LAPSE:2019.1173
Published Article
LAPSE:2019.1173
Multiple Scenarios Forecast of Electric Power Substitution Potential in China: From Perspective of Green and Sustainable Development
November 24, 2019
To achieve sustainable social development, the Chinese government conducts electric power substitution strategy as a green move. Traditional fuels such as coal and oil could be replaced by electric power to achieve fundamental transformation of energy consumption structure. In order to forecast and analyze the developing potential of electric power substitution, a forecasting model based on a correlation test, the cuckoo search optimization (CSO) algorithm and extreme learning machine (ELM) method is constructed. Besides, China’s present situation of electric power substitution is analyzed as well and important influencing factors are selected and transmitted to the CSO-ELM model to carry out the fitting analysis. The results showed that the CSO-ELM model has great forecasting accuracy. Finally, combining with the cost, policy supports, subsidy mechanism and China’s power consumption data in the past 21 years, four forecasting scenarios are designed and the forecasting results of 2019−2030 are calculated, respectively. Results under multiple scenarios may give suggestions for future sustainable development.
Record ID
Keywords
CSO-ELM, electric power substitution, green sustainable development, potential forecasting
Subject
Suggested Citation
Wu J, Tan Z, De G, Pu L, Wang K, Tan Q, Ju L. Multiple Scenarios Forecast of Electric Power Substitution Potential in China: From Perspective of Green and Sustainable Development. (2019). LAPSE:2019.1173
Author Affiliations
Wu J: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Tan Z: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China; School of Economics and Manage
De G: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Pu L: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Wang K: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Tan Q: State Grid Energy Research Institute Co., Ltd., Changping District, Beijing 102209, China
Ju L: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
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Tan Z: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China; School of Economics and Manage
De G: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Pu L: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Wang K: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
Tan Q: State Grid Energy Research Institute Co., Ltd., Changping District, Beijing 102209, China
Ju L: School of Economics and Management, North China Electric Power University, Beijing 102206, China; Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China
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Journal Name
Processes
Volume
7
Issue
9
Article Number
E584
Year
2019
Publication Date
2019-09-02
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr7090584, Publication Type: Journal Article
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Published Article
LAPSE:2019.1173
This Record
External Link
doi:10.3390/pr7090584
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390
Version History
[v1] (Original Submission)
Nov 24, 2019
Verified by curator on
Nov 24, 2019
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v1
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https://psecommunity.org/LAPSE:2019.1173
Original Submitter
Calvin Tsay
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