Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters

Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the stud...
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Autor*in:	Siyi Chen [verfasserIn] Zhijin Zhang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 13(2020), 12, p 3066
Übergeordnetes Werk:	volume:13 ; year:2020 ; number:12, p 3066

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en13123066

Katalog-ID:	DOAJ085336890

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520			\|a Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD.
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allfields	10.3390/en13123066 doi (DE-627)DOAJ085336890 (DE-599)DOAJ8f22ffe6db4b455c9f16b133de65be05 DE-627 ger DE-627 rakwb eng Siyi Chen verfasserin aut Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD. dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method Technology T Zhijin Zhang verfasserin aut In Energies MDPI AG, 2008 13(2020), 12, p 3066 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:13 year:2020 number:12, p 3066 https://doi.org/10.3390/en13123066 kostenfrei https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 kostenfrei https://www.mdpi.com/1996-1073/13/12/3066 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 12, p 3066
spelling	10.3390/en13123066 doi (DE-627)DOAJ085336890 (DE-599)DOAJ8f22ffe6db4b455c9f16b133de65be05 DE-627 ger DE-627 rakwb eng Siyi Chen verfasserin aut Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD. dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method Technology T Zhijin Zhang verfasserin aut In Energies MDPI AG, 2008 13(2020), 12, p 3066 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:13 year:2020 number:12, p 3066 https://doi.org/10.3390/en13123066 kostenfrei https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 kostenfrei https://www.mdpi.com/1996-1073/13/12/3066 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 12, p 3066
allfields_unstemmed	10.3390/en13123066 doi (DE-627)DOAJ085336890 (DE-599)DOAJ8f22ffe6db4b455c9f16b133de65be05 DE-627 ger DE-627 rakwb eng Siyi Chen verfasserin aut Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD. dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method Technology T Zhijin Zhang verfasserin aut In Energies MDPI AG, 2008 13(2020), 12, p 3066 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:13 year:2020 number:12, p 3066 https://doi.org/10.3390/en13123066 kostenfrei https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 kostenfrei https://www.mdpi.com/1996-1073/13/12/3066 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 12, p 3066
allfieldsGer	10.3390/en13123066 doi (DE-627)DOAJ085336890 (DE-599)DOAJ8f22ffe6db4b455c9f16b133de65be05 DE-627 ger DE-627 rakwb eng Siyi Chen verfasserin aut Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD. dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method Technology T Zhijin Zhang verfasserin aut In Energies MDPI AG, 2008 13(2020), 12, p 3066 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:13 year:2020 number:12, p 3066 https://doi.org/10.3390/en13123066 kostenfrei https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 kostenfrei https://www.mdpi.com/1996-1073/13/12/3066 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 12, p 3066
allfieldsSound	10.3390/en13123066 doi (DE-627)DOAJ085336890 (DE-599)DOAJ8f22ffe6db4b455c9f16b133de65be05 DE-627 ger DE-627 rakwb eng Siyi Chen verfasserin aut Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD. dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method Technology T Zhijin Zhang verfasserin aut In Energies MDPI AG, 2008 13(2020), 12, p 3066 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:13 year:2020 number:12, p 3066 https://doi.org/10.3390/en13123066 kostenfrei https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 kostenfrei https://www.mdpi.com/1996-1073/13/12/3066 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 13 2020 12, p 3066
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author	Siyi Chen
spellingShingle	Siyi Chen misc dynamic pollution model misc reference insulators misc insulator structure coefficient misc natural pollution tests misc finite element method misc Technology misc T Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters
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topic_title	Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters dynamic pollution model reference insulators insulator structure coefficient natural pollution tests finite element method
topic	misc dynamic pollution model misc reference insulators misc insulator structure coefficient misc natural pollution tests misc finite element method misc Technology misc T
topic_unstemmed	misc dynamic pollution model misc reference insulators misc insulator structure coefficient misc natural pollution tests misc finite element method misc Technology misc T
topic_browse	misc dynamic pollution model misc reference insulators misc insulator structure coefficient misc natural pollution tests misc finite element method misc Technology misc T
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title	Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters
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title_full	Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters
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title_sort	dynamic pollution prediction model of insulators based on atmospheric environmental parameters
title_auth	Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters
abstract	Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD.
abstractGer	Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD.
abstract_unstemmed	Pollution-induced flashover is one of the most serious power accidents, and the pollution degree of insulators depends on atmospheric environmental parameters. The pollution models used in the power system research are usually static, but the environmental parameters are dynamic. Therefore, the study on the dynamic pollution prediction model is of great importance. In this paper, the dynamic pollution prediction model of insulators based on atmospheric environmental parameters was built, and insulators’ structure coefficients were proposed based on the model. Firstly, the insulator dynamic pollution model based on meteorological data (PM2.5, PM10, TSP (total suspended particulate), and wind speed) was proposed, and natural pollution tests were also conducted as verification tests. Furthermore, insulator structure coefficients <i<c</i<1, <i<c</i<2 (<i<c</i<1: pollution ratio of U210BP/170 to XP-160; <i<c</i<2: calculated pollution ratio of U210BP/170T to XP-160) were then obtained, and their influence factors were discussed. At last, insulator structure coefficients were calculated, and it can be seen that the calculated error of insulator structure coefficients was acceptable, with the average <i<re</i< (relative errors) at 9.0% (<i<c</i<1) and 13.5% (<i<c</i<2), which verifies the feasibility of the model. Based on the results in this paper, the NSDD (non-soluble deposit density) of insulators with different structures can be obtained using the insulators’ structure coefficient and the reference XP-160 insulator’s NSDD.
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title_short	Dynamic Pollution Prediction Model of Insulators Based on Atmospheric Environmental Parameters
url	https://doi.org/10.3390/en13123066 https://doaj.org/article/8f22ffe6db4b455c9f16b133de65be05 https://www.mdpi.com/1996-1073/13/12/3066 https://doaj.org/toc/1996-1073
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