Electric Power Systems Research最新文献_第7页

Real-time system strength estimation using PMU data for modern grids with high IBR penetration 基于PMU数据的高IBR渗透现代电网实时系统强度估计

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-18 DOI: 10.1016/j.epsr.2025.112199

Hemantkumar Goklani , Krish Narendra , Neeraj Nayak

{"title":"Real-time system strength estimation using PMU data for modern grids with high IBR penetration","authors":"Hemantkumar Goklani , Krish Narendra , Neeraj Nayak","doi":"10.1016/j.epsr.2025.112199","DOIUrl":"10.1016/j.epsr.2025.112199","url":null,"abstract":"<div><div>With the increasing penetration of Inverter-Based Resources (IBRs) in power grids, real-time estimation of system strength has become a critical requirement for system operators to ensure grid stability and reliability. This paper introduces a robust method for system strength estimation using Phasor Measurement Unit (PMU) data, eliminating the need for model-based information. The proposed approach leverages Thevenin equivalent parameters to evaluate system strength at a specific bus. To address the phase angle drift in voltage and current measurements caused by continuous system frequency variations, corrections are applied, followed by synchronization of three consecutive phasor measurements to a common reference frame. These synchronized measurements are used to compute Thevenin equivalent parameters. Key features of the proposed method include a novel directional detection algorithm that addresses the impact of power flow directions on system strength estimation, ensuring accurate real-time evaluation. Unlike previously published literature, which primarily focused on system strength estimation at load buses, this method provides a comprehensive approach applicable across various operating scenarios. Additional enhancements, such as outlier removal through advanced filtering techniques, further improve the robustness and practical applicability of the approach. Validation using actual field PMU data from 161 kV, 275 kV and 500 kV systems demonstrates its effectiveness, while integration into a Wide Area Monitoring System (WAMS) platform underscores its readiness for operational use. Results from simulations and field data confirm the reliability and accuracy of the method for real-time applications in modern grids.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112199"},"PeriodicalIF":4.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing uncertainty management in multi-area asynchronous grids via HVDC: A distributionally robust chance constrained unit commitment approach 通过HVDC增强多区域异步电网的不确定性管理：一种分布式鲁棒机会约束单元承诺方法

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-18 DOI: 10.1016/j.epsr.2025.112255

Danyang Xu , Zhigang Wu

{"title":"Enhancing uncertainty management in multi-area asynchronous grids via HVDC: A distributionally robust chance constrained unit commitment approach","authors":"Danyang Xu , Zhigang Wu","doi":"10.1016/j.epsr.2025.112255","DOIUrl":"10.1016/j.epsr.2025.112255","url":null,"abstract":"<div><div>The advancement of high voltage direct current (HVDC) transmission technology is accelerating the evolution of large-scale power systems toward multi-area asynchronous grid (MAG) architectures. This paper proposes a unit commitment framework tailored to reserve sharing in MAGs, aiming to fully leverage the flexibility of HVDC systems to address the uncertainties introduced by renewable energy sources. The scheduling approach incorporates a response mechanism based on affine strategy for both HVDC links and conventional generator units, while a curtailment policy is introduced to enhance controllability over renewable uncertainty. At the modeling level, a distributionally robust chance constrained (DRCC) formulation is employed to reformulate uncertainty constraints, utilizing a Gaussian-based center assumption and the Wasserstein distance to characterize forecast errors of renewable generation. The proposed method is validated through simulations on a modified three-area 18-bus system, a four-area partitioned IEEE 118-bus system, and a provincial-level power grid in China. Results demonstrate the effectiveness of the approach in mitigating renewable fluctuations, enabling inter-area reserve sharing, and enhancing both the security and economic efficiency of system operations under the MAG framework.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112255"},"PeriodicalIF":4.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Residual guided and cross-level feature interaction network for substation anomaly detection 基于残差引导和跨级特征交互网络的变电站异常检测

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112189

Hang Sun , Zhenduo Wang , Yuelin Zheng , Mei Yu , Tian Wu , Lei Fang

{"title":"Residual guided and cross-level feature interaction network for substation anomaly detection","authors":"Hang Sun , Zhenduo Wang , Yuelin Zheng , Mei Yu , Tian Wu , Lei Fang","doi":"10.1016/j.epsr.2025.112189","DOIUrl":"10.1016/j.epsr.2025.112189","url":null,"abstract":"<div><div>Recently, YOLO-based object detection methods have achieved remarkable results in substation anomaly detection. However, existing detection methods lack target information with different scales of receptive fields during Backbone feature extraction, hindering the effective discrimination between targets and background amid complex background interference. Moreover, as network depth increases, the transmission of features from the backbone to the detection head is often subjected to information dilution, resulting in the inadequate utilization of shallow details and ultimately diminishing detection accuracy. To address these issues, we propose a Residual Guided and Cross-level Feature Interaction Network (RGCIN). Specifically, We propose a Residual Guided Feature Enhancement (RGFE) module that selectively amplifies multi-scale receptive field features by leveraging residual information, thereby augmenting the network’s capacity to accurately distinguish foreground objects. Furthermore, a Cross-level Feature Interaction Fusion (CFIF) module is designed to effectively integrate shallow texture features with deep semantic information through correlation-based queries among hierarchical features, thereby improving detection performance. Experimental results on the substation anomaly image dataset demonstrate that the proposed algorithm outperforms 14 state-of-the-art object detection methods. The code is released available at: <span><span>https://github.com/wzd-l/RGCIN</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112189"},"PeriodicalIF":4.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An optimal power management strategy for enhancing fuel economy in fuel cell-battery hybrid electric vehicles 提高燃料电池混合动力汽车燃油经济性的最优电源管理策略

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112256

Shelma George, Rajeev T

{"title":"An optimal power management strategy for enhancing fuel economy in fuel cell-battery hybrid electric vehicles","authors":"Shelma George, Rajeev T","doi":"10.1016/j.epsr.2025.112256","DOIUrl":"10.1016/j.epsr.2025.112256","url":null,"abstract":"<div><div>Fuel Cell-Battery Hybrid Electric Vehicles (FCBHEVs) are emerging as a promising solution for sustainable transportation, offering high efficiency and zero tailpipe emissions. Optimizing power distribution between energy sources is essential for improving fuel economy. This paper introduces a hybrid approach that combines optimization techniques with machine learning (ML). It uses LSTM networks for real-time estimation of key battery states, such as State of Charge (SoC), enabling informed decision-making. Additionally, an advanced optimisation layer utilises a weighted multi-objective cost function to minimise system costs and weights while maintaining power balance and operational constraints. To further guide energy sharing between the battery and fuel cell, a Hybrid Storage Participation Index (HSPI) is introduced, quantifying the relative contribution of each energy source over a drive cycle. The HSPI approach aims to improve fuel economy and reduce fuel consumption per 100 km, and also dynamically allocates power demand between the fuel cell and the battery according to real-time operating conditions. The results across various drive cycles demonstrate significant improvements in fuel economy, with reductions of up to 70–73 % compared to conventional rule-based strategies. Furthermore, the proposed strategy enhances vehicle fuel efficiency—measured in litres per 100 km—ensuring better energy utilization and extended system longevity.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112256"},"PeriodicalIF":4.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LitePowerCD: A lightweight anomalous change detection model for power transmission and transformation scenarios LitePowerCD：用于电力传输和转换场景的轻量级异常变化检测模型

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112194

Chengming Song, Ruirong Yang, Zhendong Cui

{"title":"LitePowerCD: A lightweight anomalous change detection model for power transmission and transformation scenarios","authors":"Chengming Song, Ruirong Yang, Zhendong Cui","doi":"10.1016/j.epsr.2025.112194","DOIUrl":"10.1016/j.epsr.2025.112194","url":null,"abstract":"<div><div>Efficient and reliable detection of anomalous changes in electrical equipment is crucial for power grid safety. To address this, the LitePowerCD model is proposed for anomalous change detection(ACD) in power scenarios, using a siamese network with a lightweight EfficientNet_B2 backbone to efficiently extract dual-phase power scene features. Next, an efficient feature fusion module, Shallow Feature Fusion Module (SFFM), is designed. By introducing dilated convolutions and the Squeeze-and-Excitation module, the receptive field is expanded, and channel selection is enhanced, improving detection performance on small-scale change regions. Then, feature reconstruction is achieved through upsampling and skip connection, which retain and strengthen anomalous edge details and regional information. Moreover, a pixel-level classifier is improved to make more precise judgments, thereby reducing the false positive rate. Furthermore, a dataset of substation equipment images, covering various scenes, seasons, and lighting conditions, is constructed to support power equipment ACD research. Finally, experiments are conducted on the proposed model. Experimental results show that the proposed approach surpasses the previous state-of-the-art model by 1.07% on the F1-score, achieving 93.21%, while reducing the model size to only 0.23 MB (1/16 of prior methods) and significantly lowering computational cost, demonstrating a superior balance between efficiency and accuracy.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112194"},"PeriodicalIF":4.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancements to Terminal Duality-based models for three-phase multi-limb multi-winding transformers 基于终端二元性的三相多肢多绕组变压器模型的改进

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112204

Meysam Ahmadi, Ali Dehkordi, Yi Zhang

引用次数: 0

Calculation of lightning-induced voltages on a large-scale distribution network using the JMarti model 基于JMarti模型的大型配电网雷击感应电压计算

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112232

Alberto De Conti , Osis E.S. Leal

引用次数: 0

Identification and Localization of False Data Injection Attacks in Smart Grids Using Graph Fourier Transform 基于图傅里叶变换的智能电网虚假数据注入攻击识别与定位

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112238

Kamal Singh, Sailaja Kumari M.

{"title":"Identification and Localization of False Data Injection Attacks in Smart Grids Using Graph Fourier Transform","authors":"Kamal Singh, Sailaja Kumari M.","doi":"10.1016/j.epsr.2025.112238","DOIUrl":"10.1016/j.epsr.2025.112238","url":null,"abstract":"<div><div>The increasing digitalization of the energy sector has enhanced efficiency in energy transfer and utilization but has also exposed smart grid operations to significant cybersecurity threats, particularly False Data Injection (FDI) attacks. These attacks manipulate measurement data within communication channels to compromise power system state estimation, thus disturbing grid reliability and security. This research proposes a detection approach based on the Graph Fourier Transform (GFT). The GFT-based method not only detects the presence of FDI attacks but also identifies the targeted buses within the power grid. The methodology uses the Degree Centrality technique to identify critical buses in the system as potential targets for FDI attacks, followed by the simulation of such attacks on these buses. The performance of the proposed approach is validated using MATLAB simulations on the IEEE 9-bus, 14-bus, 30-bus, and 118-bus system. To validate the results obtained with the proposed method, the Euclidean distance detector is also applied. The results demonstrate that the proposed GFT-based approach effectively detects and localizes FDI attacks across varying intensities, including weak, medium, and strong attacks. These findings highlight the potential of the GFT method as a robust solution for enhancing the cybersecurity of modern power systems.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112238"},"PeriodicalIF":4.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SPICE implementation of multiconductor transmission line model of transformer winding for very fast transient analysis SPICE实现了变压器绕组的多导体传输线模型，用于非常快速的暂态分析

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112207

Amir Ali Kaabi Nejadian , Hamed Moradi Tavasani , Manuja Gunawardana , Waldemar Ziomek , Behzad Kordi

引用次数: 0

Integrated theoretical and simulation analysis of Inductive FCL impact on circuit breaker RRRV and TRV characteristics 电感式FCL对断路器RRRV和TRV特性影响的综合理论与仿真分析

IF 4.2 3区工程技术

Electric Power Systems Research Pub Date : 2025-09-17 DOI: 10.1016/j.epsr.2025.112233

Mohammad Reza Barzegar-Bafrooei , Jamal Dehghani Ashkezari , Mohammad-Hadi Zare

{"title":"Integrated theoretical and simulation analysis of Inductive FCL impact on circuit breaker RRRV and TRV characteristics","authors":"Mohammad Reza Barzegar-Bafrooei , Jamal Dehghani Ashkezari , Mohammad-Hadi Zare","doi":"10.1016/j.epsr.2025.112233","DOIUrl":"10.1016/j.epsr.2025.112233","url":null,"abstract":"<div><div>Fault Current Limiters (FCLs) are crucial for curtailing short-circuit currents in power systems. Their integration, however, profoundly influences the Transient Recovery Voltage (TRV) and Rate of Rise of Recovery Voltage (RRRV) across Circuit Breakers (CBs), directly affecting their fault interruption performance. This paper presents a comprehensive investigation into the theoretical implications of Inductive FCL (IFCL) on both RRRV and TRV using an improved model that more precisely captures its inherent distributed capacitance characteristics. The investigation further extends to comprehensive simulation analyses of both RRRV and TRV, examining terminal faults and Short-Line Faults (SLFs) under diverse system arrangements, including IFCL connections on both source and load sides of the CB, and varying Current Limiting Factors (CLFs). Simulations conducted on a 20-kV distribution feeder and an IFCL model closely resembling the South Korean hybrid FCL under three-phase faults identify the most severe transient conditions affecting the CB. The findings provide valuable guidance for the robust design and strategic implementation of IFCLs, ensuring dependable CB operation and effective fault current breaking.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"251 ","pages":"Article 112233"},"PeriodicalIF":4.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0