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Systematic approach to construct and assess power electronic conversion architectures using graph theory and its application in a fuel cell system
Author(s) -
Zhang Wenping
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.6143
Subject(s) - construct (python library) , graph theory , computer science , graph , theoretical computer science , computer architecture , distributed computing , mathematics , programming language , combinatorics
With the proliferation of renewable energy generations, power conversion systems (PCSs) are becoming much more complex; it is becoming challenging to search all possible power conversion architectures (PCAs) and find the best optimisation in terms of different objectives. Therefore, this study investigates a systematic approach to construct and evaluate PCAs using graph theory. First, the components in PCSs are graphically modelled as either nodes or edges. Then, a generalised PCA deduction methodology is proposed, and all possible PCAs can be mathematically deduced by modifying elements in adjacency matrices. For a fuel cell (FC) generation system, 45 possible PCAs are found with the proposed method. Furthermore, an evaluation methodology based on graph theory is proposed. The performance indices of the deduced PCAs, including costs, efficiency, and reliability, are calculated. Then, an optimisation approach is applied to finding the best architecture compromise, where the one with the shortest distance to the ideal architecture is considered the best architecture compromise. For the FC demo system, with the proposed assessment methodology, the best architecture compromise (dc‐bus structure) is found among 45 possible architectures. Finally, the experimental platform, which adopts the dc‐bus optimised architecture, is built and experimental results validate the architecture selection.

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