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Application of Clustering Algorithm by Data Mining in the Analysis of Smart Grid from the Perspective of Electric Power

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Published under licence by IOP Publishing Ltd
, , Citation Yaru Qi et al 2021 J. Phys.: Conf. Ser. 1982 012018 DOI 10.1088/1742-6596/1982/1/012018

1742-6596/1982/1/012018

Abstract

In recent years, the research on the relationship between economic development and power consumption is also a focus of government departments at all levels. The development of electric power (EP) not only has an impact on power supply enterprises and EP industry, but also is closely related to the social and economic development of the whole region and residents' life, that is, there must be some internal relationship between economic development and EP consumption. In many areas of our country, the situation of power consumption and economic development is not coordinated. Insufficient and untimely power supply will hinder economic growth, and excessive power supply will bring unnecessary waste of resources. This also reflects that the research on the relationship between economic development and power consumption is not in-depth, so the research on the relationship between power consumption and economic development has a certain theoretical significance. This paper studies the application of clustering algorithm based on data mining in the analysis of economic development characteristics(EDC) from the perspective of EP, uses K-means clustering algorithm to understand the relationship between EP development and economic development, understands its characteristic development application, studies the relationship between EP consumption and economy from the EP elastic coefficient method and output value unit consumption method, and uses K-means clustering algorithm to calculate, this paper uses the chart analysis method to analyze the correlation degree of power consumption structure and the relationship between different industrial GDP and power consumption. The results show that the total output of each industrial structure is in direct proportion to the power consumption. The total value of each industrial structure is increasing, and the power consumption is on the rise. For example, in 2016, the total value of the first industry was 186.81 trillion yuan, the second industry was 960.54 trillion yuan, the third industry was 515.96 trillion yuan, and the power consumption was 41.246 billion kwh, by 2020, the total value of the primary industry will be 220.66 trillion yuan, the secondary industry 1916.51 trillion yuan, the tertiary industry 866.22 trillion yuan, and its electricity consumption (EC) will be 57.697 billion kwh.

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10.1088/1742-6596/1982/1/012018