Internal thermal state estimation of outdoor installed GIS by reduced order modeling and particle swarm optimization

Internal thermal state estimation of outdoor installed GIS by reduced order modeling and particle swarm optimization | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 December 2025 V1 Latest version Share on Internal thermal state estimation of outdoor installed GIS by reduced order modeling and particle swarm optimization Authors : xiangyu guan [email protected] , chaoqun xu 0009-0002-9789-8349 , xiaokun chen , and xinling xu Authors Info & Affiliations https://doi.org/10.22541/au.176645730.06118831/v1 138 views 66 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract To realize instantaneous thermal state estimation of outdoor-installed gas insulated switchgear (GIS), this work establishes a thermal-fluid coupled reduced-order model (ROM) integrated with Particle Swarm Optimization (PSO). Design of Experiments (DOEs) including operating current, contact resistance, ambient temperature, solar radiation, and wind speed/direction are conducted via Latin Hypercube Sampling (LHS) to generate snapshots for full-order thermal-fluid finite element analysis (FEA). The Proper Orthogonal Decomposition (POD) method determines the optimal reduced-order number, while Response Surface Methodology (RSM) establishes the input- coefficient correlation. Finally, a PSO algorithm integrated with ROM forward simulations achieves inversion of internal contact resistance and temperature from outer tank measurements. Results show the 16-order ROM completes thermal-fluid simulations in under 2.7 seconds (over 3140 times faster than full-order) with acceptable errors (2.51% connector, 0.8% tank) versus experiments. Internal contact resistance and temperature are inverted within 10 minutes, with errors below 2.15% and 1.311% respectively. This work provides a promising approach for instantaneous thermal field reconstruction and demonstrates potential for digital twins (DT) in outdoor GIS. Supplementary Material File (figure.docx) Download 4.67 MB File (internal thermal state estimation of outdoor installed gis by reduced order modeling and particle swarm optimization.docx) Download 4.59 MB File (table.docx) Download 21.48 KB Information & Authors Information Version history V1 Version 1 23 December 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords finite element analysis gas insulated switchgear thermal analysis Authors Affiliations xiangyu guan [email protected] Fuzhou University Department of Electrical Engineering View all articles by this author chaoqun xu 0009-0002-9789-8349 Fuzhou University View all articles by this author xiaokun chen Fuzhou University Department of Electrical Engineering View all articles by this author xinling xu Fuzhou University Department of Electrical Engineering View all articles by this author Metrics & Citations Metrics Article Usage 138 views 66 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation xiangyu guan, chaoqun xu, xiaokun chen, et al. Internal thermal state estimation of outdoor installed GIS by reduced order modeling and particle swarm optimization. Authorea . 23 December 2025. 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