The intelligent brain and the energy heart: Synergistic evolution of artificial intelligence and energy storage technology in China

被引:0
|
作者
Chen, Yan [1 ]
Lyu, Jiayi [1 ]
Akram, Umair [2 ]
Hou, Yuqi [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing, Peoples R China
[2] RMIT Univ, Business Sch, Ho Chi Minh City, Vietnam
基金
中国国家自然科学基金;
关键词
Artificial intelligence; Energy storage technology; Time-dependent interrelationship; China; TIME-SERIES; PARAMETER INSTABILITY; UNIT-ROOT; TESTS; SYSTEM;
D O I
10.1016/j.actpsy.2025.104711
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to explore how artificial intelligence (AI) and Energy Storage Technology (EST) interact and co-evolve. Utilizing a full-sample Granger causality test, we identified significant interactions between AI and EST. Afterwards, we further revealed their dynamic influence relationship using advanced sub- sampling techniques. Quantitative analysis indicates that AI positively influences EST by optimizing energy management systems, with an improvement of 15 % in efficiency, and by enhancing the intelligence level of energy storage. However, there are also negative effects, such as a 10 % increase in operational risks due to overreliance on AI. Similarly, EST facilitates the development of AI by providing a stable energy supply. AI and EST, like the intelligent brain and the energy heart, require mutual dependence for stable development. In context of the industrial revolution and technical advancement, this study provides meaningful recommendations. Strengthening technological research and innovation support, optimizing energy policies, and enhancing standardization will promote the deep integration and synergistic development of AI and EST. This will provide significant impetus for China's technological advancement and economic development, aiding in the achievement of sustainable development goals.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Energy storage technology innovation, policy support and the green transition of energy in China
    Zhao X.
    Zhao C.
    Chen G.
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2024, 44 (06): : 1749 - 1767
  • [22] Cognitive Artificial Intelligence: Brain-Inspired Intelligent Computation in Artificial Intelligence
    Ahmad, Adang Suwandi
    Sumari, Arwin Datumaya Wahyudi
    2017 COMPUTING CONFERENCE, 2017, : 135 - 141
  • [23] Exploring the Synergy of Artificial Intelligence in Energy Storage Systems for Electric Vehicles
    Miraftabzadeh, Seyed Mahdi
    Longo, Michela
    Di Martino, Andrea
    Saldarini, Alessandro
    Faranda, Roberto Sebastiano
    ELECTRONICS, 2024, 13 (10)
  • [24] Research on energy supply of intelligent energy system with energy storage
    Peng, Liyuan
    Zhang, Xiaohui
    Yuan, Jianli
    Fu, Jia
    2019 5TH INTERNATIONAL CONFERENCE ON ENERGY EQUIPMENT SCIENCE AND ENGINEERING, 2020, 461
  • [25] Artificial Intelligence and the Energy Transition
    Kyriakarakos, George
    SUSTAINABILITY, 2025, 17 (03)
  • [26] Genes, the brain, and artificial intelligence in evolution
    Naoyuki Kamatani
    Journal of Human Genetics, 2021, 66 : 103 - 109
  • [27] An evolution brain model for artificial intelligence
    Lu, Yiping
    Cha, Jianzhong
    Proceedings of 2006 International Conference on Artificial Intelligence: 50 YEARS' ACHIEVEMENTS, FUTURE DIRECTIONS AND SOCIAL IMPACTS, 2006, : 291 - 295
  • [28] Genes, the brain, and artificial intelligence in evolution
    Kamatani, Naoyuki
    JOURNAL OF HUMAN GENETICS, 2021, 66 (01) : 103 - 109
  • [29] Application of artificial intelligence and communication technology to water and energy balance models
    Zhang, Guanxiong
    Jin, Yechun
    Wang, Bingqiang
    WATER SUPPLY, 2023, 23 (07) : 2847 - 2864
  • [30] Impact of artificial intelligence technology applications on corporate energy consumption intensity
    Liu, Xiaoqian
    Cifuentes-Faura, Javier
    Zhao, Shikuan
    Wang, Long
    Yao, Jian
    GONDWANA RESEARCH, 2025, 138 : 89 - 103