Dynamical Graph-Based Models of Brayton Cycle Systems

Reid D. Smith, Andrew G. Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

For many power systems, thermodynamic cycle systems are used as subsystems for energy injection or removal. For model-based control of large, interconnected systems, model fidelity and computational efficiency must be balanced. Graph-based models have proven success at accurately modeling multiple energy domains in a computationally efficient manner. This paper presents a graph-based modeling approach governed by energy conservation to produce a general graph framework for thermodynamic cycles with mass transport. To investigate model performance, case studies on a reverse Brayton cycle and open Brayton cycle system are considered. The graph-based model of these systems produces comparable model accuracy to alternative dynamic modeling techniques while providing the modularity, scalability, and computational efficiency of graph-based models. A 98% reduction in computational time is achieved by the graph-based modeling approach.

Original languageEnglish (US)
Title of host publication2022 American Control Conference, ACC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4802-4807
Number of pages6
ISBN (Electronic)9781665451963
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: Jun 8 2022Jun 10 2022

Publication series

Name2022 American Control Conference (ACC)

Conference

Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States
CityAtlanta
Period6/8/226/10/22

Bibliographical note

Funding Information:
*Research supported by the National Science Foundation Engineering Research Center for Power Optimization of Electro Thermal Systems (POETS) with cooperative agreement EEC-1449548.

Publisher Copyright:
© 2022 American Automatic Control Council.

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