信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2025, Vol. 51 ›› Issue (6): 38-43.doi: 10.12267/j.issn.2096-5931.2025.06.007

专题:AI 驱动能源变革 上一篇    下一篇

人工智能驱动能源系统变革的挑战与应对策略

Challenges and countermeasures of artificial intelligence in energy system-driven transformation

汪振涛   

  1. 安徽电信规划设计有限责任公司,合肥 230000
  • 收稿日期:2025-05-12 出版日期:2025-06-25 发布日期:2025-07-04
  • 作者简介:
    汪振涛 安徽电信规划设计有限责任公司人工智能研究中心研究员,主要从事大语言模型应用、人工智能工程化以及智慧能源等领域的研究工作

WANG Zhentao   

  1. Anhui Telecom Planning and Design Institute Co., Ltd., Hefei 230000, China
  • Received:2025-05-12 Online:2025-06-25 Published:2025-07-04

摘要:

随着人工智能(Artificial Intelligence,AI)技术的迅猛发展,其在能源系统中的应用正逐步深入,从智能调度、故障诊断到能源管理与优化决策,正推动能源系统向智能化、低碳化、高效化方向转型。然而,AI在推动能源变革的过程中也面临诸多挑战,如数据质量和安全问题、模型透明度与可解释性不足、技术与制度协同不足以及伦理与政策的滞后等。系统梳理了AI在能源系统中的主要应用场景,深入分析了在能源系统转型过程中面临的关键技术与治理难题,并从技术、制度与政策三个维度提出应对策略,以期为实现新型能源系统的智能化升级提供理论支持和实践路径。

关键词: 人工智能, 能源系统, 智能化转型, 数据治理, 绿色低碳

Abstract:

With the rapid development of Artificial Intelligence (AI), its applications in energy systems are expanding, from intelligent scheduling and fault diagnosis to energy management and optimization, driving the transition toward smarter, low-carbon, and more efficient energy infrastructures. However, this transformation faces multiple challenges, including data quality and security issues, lack of model interpretability, insufficient coordination between technology and regulation, and delays in ethical and policy responses. This paper systematically reviews key AI application scenarios in energy systems, analyzes core technological and governance constraints in the transformation process, and proposes countermeasures from the perspectives of technology, institutions, and policy. The goal is to provide theoretical support and practical strategies for building intelligent, efficient, and sustainable future energy systems.

Key words: artificial intelligence, energy systems, intelligent transformation, data governance, green and low-carbon transition

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