and digitization drivers have caused engineering systems to evolve into systems-of-systems that deliver multiple services across multiple application domains. These engineering systems include electrified-transportation systems, the energy–water nexus, and multi-modal energy systems. The rather complex and heterogeneous interdependencies between engineering system services necessitates a precise informatic representation that ultimately supports optimized management of the holistic dynamics and tradeoffs. Consequently, ontologically-robust, quantitative modeling tools are needed to represent the heterogeneity of the modeled system-of-systems while still remaining generic and extensible to a diversity of application domains. Hetero-functional graph theory has demonstrated itself as a such modeling tool. This work now builds upon this foundation to develop a dynamic hetero-functional network minimum cost flow optimization that meets the requirements of these emerging systems-of-systems. It optimizes the supply, demand, transportation, storage, transformation, assembly, and disassembly of multiple operands in distinct locations over time in a systems-of-systems of arbitrary number, function, and topology. First, the paper introduces a general approach to define a dynamic system-of-system model that integrates customizable dynamic device models into a hetero-functional graph theory structural model. To this end, the work leverages Petri net dynamics and the hetero-functional incidence tensor. The Petri net based models are then translated into a quadratic program in canonical form. The hetero-functional network minimum cost flow optimization is demonstrated on a hydrogen–natural gas infrastructure test case. Four distinct scenarios are studied to demonstrate potential synergies and cascading network effects of policy across multiple infrastructures.

AB - Sustainable energy grids and networks are converging. In recent decades, cost, sustainability, and digitization drivers have caused engineering systems to evolve into systems-of-systems that deliver multiple services across multiple application domains. These engineering systems include electrified-transportation systems, the energy–water nexus, and multi-modal energy systems. The rather complex and heterogeneous interdependencies between engineering system services necessitates a precise informatic representation that ultimately supports optimized management of the holistic dynamics and tradeoffs. Consequently, ontologically-robust, quantitative modeling tools are needed to represent the heterogeneity of the modeled system-of-systems while still remaining generic and extensible to a diversity of application domains. Hetero-functional graph theory has demonstrated itself as a such modeling tool. This work now builds upon this foundation to develop a dynamic hetero-functional network minimum cost flow optimization that meets the requirements of these emerging systems-of-systems. It optimizes the supply, demand, transportation, storage, transformation, assembly, and disassembly of multiple operands in distinct locations over time in a systems-of-systems of arbitrary number, function, and topology. First, the paper introduces a general approach to define a dynamic system-of-system model that integrates customizable dynamic device models into a hetero-functional graph theory structural model. To this end, the work leverages Petri net dynamics and the hetero-functional incidence tensor. The Petri net based models are then translated into a quadratic program in canonical form. The hetero-functional network minimum cost flow optimization is demonstrated on a hydrogen–natural gas infrastructure test case. Four distinct scenarios are studied to demonstrate potential synergies and cascading network effects of policy across multiple infrastructures.

KW - Colored Petri nets

KW - Energy systems

KW - Hetero-functional graph Theory

KW - Hetero-functional network cost flow

KW - Hydrogen economy

KW - Multi-energy systems

KW - Natural gas system

KW - Petri nets

UR - http://www.scopus.com/inward/record.url?scp=85132411395&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85132411395&partnerID=8YFLogxK

U2 - 10.1016/j.segan.2022.100749

DO - 10.1016/j.segan.2022.100749

M3 - Article

AN - SCOPUS:85132411395

VL - 31

JO - Sustainable Energy, Grids and Networks

JF - Sustainable Energy, Grids and Networks

M1 - 100749

ER -

Schoonenberg WCH, Farid AM. Hetero-functional network minimum cost flow optimization: A hydrogen–natural gas network example. Sustainable Energy, Grids and Networks. 2022 Sep;31:100749. doi: 10.1016/j.segan.2022.100749