Issue |
E3S Web Conf.
Volume 248, 2021
2021 3rd International Conference on Civil Architecture and Energy Science (CAES 2021)
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Article Number | 02033 | |
Number of page(s) | 5 | |
Section | Energy Technology Application and Energy Saving and Emission Reduction Research and Development | |
DOI | https://doi.org/10.1051/e3sconf/202124802033 | |
Published online | 12 April 2021 |
Research on electric power development and economic growth in Hebei Province based on business cycle analysis
1 Electric Power Research Institute of State Grid Shaanxi Electric Power Company, Xi’an 710100, China ;
2 School of Economics and Management, North China Electric Power University, Beijing 102206, China ;
3 Electric Power Research Institute of State Grid Shandong Electric Power Company, Jinan 250021, China ;
* Corresponding author: ealinne13@ncepu.edu.cn
With the improvement of China’s electrification level, the relationship between electricity power consumption and social economy development is getting closer. Under this background, in this paper, the business cycle analysis method is applied to the electricity power industry in Hebei Province, and the link between electric power generation and economic development is determined through the prosperity index. First of all, the steps and methods of business cycle analysis were introduced, and the time-difference grey correlation method considering the consistency of time series to screen indicators was put forward, thus to reduce the number of indicators. Next, Hebei Province was taken as an example, and its monthly data related to power generation and economic growth in the 10 years from 2009 to 2018 to was selected to build the business cycle indicator system, at last the composite prosperity index of Hebei Province in electric power industry was calculated. This research results manifest that it is feasible to apply the business cycle analysis to the power industry.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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