Abstract

With the advent of the Energy 4.0 era, the adoption of “Internet + artificial intelligence” systems will enable the transformation and upgrading of the traditional energy industry. This will alleviate the energy and environmental problems that China is currently facing. The integrated development of artificial intelligence and the energy industry has become inevitable in the development of future energy systems. This study applied a comprehensive evaluation index to the energy industry to calculate the comprehensive development index of the energy industry in 30 provinces of China from 2000 to 2017. Then, taking Guangdong and Jiangsu as examples, the synthetic control method was used to explore the direction and intensity of the integrated development of artificial intelligence and the energy industry on the comprehensive development level of the local energy industry. The results showed that when artificial intelligence (AI) and the energy industry achieved a stable coupled development without the need to move to the coordination stage, the coupling effect promoted the development of the regional energy industry, and the annual growth rate of the comprehensive development index was above 20%. This coupling effect passed the placebo test and ranking test and was significant at the 10% level, indicating the robustness and validity of the experimental results, which strongly confirmed the great potential of AI in re-empowering traditional industries from the data perspective. Based on the findings, corresponding policy recommendations were proposed on how to promote the development of inter-regional AI, how the government, enterprises, and universities could cooperate to promote the coordinated development of AI and energy, and how to guide the integration process of regional AI and energy industries according to local conditions, in order to maximize the technological dividend of AI and help the construction of smart energy in China.

Highlights

  • The synthetic control method was used to explore the direction and impact intensity of the integration development of two systems of artificial intelligence and energy industry on the comprehensive development level of local energy industry, and the robustness and validity of the empirical results were verified by placebo and ranking tests

  • We eventually drew the following conclusions: (1) When a stable coupling development relationship between regional artificial intelligence (AI) and energy industry was achieved without the need to reach a coordination relationship, the coupling effect began to contribute to the improvement of the comprehensive development level of the local energy industry

  • (2) After the stable coupling development between regional AI and energy industry, the comprehensive development level of energy industry in Guangdong and Jiangsu grew at more than 20% per year, and this empirical result was significant at 10% level

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. By clarifying the correctness and necessity of the integration and development of AI and energy industry and putting forward targeted policy recommendations and action measures according to the actual development status of each region can we effectively promote the construction of smart energy in China. The main contributions are as follows: (1) some regions have achieved the coupling and coordinated development of AI and energy industry, but whether this integration development has a positive promoting effect or a negative inhibiting effect on the local energy industry is unknown. It is unknown when this coupling effect starts to work and how much it affects the local energy industry, but this paper can quantify this coupling effect.

Research on AI
The Synthetic Control Method
Model Construction
Variable Descriptions and Data Sources
Selection of Cities in the Experimental Group
Selection of Time Points
Evaluation
Empirical Analysis of the Synthetic Control Method
Validity Test
Conclusions
Findings
Policy Implications
Full Text
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