Research on a prediction model for gas insulation performance based on Pareto optimisation

Abstract Predicting the insulation performance of SF6 substitute gases through gas molecular structures has been a popular topic worldwide. The difficulty is that the relationships between the molecular structure and the gas insulation strength, global warming potential and boiling temperature are n...

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Main Authors: Tianpeng You, Xuzhu Dong, Wenjun Zhou, Yu Zheng, Hongyu Lei, Shubo Ren, Han Li, Hua Hou
Format: Article
Language:English
Published: Wiley 2022-12-01
Series:High Voltage
Online Access:https://doi.org/10.1049/hve2.12235
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author Tianpeng You
Xuzhu Dong
Wenjun Zhou
Yu Zheng
Hongyu Lei
Shubo Ren
Han Li
Hua Hou
author_facet Tianpeng You
Xuzhu Dong
Wenjun Zhou
Yu Zheng
Hongyu Lei
Shubo Ren
Han Li
Hua Hou
author_sort Tianpeng You
collection DOAJ
description Abstract Predicting the insulation performance of SF6 substitute gases through gas molecular structures has been a popular topic worldwide. The difficulty is that the relationships between the molecular structure and the gas insulation strength, global warming potential and boiling temperature are not clear, and general linear methods cannot be used to effectively extract the key factors. Based on published molecular structure parameters, the grey correlation method is used to extract the factors that affect the gas dielectric strength, global warming potential and boiling temperature in a dynamic (non‐linear) approach. Further, to predict the dielectric strength, global warming potential and boiling temperature of gases, a linear regression method and the factors with high correlations are used as independent variables. Through the Pareto optimal solution, the dielectric strength is set as the target, the global warming potential and boiling temperature are set as the constraints, and the ranges of the molecular structure parameters of the SF6 substitute gas are obtained. This research study provides an important reference regarding the SF6 substitute gas analysis and provides a research foundation for the design and synthesis of new environmentally friendly gases used in power equipment.
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spelling doaj.art-848de4d471d940988b663ce6b3500bb72022-12-22T04:42:15ZengWileyHigh Voltage2397-72642022-12-01761080109010.1049/hve2.12235Research on a prediction model for gas insulation performance based on Pareto optimisationTianpeng You0Xuzhu Dong1Wenjun Zhou2Yu Zheng3Hongyu Lei4Shubo Ren5Han Li6Hua Hou7School of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaSchool of Electrical Engineering and Automation Wuhan University Wuhan Hubei ChinaCollege of Chemistry and Molecular Sciences Wuhan University Wuhan Hubei ChinaAbstract Predicting the insulation performance of SF6 substitute gases through gas molecular structures has been a popular topic worldwide. The difficulty is that the relationships between the molecular structure and the gas insulation strength, global warming potential and boiling temperature are not clear, and general linear methods cannot be used to effectively extract the key factors. Based on published molecular structure parameters, the grey correlation method is used to extract the factors that affect the gas dielectric strength, global warming potential and boiling temperature in a dynamic (non‐linear) approach. Further, to predict the dielectric strength, global warming potential and boiling temperature of gases, a linear regression method and the factors with high correlations are used as independent variables. Through the Pareto optimal solution, the dielectric strength is set as the target, the global warming potential and boiling temperature are set as the constraints, and the ranges of the molecular structure parameters of the SF6 substitute gas are obtained. This research study provides an important reference regarding the SF6 substitute gas analysis and provides a research foundation for the design and synthesis of new environmentally friendly gases used in power equipment.https://doi.org/10.1049/hve2.12235
spellingShingle Tianpeng You
Xuzhu Dong
Wenjun Zhou
Yu Zheng
Hongyu Lei
Shubo Ren
Han Li
Hua Hou
Research on a prediction model for gas insulation performance based on Pareto optimisation
High Voltage
title Research on a prediction model for gas insulation performance based on Pareto optimisation
title_full Research on a prediction model for gas insulation performance based on Pareto optimisation
title_fullStr Research on a prediction model for gas insulation performance based on Pareto optimisation
title_full_unstemmed Research on a prediction model for gas insulation performance based on Pareto optimisation
title_short Research on a prediction model for gas insulation performance based on Pareto optimisation
title_sort research on a prediction model for gas insulation performance based on pareto optimisation
url https://doi.org/10.1049/hve2.12235
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