电力系统保护与控制2025，Vol.53Issue(10)：13-22,10.DOI:10.19783/j.cnki.pspc.241043
数据-物理混合驱动的配电网运行韧性评估方法与提升策略
A data-physical hybrid-driven method for evaluating and enhancing the operational resilience of distribution networks
摘要
Abstract
The opacity of production information from various sensitive users in distribution networks makes it difficult to construct explicit functions to accurately quantify the impact of voltage sags on sensitive loads,thereby limiting the effectiveness of resilience enhancement strategies for distribution network operations.To address this issue,a data-physical hybrid-driven method is proposed for evaluating and enhancing distribution network operational resilience.By drawing analogies with traditional resilience indices and their definitions,a new operational resilience index that accounts for the impact of voltage sags on sensitive users is constructed.Considering the different tolerance characteristics of various sensitive users to voltage sags,a voltage sag trajectory characteristic system is established to represent the response characteristics of different sensitive loads.A data-driven model is then proposed to evaluate distribution network operational resilience.On this basis,the data-driven resilience evaluation process is embedded into a physical model for multi-objective energy storage optimization.Finally,a case study based on the IEEE33-bus distribution network is conducted.The results demonstrate that the proposed data-physical hybrid-driven model for energy storage optimization can address the challenge of explicitly modelling the functional relationship between voltage sag characteristics and resilience indices,and can enhance resilience evaluation results while ensuring economic operation of the distribution network.关键词
配电网运行韧性/电压暂降/随机森林回归算法/储能优化配置/数据-物理混合模型Key words
distribution network operational resilience/voltage sag/random forest regression(RFR)algorithm/energy storage optimization configuration/data-physical hybrid model引用本文复制引用
陈逸飞,郑子萱,肖先勇,胡文曦,陈韵竹,王玉财..数据-物理混合驱动的配电网运行韧性评估方法与提升策略[J].电力系统保护与控制,2025,53(10):13-22,10.基金项目
This work is supported by the Young Scientists Fund of National Natural Science Foundation of China(No.52307128). 国家自然科学基金青年项目资助(52307128) （No.52307128）
四川省科技计划资助(2023YFG0245) （2023YFG0245）
