Low Carbon Operation Mode of Large High Power Consumption Venues Based on Big Data Mining Technology
Abstract Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution, this paper proposes a low-carbon operation mode for large venues with high power consumption based on big data mining technology. The DEA model...
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Published in | Journal of physics. Conference series Vol. 2418; no. 1; pp. 12092 - 12097 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Bristol
IOP Publishing
01.02.2023
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Abstract | Abstract
Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution, this paper proposes a low-carbon operation mode for large venues with high power consumption based on big data mining technology. The DEA model of high-power consumption venues is constructed by linear programming. Then the preliminary indicators of low-carbon operation mode are selected based on big data mining technology. Finally, the selected indicators are used to set up the operation system. Through experimental analysis, it is found that the low-carbon operation mode of large venues with high power consumption can reduce 2 million kg of carbon emissions on the basis of the initial value of carbon emissions. This mode can effectively reduce the carbon emissions of high-power consumption venues and play a great role in curbing environmental pollution and improving the social benefits of venues. |
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AbstractList | Abstract
Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution, this paper proposes a low-carbon operation mode for large venues with high power consumption based on big data mining technology. The DEA model of high-power consumption venues is constructed by linear programming. Then the preliminary indicators of low-carbon operation mode are selected based on big data mining technology. Finally, the selected indicators are used to set up the operation system. Through experimental analysis, it is found that the low-carbon operation mode of large venues with high power consumption can reduce 2 million kg of carbon emissions on the basis of the initial value of carbon emissions. This mode can effectively reduce the carbon emissions of high-power consumption venues and play a great role in curbing environmental pollution and improving the social benefits of venues. Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution, this paper proposes a low-carbon operation mode for large venues with high power consumption based on big data mining technology. The DEA model of high-power consumption venues is constructed by linear programming. Then the preliminary indicators of low-carbon operation mode are selected based on big data mining technology. Finally, the selected indicators are used to set up the operation system. Through experimental analysis, it is found that the low-carbon operation mode of large venues with high power consumption can reduce 2 million kg of carbon emissions on the basis of the initial value of carbon emissions. This mode can effectively reduce the carbon emissions of high-power consumption venues and play a great role in curbing environmental pollution and improving the social benefits of venues. |
Author | Dou, Haoping Xue, Wenbin Zhang, Wenbin Tang, Dehai Zhao, Yueying |
Author_xml | – sequence: 1 givenname: Dehai surname: Tang fullname: Tang, Dehai organization: State Grid Urumqi Electric Power Supply Company , China – sequence: 2 givenname: Yueying surname: Zhao fullname: Zhao, Yueying organization: State Grid Urumqi Electric Power Supply Company , China – sequence: 3 givenname: Wenbin surname: Zhang fullname: Zhang, Wenbin organization: State Grid Urumqi Electric Power Supply Company , China – sequence: 4 givenname: Wenbin surname: Xue fullname: Xue, Wenbin organization: State Grid Urumqi Electric Power Supply Company , China – sequence: 5 givenname: Haoping surname: Dou fullname: Dou, Haoping organization: State Grid Urumqi Electric Power Supply Company , China |
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References | Mengxuan (JPCS_2418_1_012092bib5) 2020 Ligong (JPCS_2418_1_012092bib4) 2020; 31 Wenjing (JPCS_2418_1_012092bib1) 2020; 13 Liying (JPCS_2418_1_012092bib7) 2020 Zhenfeng (JPCS_2418_1_012092bib3) 2020 Xiuhua (JPCS_2418_1_012092bib2) 2020 Qingman (JPCS_2418_1_012092bib9) 2021 Kai (JPCS_2418_1_012092bib10) 2020 Xueyun (JPCS_2418_1_012092bib6) 2020 Yan (JPCS_2418_1_012092bib8) 2020; 17 |
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Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution,... Given the high power consumption rate of large venues with high power consumption, excessive carbon emissions, and severe environmental pollution, this paper... |
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StartPage | 12092 |
SubjectTerms | Big Data Carbon content Data mining Indicators Linear programming Physics Power consumption |
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Title | Low Carbon Operation Mode of Large High Power Consumption Venues Based on Big Data Mining Technology |
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