Pub Date : 2026-01-12DOI: 10.1109/tsg.2026.3653032
Xin Wang, Ju H. Park, Jiangfeng Wang, Dan Zhang
{"title":"Neural Network-based adaptive LFC Approach for Multi-Area Power Systems Vulnerable to Hybrid Attacks","authors":"Xin Wang, Ju H. Park, Jiangfeng Wang, Dan Zhang","doi":"10.1109/tsg.2026.3653032","DOIUrl":"https://doi.org/10.1109/tsg.2026.3653032","url":null,"abstract":"","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"34 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/tsg.2025.3649018
Qian Wan, Yan-Wu Wang, Xiao-Kang Liu, Andrew D. Syrmakesis, Nikos D. Hatziargyriou
{"title":"Dynamic Self-Triggered Load Frequency Control for Multi-Area Power Systems under Non-Ideal Communication Environments","authors":"Qian Wan, Yan-Wu Wang, Xiao-Kang Liu, Andrew D. Syrmakesis, Nikos D. Hatziargyriou","doi":"10.1109/tsg.2025.3649018","DOIUrl":"https://doi.org/10.1109/tsg.2025.3649018","url":null,"abstract":"","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"38 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/tsg.2026.3651988
Zhenghui Li, Kangping Li, Chunyi Huang, Mahmud Fotuhi-Firuzabad
{"title":"Probability Density Forecasting of Electricity Price Difference in Spot Market","authors":"Zhenghui Li, Kangping Li, Chunyi Huang, Mahmud Fotuhi-Firuzabad","doi":"10.1109/tsg.2026.3651988","DOIUrl":"https://doi.org/10.1109/tsg.2026.3651988","url":null,"abstract":"","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"46 1","pages":"1-1"},"PeriodicalIF":9.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1109/tsg.2026.3652798
Himanshu Goyel, Alfan Presekal, Peter Palensky, Alexandru Ştefanov
{"title":"Anomaly Detection in Digital Substation Communication using Transformer-Based Distribution Fitting","authors":"Himanshu Goyel, Alfan Presekal, Peter Palensky, Alexandru Ştefanov","doi":"10.1109/tsg.2026.3652798","DOIUrl":"https://doi.org/10.1109/tsg.2026.3652798","url":null,"abstract":"","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"84 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Residential load profiling clustering is crucial for optimizing energy use and enhancing efficiency of power distribution system. However, current methods face three limitations like reliance on manual similarity measures, high computational costs, and inflexibility to new load profiles. To address these challenges, this letter proposes a large-scale anchor graph-based subspace clustering method for residential load profiling. Specifically, the distance matrix is directly learned from the load profile through subspace clustering to handle high-dimensional data and uncover hidden load patterns. Then, an anchor graph is constructed to capture the intrinsic structure of the learned subspace, which can effectively reduce the computational complexity. Finally, k-Nearest Neighbor (KNN) is adopted to assign labels to new load profiles based on selected anchor points, eliminating the need for re-clustering the entire dataset. Tests on real-world London household data confirm the method’s effectiveness and efficiency. The code is available at https://github.com/U-T-G/AGSC
{"title":"Anchor Graph-Based Subspace Clustering for Large-Scale Residential Load Profiling","authors":"Zhiping Lin;Weihao Hu;Di Cao;Pengfei Zhao;Zhe Chen","doi":"10.1109/TSG.2026.3651940","DOIUrl":"10.1109/TSG.2026.3651940","url":null,"abstract":"Residential load profiling clustering is crucial for optimizing energy use and enhancing efficiency of power distribution system. However, current methods face three limitations like reliance on manual similarity measures, high computational costs, and inflexibility to new load profiles. To address these challenges, this letter proposes a large-scale anchor graph-based subspace clustering method for residential load profiling. Specifically, the distance matrix is directly learned from the load profile through subspace clustering to handle high-dimensional data and uncover hidden load patterns. Then, an anchor graph is constructed to capture the intrinsic structure of the learned subspace, which can effectively reduce the computational complexity. Finally, k-Nearest Neighbor (KNN) is adopted to assign labels to new load profiles based on selected anchor points, eliminating the need for re-clustering the entire dataset. Tests on real-world London household data confirm the method’s effectiveness and efficiency. The code is available at <uri>https://github.com/U-T-G/AGSC</uri>","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"17 2","pages":"1746-1749"},"PeriodicalIF":9.8,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1109/tsg.2026.3651333
Yemi Ojo, Soumyadeep Nag, Temitayo O. Olowu
{"title":"Enabling Grid-Forming Control with Fault Ride-Through in Unbalanced Distribution Networks","authors":"Yemi Ojo, Soumyadeep Nag, Temitayo O. Olowu","doi":"10.1109/tsg.2026.3651333","DOIUrl":"https://doi.org/10.1109/tsg.2026.3651333","url":null,"abstract":"","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"41 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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