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  • 标题:EVALUATION AND DEVELOPMENT TREND PREDICTION OF GUANGDONG'S ELECTRIC ENERGY AND ENVIRONMENTAL EFFICIENCY
  • 本地全文:下载
  • 作者:Junjun Zheng ; Yongji Wang
  • 期刊名称:Fresenius Environmental Bulletin
  • 印刷版ISSN:1018-4619
  • 出版年度:2021
  • 卷号:30
  • 期号:7
  • 页码:8668-8674
  • 语种:English
  • 出版社:PSP Publishing
  • 摘要:Under the influence of the status of the power industry, the economic efficiency of power energy in Guangdong Province is gradually decreasing. In or-der to improve the economic efficiency of power en-ergy in Guangdong Province, the economic effi-ciency evaluation model of power energy in Guang-dong Province based on VAR analysis is constructed and its development trend is predicted. We recon-struct the characteristic space of the power energy distribution time series, obtain the average mutual information of the power energy transmission time series in Guangdong Province. Then, we use the above information as a constraint condition, use the VAR analysis method to perform statistical analysis on the economic efficiency of power energy, and ob-tain the power energy economy of Guangdong Prov-ince. The cross-correlation feature quantity of effi-ciency is used to construct the probability statistical equation of Guangdong's power energy economic efficiency. Within the confidence interval of power energy output, the economic efficiency data and panel data of Guangdong's power energy output are selected as the regression analysis objects to con-struct Guangdong economic efficiency evaluation model of provincial power energy. The experimental results show that the power energy economic effi-ciency of the designed model reaches more than 95%. Compared with the models in the literature, the model in this study can effectively improve the eco-nomic efficiency of power energy and predict the de-velopment trend of power energy in Guangdong Province, which can finally realize the sustainable development of power energy in Guangdong Prov-ince.
  • 关键词:VAR analysis;power energy;economic efficiency;evalua-tion model;development trend forecast
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