南方电网技术2024，Vol.18Issue(7)：118-128,138,12.DOI:10.13648/j.cnki.issn1674-0629.2024.07.013
考虑新能源随机性的新型电力系统图深度学习稳定指标概率分布评估模型
Graph Deep Learning Based Stability Index Probability Distribution Assessment Method of New Power System Considering the Stochastic Output of Renewable Energy
摘要
Abstract
The characteristics of large-scale stochastic output of renewable energy in the new power system have posed a risk of failure in the current online transient stability assessment results.This issue simultaneously challenges existing methods in terms of component modeling accuracy,system topology adaptability and computational speed.In this study,a novel approach is proposed that combines improved confidence band method based on re-probability and a probability distribution and confidence band evalua-tion model of stable index based on graph deep learning.The graph deep learning model rapidly evaluates a few sampled points,which are then expanded using the confidence band method based on re-probability.Temporal domain simulations are guided by co-occurrence knowledge from labeled data to enhance accuracy.Finally,the confidence band calculation method is employed to derive the stability probability distribution and assessment conclusion in intervals under stochastic output conditions.The method capitalizes on the topological adaptability and rapid computation inherent to graph deep learning.Moreover,it remains unhindered by limitations in component modeling accuracy.The conclusions drawn from the confidence band calculation are firmly rooted in theory and can evaluate the stable probability distribution.Evaluation accuracy verification on the IEEE-39 and IEEE-300 bus systems demonstrates the efficacy of the proposed method in accurately predicting specified transient stability indices and delivering reliable probability assessments.关键词
新能源随机性/新型电力系统/暂态功角稳定/概率评估/图深度学习/置信带/重概率化Key words
stochastic output of renewable energy/new power system/transient angular stability/probabilistic assessment/graph deep learning/confidence band/re-probability分类
动力与电气工程引用本文复制引用
管霖,陈鎏凯,陈灏颖,李永哲..考虑新能源随机性的新型电力系统图深度学习稳定指标概率分布评估模型[J].南方电网技术,2024,18(7):118-128,138,12.基金项目
国家自然科学基金资助项目(52077080,U22B6007):云南电网有限责任公司科技项目(056200KK52220044).Supported by the National Natural Science Foundation of China(52077080,U22B6007),the Science and Technology Project of Yunnan Power Grid Co.,Ltd.(056200KK52220044). （52077080,U22B6007）
