Proceedings of the 3rd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2024, May 24–26, 2024, Jinan, China

Research Article

Research and Application of Association Analysis Model for Power and Economy in Key Industries

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  • @INPROCEEDINGS{10.4108/eai.24-5-2024.2350206,
        author={Xueting  Zhang and Yingxue  Li and Min  Wang and Wei  Wang and Hao  Wu and Qiqi  Dai and Jiawei  Gong and Xiaotong  Zhou},
        title={Research and Application of Association Analysis Model for Power and Economy in Key Industries },
        proceedings={Proceedings of the 3rd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2024, May 24--26, 2024, Jinan, China},
        publisher={EAI},
        proceedings_a={MSEA},
        year={2024},
        month={10},
        keywords={key industries; power-economy; association analysis; economic index; leading effect},
        doi={10.4108/eai.24-5-2024.2350206}
    }
    
  • Xueting Zhang
    Yingxue Li
    Min Wang
    Wei Wang
    Hao Wu
    Qiqi Dai
    Jiawei Gong
    Xiaotong Zhou
    Year: 2024
    Research and Application of Association Analysis Model for Power and Economy in Key Industries
    MSEA
    EAI
    DOI: 10.4108/eai.24-5-2024.2350206
Xueting Zhang1,*, Yingxue Li1, Min Wang1, Wei Wang1, Hao Wu1, Qiqi Dai1, Jiawei Gong1, Xiaotong Zhou2
  • 1: State Grid Jiangxi Electric Power Co., Ltd
  • 2: North China Electric Power University
*Contact email: 1070822628@qq.com

Abstract

Electric power is a 'thermometer' and 'barometer' of the national economy, and key industries are important driving forces for its growth. This paper focuses on the research of the association analysis model between power consumption in key industries and economic development, aiming to grasp the economic development trends from the perspective of power consumption in key industries. Firstly, the correlation characteristics of power consumption in key industries and the economy are analyzed. Then, an association analysis model is constructed, including a model for leading, coincident, and lagging relationships, as well as an economic index calculation model based on power data. Finally, an empirical study is conducted based on the electricity consumption data of a certain province's key industries and industrial value-added data. The results indicate that power consumption in key industries has a certain leading effect on the growth rate of industrial value-added, and it can forecast the changing trend of the year-on-year growth rate of industrial value-added, thus supporting macroeconomic regulation and control.