Electric Power Systems Research最新文献_第10页

Incremental cost-consistent partitioning and power allocation strategy for wind-storage clusters in wind power fluctuation mitigation 缓解风电波动的蓄风集群增量成本一致划分与功率分配策略

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-23 DOI: 10.1016/j.epsr.2025.111958

Yang Yu, Yixuan Guo, Tingyan Lv, Zhongjing Wang, Yan Wang

{"title":"Incremental cost-consistent partitioning and power allocation strategy for wind-storage clusters in wind power fluctuation mitigation","authors":"Yang Yu, Yixuan Guo, Tingyan Lv, Zhongjing Wang, Yan Wang","doi":"10.1016/j.epsr.2025.111958","DOIUrl":"10.1016/j.epsr.2025.111958","url":null,"abstract":"<div><div>To effectively mitigate wind power fluctuations and boost the economic performance of Distributed Wind Storage (DWS) systems, this paper proposes a strategy for wind-storage cluster partitioning and power optimization that ensures incremental cost consistency. First, an improved sliding average method is developed to address wind power volatility, incorporating adaptive sliding windows, weighted moving averages, and short-term forecasts to optimize grid integration commands. Next, a three-dimensional clustering metric reflecting the system’s volatility-smoothing characteristics is constructed, and a large-scale DWS clustering model is developed using a data-driven improved K-means algorithm. Finally, to ensure incremental cost consistency among individual DWS units, cluster output is optimized using the equal incremental rate criterion and a multi-agent consensus algorithm, achieving economically efficient power distribution. Simulation results show that the proposed method reduces power volatility and improves the operational economic efficiency of DWS systems.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111958"},"PeriodicalIF":3.3,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338657","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

Deep learning empowering gas monitoring in GIL pipeline corridor: super-resolution reconstruction of gas leakage distribution data and optimization of sensor placement 深度学习增强GIL管道走廊气体监测：气体泄漏分布数据的超分辨率重建和传感器放置的优化

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-23 DOI: 10.1016/j.epsr.2025.111956

Ma Aiqing , Wang Kexin , Wu Xinyu , He Xing

{"title":"Deep learning empowering gas monitoring in GIL pipeline corridor: super-resolution reconstruction of gas leakage distribution data and optimization of sensor placement","authors":"Ma Aiqing , Wang Kexin , Wu Xinyu , He Xing","doi":"10.1016/j.epsr.2025.111956","DOIUrl":"10.1016/j.epsr.2025.111956","url":null,"abstract":"<div><div>In Gas Insulated Metal Enclosed Transmission Lines (GIL), which are a unique environment with complex spatial structures, extensive spanning distances and enclosed spaces, the prevailing monitoring practices for Sulphur Hexafluoride (SF<sub>6</sub>) concentration depend on a limited number of sensors. The gas concentration distribution is not readily visualized, and the monitoring lacks intuitive visibility. Thus, we employed computational fluid dynamics (CFD) to simulate typical gas leakage scenarios and constructed a digital twin model that accurately reflects the physical state of GIL systems, generating high-precision datasets. We propose a U-net-based super-resolution reconstruction (SRR) method capable of reconstruct high-resolution 3D gas concentration distribution from limited low-resolution sensor data. The investigation encompasses the impact of varying sensor numbers and distributions on the reconstruction outcomes. The findings indicate that enhancing the number of sensors can improve the reconstruction accuracy, with uniform sensor distribution yielding better results than non-uniform. The proposed method facilitates the reconstruction of sparsely distributed monitoring data of gas concentration into a high-density distribution and an intuitively visible monitoring image. It provides data support for optimizing the distribution of sensors in the pipeline corridor and the safe evacuation paths of the personnel in case of emergencies.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111956"},"PeriodicalIF":3.3,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338658","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

Transmission line pilot relaying scheme based on superimposed DC decaying component energy 基于直流衰减分量能量叠加的输电线路导频继电方案

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-23 DOI: 10.1016/j.epsr.2025.111928

Sandeep Biswal

引用次数: 0

Enhancing resilience of inverter-based resources: Adaptive neural network control for virtual synchronous generator damping under grid impedance uncertainty 增强基于逆变器资源的弹性：电网阻抗不确定性下虚拟同步发电机阻尼的自适应神经网络控制

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-23 DOI: 10.1016/j.epsr.2025.111893

Lydia Asare Bediako, Ali Hosseinipour, Javad Khazaei

{"title":"Enhancing resilience of inverter-based resources: Adaptive neural network control for virtual synchronous generator damping under grid impedance uncertainty","authors":"Lydia Asare Bediako, Ali Hosseinipour, Javad Khazaei","doi":"10.1016/j.epsr.2025.111893","DOIUrl":"10.1016/j.epsr.2025.111893","url":null,"abstract":"<div><div>The increasing integration of renewable energy sources (RESs) into the power grid has led to the widespread replacement of synchronous generators (SGs) with inverter-based resources (IBRs). Unlike SGs, inverters lack inherent inertia, which is critical for frequency stability. Virtual synchronous generator (VSG) control has emerged as a promising solution by emulating SG dynamics in inverter control. However, conventional VSGs rely on fixed damping and inertia parameters designed for specific operating conditions <span><math><mo>−</mo></math></span> typically assuming a fixed grid strength. These assumptions often fail when operating conditions change and the impedance of the grid varies, leading to degraded performance or even instability. To address these limitations, this paper proposes a data-driven neural network (NN)-based damping controller that replaces fixed damping terms with adaptive measurement-driven damping. The NN is trained offline across a wide range of short-circuit ratios (SCRs) and <span><math><mrow><msub><mrow><mi>X</mi></mrow><mrow><mi>g</mi></mrow></msub><mo>/</mo><msub><mrow><mi>R</mi></mrow><mrow><mi>g</mi></mrow></msub></mrow></math></span> impedance profiles, allowing it to generalize across operating points without requiring online re-tuning. A Lyapunov-based input-to-state stability (ISS) analysis is presented to guarantee system stability under bounded disturbances, even in the absence of an explicit transfer function. Finally, real-time simulations validate the proposed controller’s damping performance under both strong and weak grid conditions, and across different impedance types.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111893"},"PeriodicalIF":3.3,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338654","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

Medium-term scheduling of cascade hydropower systems incorporating ecological constraints considering spawning demand of drift-spawning fishes 考虑漂卵鱼类产卵需求的生态约束梯级水电系统中期调度

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-22 DOI: 10.1016/j.epsr.2025.111951

Yaning Zhang , Yingmin Zhang , Yikui Liu , Lei Wu , Xiangbang Chen

{"title":"Medium-term scheduling of cascade hydropower systems incorporating ecological constraints considering spawning demand of drift-spawning fishes","authors":"Yaning Zhang , Yingmin Zhang , Yikui Liu , Lei Wu , Xiangbang Chen","doi":"10.1016/j.epsr.2025.111951","DOIUrl":"10.1016/j.epsr.2025.111951","url":null,"abstract":"<div><div>As globally recognized flexible and efficient green and clean energy, the development and utilization of hydropower have progressed over the past few decades. Although the scheduling of hydropower stations is relatively extensively studied, most of the existing models are economic benefit orientated, namely simply pursuing the maximization of the benefit or the energy generation, while ignoring the negative impact on the ecological environment of the downstream. In fact, the spawning scale of drift-spawning fishes during the reproductive period is highly susceptible to flow rising processes, i.e., water level increasing process. The scheduling of hydropower stations can lead to changes in river water flow patterns that may severely affect the spawning activity of drift-spawning fishes. To this end, this paper proposes a cascade hydropower scheduling model with ecological constraints that coordinates the water discharge to meet ecological requirements, while pursuing the maximization of power generation. The ecological constraints can compensate for the negative impacts on drift-spawning fishes during the spawning period. Besides, the nonlinear constraints representing the operational characteristics of hydropower stations and hydropower units are linearized, rendering a mixed-integer linear programming (MILP) based scheduling model to facilitate the solving process. The case study with an actual cascade hydropower system located in a river basin in United States show that the proposed ecological constraints can effectively enforce flow rising processes, while the cost of power generation reduction is very limited. In addition, the computational burden accompanied with incorporating ecological constraints are acceptable for medium-term scheduling of cascade hydropower systems.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111951"},"PeriodicalIF":3.3,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338674","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

A novel flexible fault current limiter for DC distribution applications 一种用于直流配电的新型柔性故障限流器

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-21 DOI: 10.1016/j.epsr.2025.111919

Feng Zheng , Fan Yang , Baojin Liu , Hao Zhong , Yuncong Huang , Ning Liang

{"title":"A novel flexible fault current limiter for DC distribution applications","authors":"Feng Zheng , Fan Yang , Baojin Liu , Hao Zhong , Yuncong Huang , Ning Liang","doi":"10.1016/j.epsr.2025.111919","DOIUrl":"10.1016/j.epsr.2025.111919","url":null,"abstract":"<div><div>This paper proposes a novel fault current limiter(NFCL) topology tailored for DC distribution systems, aiming to improve fault response speed, system protection coordination, and recovery capability. The NFCL integrates a fast-acting solid-state switching path and an energy-absorbing branch, forming a coordinated fault control mechanism that enables both transient ride-through and permanent fault isolation. A hybrid protection strategy, combining voltage-differential detection and directional overcurrent identification, ensures selective response and enhances protection flexibility. Compared with conventional limiter topologies, the proposed NFCL achieves over 85 % reduction in peak fault current within 0.6 ms, significantly alleviating stress on DC circuit breakers. Experimental tests based on a 10 kV prototype confirm the NFCL's fast dynamic performance and practical applicability. These results demonstrate that the proposed NFCL offers a technically innovative and cost-effective approach to enhancing the reliability and resilience of future DC distribution networks.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111919"},"PeriodicalIF":3.3,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330451","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

A fault detection method based on active injection using dual active bridge converter in photovoltaic DC integration system 基于双有源桥式变换器的光伏直流集成系统主动注入故障检测方法

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-21 DOI: 10.1016/j.epsr.2025.111926

Jiayi Yang, Guobing Song, Ruidong Xu, Zhongxue Chang, Yiming Ren

{"title":"A fault detection method based on active injection using dual active bridge converter in photovoltaic DC integration system","authors":"Jiayi Yang, Guobing Song, Ruidong Xu, Zhongxue Chang, Yiming Ren","doi":"10.1016/j.epsr.2025.111926","DOIUrl":"10.1016/j.epsr.2025.111926","url":null,"abstract":"<div><div>Fault characteristics in photovoltaic DC integration systems exhibit short durations, making traditional protection principles less effective and unreliable. To address this challenge, a control-protection coordinated fault detection strategy based on active dual-frequency signal injection is proposed. By modifying the phase shift modulation of DAB converters, two specific frequency signals are injected with flexible control over frequency, amplitude, and duration according to system requirements. The fault characteristics under injected signals are subsequently analyzed, revealing that for healthy lines, the calculated capacitance closely matches the actual values, while for faulty lines, it consistently exceeds the true value. Based on this observation, a fault line identification method utilizing the Relative Capacitance Deviation (RCD) algorithm and fluctuation criteria is developed. Furthermore, a high-precision fault location method is introduced, employing parameter identification combined with a nonlinear interior-point optimization algorithm. The proposed method requires no communication or prior knowledge of line parameters, and demonstrates robust performance under transient resistance up to 200 Ω and noise levels up to 20 dB. Simulation results validate the effectiveness of the proposed method.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111926"},"PeriodicalIF":3.3,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330452","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

Multiscale feature decoupling via VMD and dual-channel networks for dissolved gas prediction in transformers 基于VMD和双通道网络的多尺度特征解耦变压器溶解气体预测

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-20 DOI: 10.1016/j.epsr.2025.111911

Haijun Xiong , Yahan Li , Yiji Meng , Junping Wang , Yutian Wang

{"title":"Multiscale feature decoupling via VMD and dual-channel networks for dissolved gas prediction in transformers","authors":"Haijun Xiong , Yahan Li , Yiji Meng , Junping Wang , Yutian Wang","doi":"10.1016/j.epsr.2025.111911","DOIUrl":"10.1016/j.epsr.2025.111911","url":null,"abstract":"<div><div>To address the impact of the non-linearity and non-stationarity of transformer oil dissolved gas concentration sequences on prediction accuracy, a multi-scale hybrid prediction framework based on VMD optimized by PSO and deep learning is proposed. By introducing a sliding average pooling operation method, the subsequences obtained from VMD decomposition are further decoupled into long-term trend and residual components, establishing a dual-channel heterogeneous modeling system. BiGRU is employed to capture the trend component, while TCN integrated with a multi-head self-attention mechanism is designed to enhance the dynamic representation capability of key time points in the residual component, enabling the collaborative optimization of multi-scale features. Experimental results show that the proposed model outperforms traditional methods in predicting dissolved gas <span><math><mrow><msub><mrow><mi>C</mi></mrow><mrow><mn>2</mn></mrow></msub><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></mrow></math></span> in transformer oil, with a reduction in RMSE by 0.2918, a decrease in MAPE by 23.78%, and an improvement in <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> by 37.25%. Predictions of other gas components, such as <span><math><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub></math></span> and total hydrocarbons, further demonstrate that the model exhibits strong generalization performance across various gas components.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111911"},"PeriodicalIF":3.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322124","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

Fault detection, classification and localization in HV power transmission lines using ANN 基于神经网络的高压输电线路故障检测、分类与定位

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-20 DOI: 10.1016/j.epsr.2025.111927

Živko Sokolović , Mileta Žarković

{"title":"Fault detection, classification and localization in HV power transmission lines using ANN","authors":"Živko Sokolović , Mileta Žarković","doi":"10.1016/j.epsr.2025.111927","DOIUrl":"10.1016/j.epsr.2025.111927","url":null,"abstract":"<div><div>Power transmission line is key equipment in secure and reliable power flow in each power system. To arise reliability and security of overhead power lines, different types of failures should be simulated to minimize their impact and to detect and resolve them as quickly as possible. The objective of this paper is to provide an accurate method for detection, classification and localization of faults occurring in power transmission lines using Artificial Neural Network (ANN). Power transmission system was modelled in DIgSILENT PowerFactory, simulating both normal and fault scenarios. Three types of faults were considered for simulation: single-phase-to-ground fault, two-phase short circuit, and three-phase short circuit. Each fault was simulated across the 110 kV power lines with a resolution of 5 %. In addition to the fault scenarios, normal scenario was carried out using a load flow analysis, where the system’s load was varied. Voltage and current data from these simulations were utilized to train and test the ANN model. Principal Component Analysis (PCA) was applied for dimensionality reduction, improving the efficiency and performance of the ANN model. The proposed model achieved an accuracy of 100 % in detecting fault types, a fault classification accuracy of 94 % for identifying the fault line, and a mean absolute error (MAE) of 1.15 in pinpointing the exact fault position. These results demonstrate the model's effectiveness in accurately identifying and localizing faults in power transmission lines, significantly contributing to the reliability and stability of power grid operations.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111927"},"PeriodicalIF":3.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322125","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

Sub-synchronous oscillation suppression strategy in wind power systems with DFIGs based on improved deep reinforcement learning algorithms 基于改进深度强化学习算法的DFIGs风力发电系统次同步振荡抑制策略

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-06-20 DOI: 10.1016/j.epsr.2025.111959

Ge Liu, Jun Liu, Andong Liu

{"title":"Sub-synchronous oscillation suppression strategy in wind power systems with DFIGs based on improved deep reinforcement learning algorithms","authors":"Ge Liu, Jun Liu, Andong Liu","doi":"10.1016/j.epsr.2025.111959","DOIUrl":"10.1016/j.epsr.2025.111959","url":null,"abstract":"<div><div>The characteristics of sub-synchronous oscillations (SSOs) in Doubly-Fed Induction Generator (DFIG)-based wind farms connected to series-compensated grids are influenced by various factors such as operating conditions, control parameters, and external environments. The complex and variable interaction between the wind farm and the grid leads to diverse oscillation patterns in interconnected systems. This study aims to develop an adaptive sub-synchronous damping controller (SSDC) that enhances system damping and operational stability under dynamic real-world conditions. First, a joint distribution adaptive transfer learning method (JDA-TFL) is employed to locate oscillation sources under multiple operating conditions. The optimal location of the SSDC at the oscillation source significantly reduces control costs. Second, the SSDC design problem is redefined as a Markov Decision Process (MDP), with the sensitivity of measured electrical parameters to system stability being embedded in the reward function construction. Third, the twin delayed deep deterministic policy gradients algorithm incorporating an exploration network (EMTD3) is utilized to generate optimal control signals. The encouragement mechanism improves the model's ability to explore the optimal strategy. Additionally, a multi-experience probability replay strategy is employed to accelerate training convergence. Finally, the effectiveness and robustness of the proposed method are validated through simulations across multiple scenarios. The proposed method offers a novel solution for mitigating SSOs in wind power systems, with significant theoretical and practical implications for enhancing the reliability of these systems.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"248 ","pages":"Article 111959"},"PeriodicalIF":3.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322126","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