摘要
随着全球能源转型和电力系统日益复杂,传统的配电网故障识别方法已难以满足新型配电网对高效、精准、实时诊断的需求,人工智能技术成为配电网故障识别的重要技术手段。本文分析了人工智能在配电网故障识别中的应用,介绍了特征工程、深度学习、强化学习和混合智能方法等四种主要技术,讨论了当前技术面临的数据质量、可解释性等挑战,并展望了未来技术的发展方向。本文为配电网故障识别领域的智能化发展提供了一些思路。
With the global energy transition and increasing complexity of the power system,traditional fault identification methods for distribution networks are no longer able to meet the needs of new distribution networks for efficient,accurate,and real-time diagnosis.Artificial intelligence technology has become an important technical means for fault identification in distribution networks.This article analyses the application of artificial intelligence in fault recognition in distribution networks,introducing four main technologies:feature engineering,deep learning,reinforcement learning,and hybrid intelligence methods.It discusses the challenges faced by current technologies,such as data quality and interpretability,and looks forward to the development direction of future technologies.This article provides some ideas for the intelligent development of fault identification in the field of distribution networks.
作者
郭泽霖
GUO Zelin(Zhongshan Power Supply Bureau of Guangdong Power Grid Co.,Ltd.,Zhongshan Guangdong 528403)
出处
《软件》
2025年第2期156-158,共3页
Software
关键词
配电网
故障识别
人工智能
深度学习
特征工程
distribution network
fault identification
artificial intelligence
deep learning
feature engineering
