Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment

Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption...
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Autor*in:	Zhang Jieliang [verfasserIn] Jiang Libin [verfasserIn] Zhang Huanghui [verfasserIn] Zhao Sikan [verfasserIn] Yong Lin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	artificial intelligence intelligent sensor ees internet of things

Übergeordnetes Werk:	In: High Temperature Materials and Processes - De Gruyter, 2020, 42(2023), 1, Seite pp. 136-138
Übergeordnetes Werk:	volume:42 ; year:2023 ; number:1 ; pages:pp. 136-138

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1515/htmp-2022-0300

Katalog-ID:	DOAJ098128256

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520			\|a Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES.
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spelling	10.1515/htmp-2022-0300 doi (DE-627)DOAJ098128256 (DE-599)DOAJ0a0cabd704e5417bbd5eb472b1525f6f DE-627 ger DE-627 rakwb eng TP1-1185 TP200-248 Zhang Jieliang verfasserin aut Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES. artificial intelligence intelligent sensor ees internet of things Technology T Chemical technology Chemicals: Manufacture, use, etc. Jiang Libin verfasserin aut Zhang Huanghui verfasserin aut Zhao Sikan verfasserin aut Yong Lin verfasserin aut In High Temperature Materials and Processes De Gruyter, 2020 42(2023), 1, Seite pp. 136-138 (DE-627)656019751 (DE-600)2602423-8 21910324 nnns volume:42 year:2023 number:1 pages:pp. 136-138 https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/article/0a0cabd704e5417bbd5eb472b1525f6f kostenfrei https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/toc/2191-0324 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4277 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 42 2023 1 pp. 136-138
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allfieldsGer	10.1515/htmp-2022-0300 doi (DE-627)DOAJ098128256 (DE-599)DOAJ0a0cabd704e5417bbd5eb472b1525f6f DE-627 ger DE-627 rakwb eng TP1-1185 TP200-248 Zhang Jieliang verfasserin aut Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES. artificial intelligence intelligent sensor ees internet of things Technology T Chemical technology Chemicals: Manufacture, use, etc. Jiang Libin verfasserin aut Zhang Huanghui verfasserin aut Zhao Sikan verfasserin aut Yong Lin verfasserin aut In High Temperature Materials and Processes De Gruyter, 2020 42(2023), 1, Seite pp. 136-138 (DE-627)656019751 (DE-600)2602423-8 21910324 nnns volume:42 year:2023 number:1 pages:pp. 136-138 https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/article/0a0cabd704e5417bbd5eb472b1525f6f kostenfrei https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/toc/2191-0324 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4277 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 42 2023 1 pp. 136-138
allfieldsSound	10.1515/htmp-2022-0300 doi (DE-627)DOAJ098128256 (DE-599)DOAJ0a0cabd704e5417bbd5eb472b1525f6f DE-627 ger DE-627 rakwb eng TP1-1185 TP200-248 Zhang Jieliang verfasserin aut Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES. artificial intelligence intelligent sensor ees internet of things Technology T Chemical technology Chemicals: Manufacture, use, etc. Jiang Libin verfasserin aut Zhang Huanghui verfasserin aut Zhao Sikan verfasserin aut Yong Lin verfasserin aut In High Temperature Materials and Processes De Gruyter, 2020 42(2023), 1, Seite pp. 136-138 (DE-627)656019751 (DE-600)2602423-8 21910324 nnns volume:42 year:2023 number:1 pages:pp. 136-138 https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/article/0a0cabd704e5417bbd5eb472b1525f6f kostenfrei https://doi.org/10.1515/htmp-2022-0300 kostenfrei https://doaj.org/toc/2191-0324 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4277 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 42 2023 1 pp. 136-138
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source	In High Temperature Materials and Processes 42(2023), 1, Seite pp. 136-138 volume:42 year:2023 number:1 pages:pp. 136-138
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title_auth	Research on electric energy measurement system based on intelligent sensor data in artificial intelligence environment
abstract	Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES.
abstractGer	Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES.
abstract_unstemmed	Electric power resources are the core energy for a country’s economic development and growth. China is at the peak of electric energy consumption at this stage. Improving the accuracy and integrity of electric energy metering technology is of great significance for evaluating the use and consumption of resources in China. Under the background of artificial intelligence, this research analyzes and studies the integrated module, demand status, performance optimization, and coupling degree of the electric energy metering system (hereinafter referred to as EES) through the application of two different types of sensors. The results show that the application of intelligent sensors has a better integration effect with the system management of electric energy metering, which plays a very important role in promoting the sustainable development of automation and informatization of the EES.
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