Prediction Method of Beijing Electric-Energy Substitution Potential Based on a Grid-Search Support Vector Machine

Yuanying Chi, Yangyi Zhang, Guozheng Li and Yongke Yuan
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Yuanying Chi: School of Economics and Management, Beijing University of Technology, Beijing 100021, China
Yangyi Zhang: School of Economics and Management, Beijing University of Technology, Beijing 100021, China
Guozheng Li: School of Economics and Management, Beijing University of Technology, Beijing 100021, China
Yongke Yuan: School of Economics and Management, Beijing University of Technology, Beijing 100021, China

Energies, 2022, vol. 15, issue 11, 1-11

Abstract: Recently, “power cuts” and “coal price surges” have been significant concerns of individuals and societies. The main reasons for a power cut are a recent rapid increase in power consumption, shortage of thermal coal or the large shutdown capacity of thermal power units, resulting in a tight power supply in the power grid. In recent years, the shortage of fossil resources has led to frequent energy crises. In the context of carbon peaks and carbon neutralization, how to better develop electric-energy substitution and eliminate the dependence on fossil energy has become a problem that needs to be solved at present. In this paper, the influencing factors of electric-energy substitution in Beijing are analyzed, and the indexes affecting the electric-energy substitution are outlined. By constructing various machine-learning models, the prediction is performed. The results show that the Gaussian kernel support vector machine model based on a grid search has a good prediction effect on the electric-energy substitution potential in Beijing, which has certain guiding significance for electric-energy substitution potential analysis.

Keywords: electric-energy substitution; support vector machine; grid search (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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