International Journal of Electrical Power & Energy Systems最新文献

{"title":"Aggregate model of large-scale parallel grid-forming inverters for converter-driven stability analysis","authors":"Naiara Goñi ,&nbsp;Javier Marcos ,&nbsp;Miguel García ,&nbsp;Alberto García ,&nbsp;Luis Marroyo ,&nbsp;Guillermo Bautista","doi":"10.1016/j.ijepes.2026.111899","DOIUrl":"10.1016/j.ijepes.2026.111899","url":null,"abstract":"<div><div>The increasing share of renewable energy plants is transforming power systems into inverter-dominated grids with low inertia and weak-grid conditions. Grid-Forming (GFM) inverters can address these challenges by emulating the dynamics of synchronous generators; however, large-scale GFM plants introduce complex multi-inverter and grid interactions that are not yet fully understood. This paper proposes a reduced order but high-fidelity aggregate model for large-scale GFM plants, capable of representing both plant-to-grid and internal inverter-to-inverter resonances while considering parameter dispersion among inverters for converter-driven stability analysis. The model is specifically designed for the planning and diagnosis of resonances occurring at the normal operating point in grids with a high penetration of GFM resources. Cross-validation against detailed averaged electromagnetic transient simulations confirm that the proposed 2-AggGFM model accurately reproduces the critical dynamic behavior of multi-inverter plants, including resonance excitability from grid and inverter perturbations. These results demonstrate its effectiveness as a practical and efficient model for converter-driven stability assessment and control-oriented design in large-scale inverter-based grids.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111899"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854116","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}

{"title":"Joint community detection and game-theoretic coordination for optimal parallel power system restoration planning","authors":"Tarique Aziz ,&nbsp;Muhammad Waseem ,&nbsp;Qamar ud Din Memon ,&nbsp;Noor Muhammad Memon","doi":"10.1016/j.ijepes.2026.111890","DOIUrl":"10.1016/j.ijepes.2026.111890","url":null,"abstract":"<div><div>Parallel power system restoration (PPSR) is a quick and efficient way to restore power after a blackout. The main goals of the PPSR are to divide the blackout system into smaller sections, identify connections between these sections, reduce the time needed for restoration, and supply as much load as possible. This paper presents a sectionalizing-based decision-making strategy for PPSR using label propagation algorithm (LPA) and cooperative game theory. Firstly, this paper introduces an improved LPA based on complex network theory to detect groups within the power system for PPSR. The proposed LPA is designed based on the influence of bus labels and the node influence index to address the sectionalizing problem. This provides a clear ranking of nodes across the network, helping to prevent label switching issues seen in traditional LPAs. Secondly, a game theory-based strategy is presented which provides the cooperation between buses and subsystems by evaluating the Shapley value of buses. The method makes recommendations for cooperated subsystems by calculating the real-time Shapley value of the buses. This proposes the dynamical interaction between buses and subsystems with the purpose of improving system restoration stability and efficiency based on a novel cooperative game strategy. Finally, an optimization model for determining the optimal sectionalizing schemes is developed to minimize the cut-sets (i.e., tie-lines between the subsystems) and to minimize the real power exchange (i.e., power flow) between subsystems. The proposed optimization model considers the system topology as well as the operating characteristics (i.e., power flow) before the pre-blackout system. Furthermore, the sectionalizing constraints is applied in the proposed strategy for feasibility verification. The proposed LPA and cooperative game theory-based sectionalizing strategy (SS) is suitable for quickly finding a community division (i.e., optimal sectionalizing scheme) solution after a power system blackout. Finally, case studies on the modified IEEE 9-bus, 39-bus, and 118-bus power systems are performed. The simulation results verify that the proposed strategy can successfully restore the power system and determine the efficient sectionalizing scheme.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111890"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854016","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}

{"title":"Feedforward-feedback compound control to improve dynamic and steady-state performance of grid-forming virtual synchronous generator","authors":"Yaqian Yang ,&nbsp;Xiuliang Chen ,&nbsp;Mengyuan Pan ,&nbsp;Shijie Wu ,&nbsp;Chang Li","doi":"10.1016/j.ijepes.2026.111905","DOIUrl":"10.1016/j.ijepes.2026.111905","url":null,"abstract":"<div><div>Grid forming virtual synchronous generators have been widely adopted and are equipped with active grid support capability. However, the dynamic overshoot and steady state deviation may be introduced by the disturbance from active power command and grid voltage and frequency in the case of limited damping as well as coupling between virtual damping and frequency regulator coefficient. This article proposes a compound control method based on the active power deviation feedforward and active power positive feedback control theory, which suppresses power oscillation and eliminate steady state deviation. Furthermore, the parameter design and system stability of the proposed control are illustrated by the active power response. Finally, the effectiveness of the proposed compound control and the corresponding theoretical analysis are verified through the hardware-in-the-loop results.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"178 ","pages":"Article 111905"},"PeriodicalIF":5.0,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147854113","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}

{"title":"Multi-modal learning from image-derived graphical construction to improve ultra-short-term photovoltaic power forecasting","authors":"Yunan Jiang,&nbsp;Haixiang Zang,&nbsp;Jingxuan Liu,&nbsp;Lilin Cheng,&nbsp;Guoqiang Sun,&nbsp;Zhinong Wei","doi":"10.1016/j.ijepes.2026.111817","DOIUrl":"10.1016/j.ijepes.2026.111817","url":null,"abstract":"<div><div>Solar energy plays a crucial role in addressing global climate change and energy crisis. However, the high volatility and instability of photovoltaic (PV) power generation, driven by complex cloud motion, pose significant challenges for grid integration. Accurate PV power forecasting with the assistance of sky images is key to managing the variation. Few existing researches have comprehensively explored inter-image coupling features that could capture complex cloud-driven dynamic and enhance forecasting precision. Consequently, this paper proposes a novel ultra-short-term PV power forecasting framework based on multi-modal learning from image-derived graphical construction. Firstly, this research develops super-pixel segmentation to overcome the limitations on capturing complex pixel relationships and enhance boundary-texture recognition. Subsequently, this method proposes a graph structure to extract global coupling features across sky images chunks and historical data, then applies Graph Sample and Aggregate network to learn embedded representations of graph. Finally, a cross-modal feature synergy fusion module based on multi-headed attention mechanism is proposed to explore coupling correlations between different modalities that enable global interaction and redundancy elimination. Experimental results show that the proposed method achieves a normalized root mean square error (nRMSE) of 6.1% in 5-min-ahead forecasting. Compared to eleven mainstream models, the proposed method surpasses them across various performance indicators, particularly under cloudy and rapidly fluctuating conditions. This work expands the research on PV power forecasting and provides vital numerical support for achieving stable and efficient grid integration of PV power generation.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111817"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147602611","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}

{"title":"MAVL-DRL: Multimodal foundation using multi-agent deep reinforcement learning for intelligent predictive maintenance of wind turbine energy systems","authors":"Amreen Batool ,&nbsp;Yong-Woon Kim ,&nbsp;Yung-Cheol Byun","doi":"10.1016/j.ijepes.2026.111781","DOIUrl":"10.1016/j.ijepes.2026.111781","url":null,"abstract":"<div><div>Wind energy systems are a critical component of global renewable power generation, yet their maintenance remains technically complex and economically demanding, with operation and maintenance (O&amp;M) activities accounting for 20%–35% of the levelized cost of energy. Existing predictive maintenance approaches face three major limitations: reliance on single data modalities, isolated single-agent decision frameworks, and static supervised learning models that struggle to adapt to evolving operational conditions. This paper proposes a Multi-Agent Vision–Language Deep Reinforcement Learning (MAVL-DRL) framework that unifies heterogeneous information sources for coordinated predictive maintenance. The system employs Temporal Convolutional Networks (TCNs) for Supervisory Control and Data Acquisition (SCADA) time-series signals, Distillation with No Labels Version 2 (DINOv2) vision transformers for drone-based blade inspection, Bidirectional Encoder Representations from Transformers (BERT) models for interpreting maintenance logs, and Multi-Layer Perceptrons (MLPs) for meteorological data processing. A cross-attention fusion mechanism learns inter-modal dependencies to construct consistent state representations, which are utilized by a QMIX-based multi-agent reinforcement learning architecture enabling decentralized yet cooperative maintenance policies. Experiments conducted on a real-world 20-turbine offshore wind farm over a 365-day period demonstrate substantial improvements, including 98.3% system availability, only two annual failures (33% fewer than the best-performing baseline), a mean time between failures of 182.5 days, and a 30.8% faster decision response time of 1.8 h. These results position MAVL-DRL as a promising approach for next-generation intelligent predictive maintenance systems in renewable energy infrastructure.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111781"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147602795","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}

{"title":"Research on optimized control strategy for LCC-CLCC Receiving-End under different Degrees of Three-Phase fault conditions","authors":"Weiru Wang,&nbsp;Yuxuan Li,&nbsp;Tuo Wang,&nbsp;Yechun Xin,&nbsp;Guoqing Li,&nbsp;Hairun Guo","doi":"10.1016/j.ijepes.2026.111831","DOIUrl":"10.1016/j.ijepes.2026.111831","url":null,"abstract":"<div><div>Compared with traditional Line-Commutated Converters (LCCs), the Controllable Line-Commutated Converter (CLCC) exhibits a significantly enhanced immunity to commutation failures. To fully leverage this characteristic and further improve the system’s power transfer efficiency during faults, this paper analyzes the characteristics of the rectifier-side controller and the relationship between the CLCC’s reactive power and its firing angle as well as DC current in an LCC-CLCC system during a three-phase AC fault at the receiving end, so as to facilitate system regulation under fault conditions. Subsequently, a transient expression for the firing angle under fault conditions is derived to calculate its target adjustment value. Utilizing its controllable advantages, a control optimization method based on maximizing the firing angle elevation is proposed for mild AC faults at the receiving end. Furthermore, starting from the commutation area theory of the CLCC, the reasons for its strong immunity to commutation failures are revealed. An optimized Voltage Dependent Current Order Limiter (VDCOL) control strategy that compensates for DC current variations is proposed for severe AC faults at the receiving end. Both control strategies enhance AC voltage support and active power retention capability during faults and accelerate system recovery. Finally, the effectiveness of the proposed control strategies under three-phase short-circuit ground faults is verified through electromagnetic transient simulations using PSCAD/EMTDC.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111831"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147658475","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}

{"title":"Multi-timescale bi-level game optimization of microgrids incorporating unexpected load deviations","authors":"Xuming Chen,&nbsp;Le Liu,&nbsp;Xiaoning Kang","doi":"10.1016/j.ijepes.2026.111832","DOIUrl":"10.1016/j.ijepes.2026.111832","url":null,"abstract":"<div><div>The growing global environmental awareness and the increasing penetration of new energy vehicles and renewable energy have brought significant challenges to microgrid operation. In particular, maintaining economic efficiency in real-time operation under unexpected deviations has become a key challenge for microgrid scheduling. To address power fluctuations and economic deviations caused by unplanned vehicle trips and renewable energy, this paper proposes a bi-level game optimization strategy that incorporates unexpected deviations across multiple time scales. A Stackelberg–Shapley bi-level game framework is established, in which the integrated energy system operator (IESO), user load aggregator (ULA), and new energy vehicle load aggregator (NEVLA) act as the main participants. This framework is then embedded into a two-stage model predictive control (MPC) rolling scheduling model with feedback. In the real-time scheduling stage, the operator and load aggregators perform feedback correction and cooperative game interactions to mitigate power deviations and economic inefficiencies resulting from unplanned travel behaviors. Finally, the proposed strategy is validated through a case of electricity–thermal–hydrogen (ETH) integrated microgrid. The results demonstrate that the proposed method effectively reduces the load deviations and additional scheduling cost caused by unplanned vehicle trips, ensuring safe and economic operation of the system.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111832"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147658479","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}

{"title":"Blackstart strategies with grid forming offshore Type-IV wind turbines and BESS for effective system restoration","authors":"Mohamed Galeela ,&nbsp;Muhammad Fawad ,&nbsp;Diptargha Chakravorty ,&nbsp;Zahid Javid ,&nbsp;Chuanyue Li ,&nbsp;Jun Liang","doi":"10.1016/j.ijepes.2026.111820","DOIUrl":"10.1016/j.ijepes.2026.111820","url":null,"abstract":"<div><div>The increasing penetration of converter-interfaced generation motivates restoration strategies that can establish and regulate voltage and frequency during blackstart. This paper evaluates blackstart of an offshore wind farm using grid-forming (GFM) Type-IV wind turbines and battery energy storage systems (BESS), and compares four energization methods: (i) offshore diesel generator (DG) at the offshore PCC, (ii) offshore GFM-BESS at the offshore PCC, (iii) WT-assisted start using WT-integrated GFM-BESS followed by sequential turbine energization, and (iv) onshore GFM-BESS initiating restoration from the onshore side. Detailed EMT simulations in PSCAD follow explicit staged energization sequences of cables, transformers, and loads, enabling a consistent cross-method assessment of transient behavior. As a key contribution, the paper introduces an objective benchmarking framework based on measurable restoration indicators and applies it to quantify voltage and frequency containment and transient stress across methods. Results show that placing GFM capability offshore or at the turbine level yields the most robust restoration trajectories, including successful operation without offshore damping load, whereas DG-based and onshore-initiated strategies exhibit higher sensitivity to corridor charging and resonance-driven transients. The findings provide quantitative guidance for selecting practical blackstart architectures for offshore wind power plants.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111820"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147707036","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}

{"title":"Cloud-Edge coordinated economic scheduling for integrated Source-Grid-Load-Storage system considering demand response","authors":"Ping Yang,&nbsp;Tao Sun,&nbsp;Yingxuan Sun,&nbsp;Yuhang Wu,&nbsp;Xin Luo,&nbsp;Kaiyue Duan","doi":"10.1016/j.ijepes.2026.111838","DOIUrl":"10.1016/j.ijepes.2026.111838","url":null,"abstract":"<div><div>When coordinating adjustable loads in integrated source-grid-load-storage systems to participate in demand response programs, it is often challenging to simultaneously capture the complex dynamic regulation characteristics of industrial loads and overcome the bottlenecks of production data confidentiality. To address these issues, this paper proposes a cloud-edge coordinated economic scheduling method based on a physics-embedded neural network architecture. By structurally integrating the physical dynamics and operational constraints of heterogeneous devices into the neural network, this approach enables the efficient utilization of the system’s regulatory flexibility while ensuring data privacy. Specifically, this study encompasses three main contributions. First, a comprehensive scheduling model for the integrated source-grid-load-storage system is established, incorporating refined regulation models for two typical industrial loads. Second, a customized physics-embedded neural network is constructed, wherein the physical dynamics and operational constraints of heterogeneous devices are structurally encoded into specialized neurons. Third, a privacy-preserving cloud-edge collaborative scheduling algorithm is developed, in which distributed backpropagation and a gradient correction mechanism are constructed to jointly derive economic scheduling strategies while strictly preserving data privacy. Finally, multi-scenario simulations under varying production tasks, along with comprehensive comparisons and ablation analysis, are conducted to validate the effectiveness and practical advantages of the proposed method.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111838"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147707039","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}

{"title":"Mechanism analysis of VSG control SVG in suppressing mid-frequency resonance in doubly-fed wind farms","authors":"Jikai Chen ,&nbsp;Shuangshuang Yao ,&nbsp;Chuang Liu ,&nbsp;Jiansheng Ming ,&nbsp;Haibo Zhong","doi":"10.1016/j.ijepes.2026.111861","DOIUrl":"10.1016/j.ijepes.2026.111861","url":null,"abstract":"<div><div>Under weak grid conditions, the static var generator controlled by a virtual synchronous generator exhibits enhanced stability and can mitigate mid-frequency resonance in doubly-fed induction generator wind farms, which commonly occurs under grid-following control. To comparatively analyze the characteristics and mechanisms of the static var generator in improving resonance stability under single-loop and dual-loop virtual synchronous generator control modes, this study first establishes sequential impedance models for the static var generator and doubly-fed induction generator under different control modes. Subsequently, the impedance analysis method is employed to investigate the generation mechanism and key influencing factors of mid-frequency resonance. Furthermore, the dynamic performance and resonance suppression effectiveness of the static var generator under the virtual synchronous generator single-loop and dual-loop control modes are compared. Finally, simulation verification is conducted using the StarSim-HIL platform. The impedance analysis reveals that the grid-following static var generator introduces a negative damping region in the mid-frequency band, causing the system resonance. In contrast, the virtual synchronous generator control effectively reshapes the static var generator output impedance, elevating the phase from negative to positive damping in the critical frequency range, thereby fundamentally suppressing the resonance. And the dual-loop virtual synchronous generator control the static var generator, leveraging its current inner loop, exhibits superior reactive power tracking capability, faster and smoother transient responses, and enhanced rapidity and effectiveness in suppressing mid-frequency resonance.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"177 ","pages":"Article 111861"},"PeriodicalIF":5.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147744564","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}