集成技术2026，Vol.15Issue(2)：50-75,26.DOI:10.12146/j.issn.2095-3135.20250815001
耦合多源不确定性的虚拟电厂极端场景:分类框架、生成机制与影响评估综述
Extreme Scenarios of Virtual Power Plants Coupled with Multi-Source Uncertainties:Classification Frameworks,Generation Mechanisms,and Impact Assessment
摘要
Abstract
As a novel energy regulation paradigm,the stability of virtual power plants faces severe challenges under extreme scenarios.This paper systematically reviews the classification frameworks,generation methods,and impact assessment of virtual power plant extreme scenarios.Firstly,a three-dimensional classification framework is constructed based on source mechanisms,impact scope,and temporal scales,revealing the heterogeneous characteristics of extreme events.Secondly,extreme scenario generation methods are categorized:physics-based approaches including Monte Carlo simulation,fault tree analysis,Markov chains,and multi-physics-domain simulation;data-driven approaches encompassing extreme value theory,generative adversarial networks,and reinforcement learning;and hybrid methods integrating physical constraints with data-driven techniques.Evaluation metrics and verification methodologies are further proposed to ensure the engineering applicability of generated scenarios.Finally,this paper points out the current challenges such as data scarcity and low computational efficiency,and looks forward to future research directions including cross-scale coupled modeling,construction of a physics-data fusion framework,and application of large language models to improve scenario generation,thereby providing theoretical support for enhancing the resilience of virtual power plants.关键词
虚拟电厂/极端场景分类/场景生成方法/韧性评估Key words
virtual power plant/extreme scenario classification/scenario generation methods/resilience assessment分类
信息技术与安全科学引用本文复制引用
宋家冯,杨之乐,梁睿,刘典安,郭媛君..耦合多源不确定性的虚拟电厂极端场景:分类框架、生成机制与影响评估综述[J].集成技术,2026,15(2):50-75,26.基金项目
天津市科技局2022年院市合作项目(22YFYSHZ00330) （22YFYSHZ00330）
2022 年度可持续发展科技专项(双碳专项)(KCXST20221021111402006) （双碳专项）
"广东特支计划"青年拔尖人才项目(2023TQ07L745) （2023TQ07L745）
韶关市"南岭团队计划"项目(2022001) This work is supported by Tianjin Municipal Science and Technology Bureau 2022 Institute-City Cooperation Project(22YFYSHZ00330),and 2022 Science and Technology Special Project for Sustainable Development(Dual Carbon Special Project)(KCXST20221021111402006),and Guangdong Special Support Plan for Young Top-Talent Project(2023TQ07L745),and Nanling Team Project of Shaoguan City(2022001) （2022001）
