摘要
可解释人工智能(XAI)作为新型人工智能(AI)技术,具有呈现AI过程逻辑、揭示AI黑箱知识、提高AI结果可信程度的能力。XAI与电力系统的深度耦合将加速AI技术在电力系统的落地应用,在人机交互的过程中为电力系统的安全、稳定提供助力。文中梳理了电力系统XAI的历史脉络、发展需求及热点技术,总结了XAI在源荷预测、运行控制、故障诊断、电力市场等方面的电力应用,并围绕解释含义、迭代框架、数模融合等方面展望了电力系统XAI的应用前景,可为推动电力系统智能化转型与人机交互迭代提供理论参考与实践思路。
Explainable artificial intelligence(XAI),as a new type of artificial intelligence(AI)technologies,can present the logic of the AI process,reveal the AI black-box knowledge,and improve the credibility of the AI results.The deep coupling between XAI and power systems may accelerate the AI technology application in the power system and assist with the safety and stability of human-machine interaction.Therefore,this paper reviews the historical context,development needs,and hot technologies of XAI in the power system,summarizes its applications in source-load forecasting,operation control,fault diagnosis,and electricity market,and explores the application prospects of XAI in the power system around aspects such as interpretability,iterative framework,and number-matrix fusion.This paper aims to provide theoretical references and practical ideas for promoting the intelligent transformation and iterative human-machine interaction of the power system.
作者
王小君
窦嘉铭
刘曌
刘畅宇
蒲天骄
和敬涵
WANG Xiaojun;DOU Jiaming;LIU Zhao;LIU Changyu;PU Tianjiao;HE Jinghan(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China;China Electric Power Research Institute,Beijing 100192,China)
出处
《电力系统自动化》
EI
CSCD
北大核心
2024年第4期169-191,共23页
Automation of Electric Power Systems
基金
国家自然科学基金资助项目(52377071)
国家自然科学基金青年基金资助项目(52107068)。
关键词
电力系统
人工智能
可解释性
机器学习
power system
artificial intelligence
explainability
machine learning
