Pub Date : 2025-12-26DOI: 10.1109/tpwrd.2025.3646938
Mohamad-Amin Nasr, Ali Hooshyar
{"title":"Does Series Compensation Improve the Transient Stability of Inverter-Based Resources?","authors":"Mohamad-Amin Nasr, Ali Hooshyar","doi":"10.1109/tpwrd.2025.3646938","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3646938","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"50 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-26DOI: 10.1109/TPWRD.2025.3648940
Eric P. Nied;Stephen F. Poterala;Xingniu Huo;Dustin L. Sullivan
While it is well known that a Metal Oxide Varistor (MOV) heavily distorts the voltage wave of a high-current lightning impulse, less has been said about waveform distortions observed during power frequency testing. This paper shows that significant distortions are likely produced by practical generators during power frequency testing of MOVs, with the effect that average power dissipation of MOVs and surge arresters is severely impacted by generator setup. Four distribution transformer configurations with different output impedances were used to apply 60 Hz voltage waves to a conducting, 5 kV-rated MOV at six peak current levels. Distortion was found to be a function of generator impedance and current magnitude. In one typical experiment, even a slight distortion (Vrms / (Vpeak / √2) = 1.014) led to ∼33% decrease in average power dissipation compared to that of a distortion-free wave of the same rms voltage. Without consideration of these effects, seemingly minor differences in procedure can cause parts to erroneously pass or fail tests prescribed in IEEE C62.11 (2020) or IEC 60099-4 ed. 3.0, leading to arresters not meeting manufacturers’ 60 Hz TOV claims. A method is also outlined to correct for waveform distortion, enabling calculation of distortion-free average power dissipation.
{"title":"Waveform Distortions During Power Frequency Testing of Metal Oxide Varistors: Their Origin and Effect on Average Power Dissipation","authors":"Eric P. Nied;Stephen F. Poterala;Xingniu Huo;Dustin L. Sullivan","doi":"10.1109/TPWRD.2025.3648940","DOIUrl":"10.1109/TPWRD.2025.3648940","url":null,"abstract":"While it is well known that a Metal Oxide Varistor (MOV) heavily distorts the voltage wave of a high-current lightning impulse, less has been said about waveform distortions observed during power frequency testing. This paper shows that significant distortions are likely produced by practical generators during power frequency testing of MOVs, with the effect that average power dissipation of MOVs and surge arresters is severely impacted by generator setup. Four distribution transformer configurations with different output impedances were used to apply 60 Hz voltage waves to a conducting, 5 kV-rated MOV at six peak current levels. Distortion was found to be a function of generator impedance and current magnitude. In one typical experiment, even a slight distortion (V<sub>rms</sub> / (V<sub>peak</sub> / √2) = 1.014) led to ∼33% decrease in average power dissipation compared to that of a distortion-free wave of the same rms voltage. Without consideration of these effects, seemingly minor differences in procedure can cause parts to erroneously pass or fail tests prescribed in IEEE C62.11 (2020) or IEC 60099-4 ed. 3.0, leading to arresters not meeting manufacturers’ 60 Hz TOV claims. A method is also outlined to correct for waveform distortion, enabling calculation of distortion-free average power dissipation.","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"41 1","pages":"447-457"},"PeriodicalIF":3.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-26DOI: 10.1109/tpwrd.2025.3648950
Veeranna Kuruva, Amir H. Abolmasoumi, Vinu Thomas, Bogdan Marinescu
{"title":"Robust Loop-Shaping Control for Medium-High Frequency Oscillations Mitigation in Grid-Connected Converters with Effective Hardware Implementation","authors":"Veeranna Kuruva, Amir H. Abolmasoumi, Vinu Thomas, Bogdan Marinescu","doi":"10.1109/tpwrd.2025.3648950","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3648950","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"8 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-26DOI: 10.1109/TPWRD.2025.3648739
Chanaka Keerthisinghe;Aijun Deng;Xueyin Yu;Rosebud J. Lambert;Fernando Freitas
Lightning is a leading cause of wind turbine blade failures in the United States and globally, resulting in significant financial losses for the industry. Rapid detection of turbine strikes is essential to reduce these costs. While nearby lightning strikes can be detected with high accuracy, confirming whether a specific turbine was struck remains challenging. Current confirmation relies on manual inspections with drones, which may take hours to years if damage develops slowly during operation. This work presents a scalable, three-step framework for lightning strike confirmation that integrates lightning measurements, turbine alarms, and supervisory control and data acquisition (SCADA) based machine-learning anomaly detection. The first step analyzes the magnitude (kA) and proximity of nearby lightning strikes. The second step evaluates historical alarm patterns associated with lightning-induced damage. The third step applies machine learningbased anomaly detection to post-event SCADA signals, focusing on rotor speed, wind speed, and pitch angle behavior. The framework was evaluated using 26 U.S. wind turbines with confirmed lightning strikes between 2021 and 2024, together with 1650 turbines that experienced nearby strikes without direct impact. This timealigned dataset enables robust model training and validation. The proposed approach is designed for fleet-wide deployment and demonstrates strong scalability. At the highest confidence level, recall and precision were 96% and 86% at the next level, 100% and 81%. Deployment across Vestas' U.S. fleet could conservatively save over ${$}$ 16 million annually in avoided blade repair costs, excluding additional benefits from reduced turbine downtime, thereby contributing to lower wind energy costs.
{"title":"A Machine Learning-Enhanced System for Rapid Detection of Lightning-Impacted Wind Turbines","authors":"Chanaka Keerthisinghe;Aijun Deng;Xueyin Yu;Rosebud J. Lambert;Fernando Freitas","doi":"10.1109/TPWRD.2025.3648739","DOIUrl":"10.1109/TPWRD.2025.3648739","url":null,"abstract":"Lightning is a leading cause of wind turbine blade failures in the United States and globally, resulting in significant financial losses for the industry. Rapid detection of turbine strikes is essential to reduce these costs. While nearby lightning strikes can be detected with high accuracy, confirming whether a specific turbine was struck remains challenging. Current confirmation relies on manual inspections with drones, which may take hours to years if damage develops slowly during operation. This work presents a scalable, three-step framework for lightning strike confirmation that integrates lightning measurements, turbine alarms, and supervisory control and data acquisition (SCADA) based machine-learning anomaly detection. The first step analyzes the magnitude (kA) and proximity of nearby lightning strikes. The second step evaluates historical alarm patterns associated with lightning-induced damage. The third step applies machine learningbased anomaly detection to post-event SCADA signals, focusing on rotor speed, wind speed, and pitch angle behavior. The framework was evaluated using 26 U.S. wind turbines with confirmed lightning strikes between 2021 and 2024, together with 1650 turbines that experienced nearby strikes without direct impact. This timealigned dataset enables robust model training and validation. The proposed approach is designed for fleet-wide deployment and demonstrates strong scalability. At the highest confidence level, recall and precision were 96% and 86% at the next level, 100% and 81%. Deployment across Vestas' U.S. fleet could conservatively save over <inline-formula><tex-math>${$}$</tex-math></inline-formula> 16 million annually in avoided blade repair costs, excluding additional benefits from reduced turbine downtime, thereby contributing to lower wind energy costs.","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"41 1","pages":"437-446"},"PeriodicalIF":3.7,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145844697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Closing resistors are critical components in ultra-high-voltage circuit breakers, however, their dynamic conduction under pulsed-energy injection remains poorly understood, thereby limiting energy-handling capability and compromising breaker reliability. This study combines pulsed-energy injection experiments and thermoelectrically coupled simulations to elucidate the electrothermal response and conductivity evolution of carbon-ceramic resistors. By correlating macroscopic resistance variations with microscopic conductive-chain dynamics, the conduction process is divided into four distinct stages: transient conduction, sustained decline, steady fluctuation, and gradual recovery. A thermoelectric-driven mechanism governing the conductive network is proposed. The microscale network consists of non-conductive, discontinuous, and continuous conductive chains, whose activation is jointly controlled by both the electric field and temperature. Strong electric fields induce tunneling conduction in discontinuous chains, whereas thermal expansion effectively reduces contact resistance in continuous chains. The individual and coupled influences of temperature and electric field are quantified by numerical fitting of the recovery resistance versus temperature and transient resistance versus field. Results reveal a pronounced thermoelectric synergy with clear energy dependence. Under low-energy injection, coupling enhances carrier excitation, yielding resistance reductions exceeding the sum of individual thermal and electrical contributions. Under high-energy injection, conductive-chain saturation suppresses further synergy, leading to smaller-than-additive resistance reductions.
{"title":"Thermoelectric-Driven Conduction Mechanisms of Carbon-Ceramic Closing Resistors in Circuit Breakers Under Pulsed-Energy Injection","authors":"Jinru Sun;Huixiang Dai;Aoyu Wang;Zixin Fang;Xueling Yao;Guilai Yin;Wei Chen","doi":"10.1109/TPWRD.2025.3648189","DOIUrl":"10.1109/TPWRD.2025.3648189","url":null,"abstract":"Closing resistors are critical components in ultra-high-voltage circuit breakers, however, their dynamic conduction under pulsed-energy injection remains poorly understood, thereby limiting energy-handling capability and compromising breaker reliability. This study combines pulsed-energy injection experiments and thermoelectrically coupled simulations to elucidate the electrothermal response and conductivity evolution of carbon-ceramic resistors. By correlating macroscopic resistance variations with microscopic conductive-chain dynamics, the conduction process is divided into four distinct stages: transient conduction, sustained decline, steady fluctuation, and gradual recovery. A thermoelectric-driven mechanism governing the conductive network is proposed. The microscale network consists of non-conductive, discontinuous, and continuous conductive chains, whose activation is jointly controlled by both the electric field and temperature. Strong electric fields induce tunneling conduction in discontinuous chains, whereas thermal expansion effectively reduces contact resistance in continuous chains. The individual and coupled influences of temperature and electric field are quantified by numerical fitting of the recovery resistance versus temperature and transient resistance versus field. Results reveal a pronounced thermoelectric synergy with clear energy dependence. Under low-energy injection, coupling enhances carrier excitation, yielding resistance reductions exceeding the sum of individual thermal and electrical contributions. Under high-energy injection, conductive-chain saturation suppresses further synergy, leading to smaller-than-additive resistance reductions.","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"41 1","pages":"458-469"},"PeriodicalIF":3.7,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-25DOI: 10.1109/tpwrd.2025.3647884
Jiawei Yuan, Xiaojian Dong, Lifeng Xing, Xuan Dong, Jun Liu, Zaibin Jiao
{"title":"Fault Diagnosis Method for Single-Phase-to-Ground Faults Based on Phase-to-Phase Current Fault Components in Distribution Networks","authors":"Jiawei Yuan, Xiaojian Dong, Lifeng Xing, Xuan Dong, Jun Liu, Zaibin Jiao","doi":"10.1109/tpwrd.2025.3647884","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3647884","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"26 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-25DOI: 10.1109/tpwrd.2025.3647954
Fengrun Wang, Wenqiang Zhao, Jun Zhou, Yuanjie Li, Tianqi Song, Zhitong Tian, Lei Lan, Hailiang Lu
{"title":"Cable Shield Grounding for Transient Overvoltage Testing in Power Generation/Transformer Substations","authors":"Fengrun Wang, Wenqiang Zhao, Jun Zhou, Yuanjie Li, Tianqi Song, Zhitong Tian, Lei Lan, Hailiang Lu","doi":"10.1109/tpwrd.2025.3647954","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3647954","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"8 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145830080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Synchrophasor-based sub-synchronous oscillation (SSO) parameter identification is effective for monitoring SSOs, while its performance can be significantly affected by measurement noise, posing serious challenges to reliable identification. This study proposes an improved identification scheme that combines adaptive empirical Fourier decomposition (AEFD) with the Prony method to enable accurate and simultaneous estimation of sub/super-synchronous modes. First, the AEFD method is applied to oscillation signals, effectively decomposing the signals into sub-synchronous and super-synchronous modal components. Particularly, the sparsity index (SI) is introduced to determine the number of oscillation modes contained in the signal. Subsequently, the Prony method is employed on the decomposed components to extract modal parameters. The proposed method effectively suppresses modal aliasing and improves noise robustness of the empirical wavelet transform by employing an improved spectrum segmentation technique and a zero-phase filter bank, thereby enhancing the extraction accuracy of the estimation results. Through comparisons with existing methods and simulated case studies, it is verified that the proposed method performs exceptionally well in terms of accuracy, mode mixing suppression and noise robustness, demonstrating its superiority and effectiveness in the extraction of sub/super-synchronous oscillation parameters.
{"title":"Synchrophasor-Based Parameter Identification of Sub/Super-Synchronous Oscillations Using Adaptive Empirical Fourier Decomposition","authors":"Lixin Wang;Zihan Zhang;Zhenglong Sun;Han Gao;Shouqi Jiang;Shiwei Xia;Tek Tjing Lie","doi":"10.1109/TPWRD.2025.3647587","DOIUrl":"10.1109/TPWRD.2025.3647587","url":null,"abstract":"Synchrophasor-based sub-synchronous oscillation (SSO) parameter identification is effective for monitoring SSOs, while its performance can be significantly affected by measurement noise, posing serious challenges to reliable identification. This study proposes an improved identification scheme that combines adaptive empirical Fourier decomposition (AEFD) with the Prony method to enable accurate and simultaneous estimation of sub/super-synchronous modes. First, the AEFD method is applied to oscillation signals, effectively decomposing the signals into sub-synchronous and super-synchronous modal components. Particularly, the sparsity index (SI) is introduced to determine the number of oscillation modes contained in the signal. Subsequently, the Prony method is employed on the decomposed components to extract modal parameters. The proposed method effectively suppresses modal aliasing and improves noise robustness of the empirical wavelet transform by employing an improved spectrum segmentation technique and a zero-phase filter bank, thereby enhancing the extraction accuracy of the estimation results. Through comparisons with existing methods and simulated case studies, it is verified that the proposed method performs exceptionally well in terms of accuracy, mode mixing suppression and noise robustness, demonstrating its superiority and effectiveness in the extraction of sub/super-synchronous oscillation parameters.","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"41 1","pages":"423-436"},"PeriodicalIF":3.7,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-24DOI: 10.1109/tpwrd.2025.3647761
Peng Zhang, Wenjuan Du, H. F. Wang
{"title":"Design and Small-Signal Stability Analysis of Grid-Forming Inverter Based on Generalized Fractional-Order Virtual Synchronous Generator Control","authors":"Peng Zhang, Wenjuan Du, H. F. Wang","doi":"10.1109/tpwrd.2025.3647761","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3647761","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"3 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-12-24DOI: 10.1109/tpwrd.2025.3647646
Rizwan Rafique Syed, Hans Kristian Høidalen
{"title":"Investigating the Impact of Fault Handling Models on Reliability Indices of Digital Substation","authors":"Rizwan Rafique Syed, Hans Kristian Høidalen","doi":"10.1109/tpwrd.2025.3647646","DOIUrl":"https://doi.org/10.1109/tpwrd.2025.3647646","url":null,"abstract":"","PeriodicalId":13498,"journal":{"name":"IEEE Transactions on Power Delivery","volume":"8 1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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