{"title":"Operation resilience assessment of distribution networks based on voltage sag recorded data","authors":"Yifei Chen, Zixuan Zheng, Xianyong Xiao, Wenxi Hu, Yunzhu Chen","doi":"10.1049/ell2.70126","DOIUrl":null,"url":null,"abstract":"<p>Voltage sags are one of the primary factors in power quality issues that lead to losses for sensitive users and reduce the operation resilience of distribution networks. However, due to the lack of accessibility in sensitive users’ production information, accurately quantifying the resilience of distribution networks under the impact of voltage sags is challenging. In this letter, first an operation resilience index using a trapezoidal curve is defined. Considering the varying tolerance levels of sensitive users to voltage sags, a feature indices system is established using the adaptive <i>S</i>-transform, and a sample dataset is generated through the Monte Carlo method. Finally, a mapping relationship between sag characteristics and operation resilience indices is established using the XGBoost-stacking algorithm. Simulations based on voltage sag recorded data validate the effectiveness and practicality of the proposed method. This data-physics hybrid-driven model offers a quantitative approach for developing resilience enhancement strategies.</p>","PeriodicalId":11556,"journal":{"name":"Electronics Letters","volume":"61 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ell2.70126","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronics Letters","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ell2.70126","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Voltage sags are one of the primary factors in power quality issues that lead to losses for sensitive users and reduce the operation resilience of distribution networks. However, due to the lack of accessibility in sensitive users’ production information, accurately quantifying the resilience of distribution networks under the impact of voltage sags is challenging. In this letter, first an operation resilience index using a trapezoidal curve is defined. Considering the varying tolerance levels of sensitive users to voltage sags, a feature indices system is established using the adaptive S-transform, and a sample dataset is generated through the Monte Carlo method. Finally, a mapping relationship between sag characteristics and operation resilience indices is established using the XGBoost-stacking algorithm. Simulations based on voltage sag recorded data validate the effectiveness and practicality of the proposed method. This data-physics hybrid-driven model offers a quantitative approach for developing resilience enhancement strategies.
期刊介绍:
Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews.
Scope
As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below.
Antennas and Propagation
Biomedical and Bioinspired Technologies, Signal Processing and Applications
Control Engineering
Electromagnetism: Theory, Materials and Devices
Electronic Circuits and Systems
Image, Video and Vision Processing and Applications
Information, Computing and Communications
Instrumentation and Measurement
Microwave Technology
Optical Communications
Photonics and Opto-Electronics
Power Electronics, Energy and Sustainability
Radar, Sonar and Navigation
Semiconductor Technology
Signal Processing
MIMO