发电技术2025，Vol.46Issue(3)：438-453,16.DOI:10.12096/j.2096-4528.pgt.24152
基于大语言模型的电力系统预测技术研究综述
Review of Power System Prediction Technologies Based on Large Language Models
摘要
Abstract
[Objectives]With the large-scale integration of renewable energy,new-type power systems require greater flexibility and higher prediction accuracy for prediction technology.Traditional prediction methods have limitations in handling dynamic and complex scenarios,highlighting the need for prediction technologies tailored to these systems.Large language models(LLMs),as generative artificial intelligence technologies,have capabilities in multimodal data integrating,few-shot learning,and multitask handling,enabling more intelligent and precise solutions for the prediction of power systems.Therefore,this study focuses on analyzing the current applications and advantages of LLMs in power system prediction.[Methods]First,the fundamental architecture,training methods,and current application status of LLMs are discussed.Then,their principles and implementations in prediction are explained,with emphasis on advantages and prospects in load prediction,renewable generation prediction,and electricity price prediction.Finally,challenges in LLM-based prediction applications are analyzed from three aspects:data quality management,privacy protection,and computational resources,and feasible solutions are proposed.[Conclusions]Through comparative analysis of various forecasting tasks,LLMs demonstrate superior capabilities in few-shot learning and multimodal data processing compared to traditional methods,making them more adaptable to complex and variable prediction scenarios.Effective application of LLMs can provide innovative solutions for electricity market prediction.关键词
大语言模型(LLM)/人工智能(AI)/新型电力系统/负荷预测/电价预测/新能源出力预测/隐私保护/数据训练Key words
large language model(LLM)/artificial intelligence(AI)/new-type power system/load prediction/electricity price prediction/renewable energy output prediction/privacy protection/data training分类
动力与电气工程引用本文复制引用
张祖菡,刘敦楠,凡航,杨柳青,段赟杰,李赟,马振宇..基于大语言模型的电力系统预测技术研究综述[J].发电技术,2025,46(3):438-453,16.基金项目
国家自然科学基金项目(72171082) （72171082）
中央高校基本科研业务费专项资金(2024MS027).Project Supported by National Natural Science Foundation of China(72171082) （2024MS027）
Special Funds for Basic Scientific Research Operations of Central Universities(2024MS027). （2024MS027）
