发电技术 ›› 2022, Vol. 43 ›› Issue (5): 707-717.DOI: 10.12096/j.2096-4528.pgt.22109

• 新型储能系统 • 上一篇    下一篇

人工智能在分布式储能技术中的应用

霍龙1,2, 张誉宝1,2, 陈欣1,2   

  1. 1.西安交通大学电力设备电气绝缘国家重点实验室新型储能能量转换纳米研究中心,陕西省 西安市 710049
    2.西安交通大学电气工程学院,陕西省 西安市 710049
  • 收稿日期:2022-06-24 出版日期:2022-10-31 发布日期:2022-11-04
  • 作者简介:霍龙(1992),男,博士研究生,研究方向为电网鲁棒性分析、人工智能在电力系统中的应用,eehl921105@stu.xjtu.edu.cn
    张誉宝(1997),男,硕士研究生,研究方向为基于深度强化学习的V2G调度研究,yubaozhang@stu.xjtu.edu.cn
    陈欣(1977),男,博士,副教授,研究方向为基于人工智能的电网预测、调控和诊断技术,复杂电网稳定性和鲁棒性分析等,本文通信作者,xin.chen.nj@xjtu.edu.cn
  • 基金资助:
    国家自然科学基金项目(21773182(B030103)

Artificial Intelligence Applications in Distributed Energy Storage Technologies

Long HUO1,2, Yubao ZHANG1,2, Xin CHEN1,2   

  1. 1.Center of Nanomaterials for Renewable Energy, State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, Shaanxi Province, China
    2.School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, Shaanxi Province, China
  • Received:2022-06-24 Published:2022-10-31 Online:2022-11-04
  • Supported by:
    the National Natural Science Foundation of China (21773182(B030103)

摘要:

分布式储能是智能配电网和微电网中的关键组成部分。作为目前最具颠覆性的科学技术之一,人工智能有望改变传统分布式储能建模、分析和控制方式,营造更智能化的应用前景。针对人工智能在分布式储能技术中的应用问题,简要回顾了人工智能在电力系统的发展历程,分析了其在分布式储能中的应用适配性问题,归纳总结微电网、智能楼宇和车网协同3种不同空间尺度场景下,人工智能在分布式储能中的具体应用方向和研究成果,并对未来发展趋势进行了展望,以期为分布式储能的智能化研究和发展提供有益参考。

关键词: 分布式储能, 人工智能, 微电网, 智能楼宇, 车网协同

Abstract:

Distributed energy storage (DES) is a key component in smart distribution networks and microgrids. As one of the current disruptive technologies, artificial intelligence (AI) is expected to change the traditional modeling, analysis, and control methods of DES and make DES more intelligent. The development of the AI application in the field of power systems and the applicability of the modern AI methods in DES were briefly reviewed. Then, the AI application directions and the related research trends in three DES of different scales, micro-grid, smart building, and vehicle-to-grid (V2G), were considered. Finally, the future development of AI in DES was presented, in order to provide useful reference for intelligent research and development of distributed energy storage

Key words: distributed energy storage, artificial intelligence, micro-grid, smart building, vehicle-to-grid

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