IEEE Open Access Journal of Power and Energy最新文献_第4页

Delay-Resilient Voltage Control via Multi-Agent Reinforcement Learning With Causal State Augmentation 基于因果状态增强的多智能体强化学习延迟弹性电压控制

IF 2.8

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-10-02 DOI: 10.1109/OAJPE.2026.3740043

Joseph Owusu;Di SHI;Praveen Verma;Fengyu Wang;Yingying Wang

引用次数: 0

A Decision-Analytics Framework Combining DEA, SFA, and ML With Mixture Optimization for Industrial Photovoltaics 结合DEA， SFA和ML的决策分析框架与混合优化的工业光伏

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-03-19 DOI: 10.1109/OAJPE.2026.3694970

Gustavo S. Leal;Victor E. M. Valério;Pedro P. Balestrassi;Lupércio F. Bessegato;Farid Melgani

{"title":"A Decision-Analytics Framework Combining DEA, SFA, and ML With Mixture Optimization for Industrial Photovoltaics","authors":"Gustavo S. Leal;Victor E. M. Valério;Pedro P. Balestrassi;Lupércio F. Bessegato;Farid Melgani","doi":"10.1109/OAJPE.2026.3694970","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3694970","url":null,"abstract":"The rapid rollout of industrial photovoltaic (PV) generation demands robust tools for benchmarking performance and guiding investment. Traditional efficiency techniques–non-parametric data envelopment analysis (DEA) and parametric stochastic-frontier analysis (SFA)–offer complementary strengths, yet each has recognized limitations when applied in isolation. This study proposes a hybrid framework that i) estimates multiple DEA and SFA frontiers; ii) learns their predictive patterns with Random Forest, Gradient Boosting and XGBoost models; and iii) integrates the resulting efficiency scores through an optimized weighting scheme derived from a simplex-lattice mixture design of experiments. The approach is demonstrated on a statewide dataset covering 70 immediate geographic regions of Minas Gerais, Brazil, comprising installed capacity, number of PV units, solar-radiation estimates and realized energy output. Optimization yields a parsimonious composite based primarily on the DEA and SFA models, reducing the principal-component loss metric by 18 % relative to equal weighting. Spatial analysis reveals a clear north–south efficiency gradient correlated with solar insolation; nonetheless, centrally located industrial hubs also achieve high scores, underscoring the moderating role of infrastructure. The findings highlight regions where policy support or technology upgrades could deliver the greatest marginal gains and illustrate how mixture-design optimization can reconcile diverse frontier estimates, offering a generalizable decision-analytics toolkit for renewable-energy assessment.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"403-415"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11525404","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148171725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Power Flow-Based Estimation of Short-Circuit Currents From Inverter-Based Resources 基于功率流的逆变器资源短路电流估计

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-03-12 DOI: 10.1109/OAJPE.2026.3673646

Ramon Abritta;Gabriel M. G. Guerreiro;Alexey Pavlov;Børre Tore Børresen;Elisabetta Tedeschi;Ranjan Sharma;Ivo C. da Silva Junior

{"title":"Power Flow-Based Estimation of Short-Circuit Currents From Inverter-Based Resources","authors":"Ramon Abritta;Gabriel M. G. Guerreiro;Alexey Pavlov;Børre Tore Børresen;Elisabetta Tedeschi;Ranjan Sharma;Ivo C. da Silva Junior","doi":"10.1109/OAJPE.2026.3673646","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3673646","url":null,"abstract":"The generator side of inverter-based resources (IBRs) interfaced with back-to-back converters is electrically decoupled from the grid. During electrical faults, grid-following IBRs behave as voltage-dependent current sources due to grid code requirements and converter control. This paper presents Newton-Raphson formulations for estimating short-circuit currents from IBRs using novel power flow modeling approaches to address voltage-dependent current sources. The work shows how to represent dq0 current injections, which are typically implemented in control architectures based on phase-locked loops. The power flow formulations are adapted to capture grid codes with different characteristics, such as the injection of negative-sequence currents during unbalanced faults. Comparisons against a field-validated electromagnetic transients (EMT) model reveal mean absolute errors of less than 0.5% for the proposed approach when estimating steady-state short-circuit currents from type IV wind turbine generators under grid-following control.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"229-239"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11432888","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent Coordination and Control of Distributed Energy Resources, OLTC, and SCB in Smart Grid Using X-DNN 基于X-DNN的智能电网分布式能源、OLTC和SCB智能协调与控制

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-04-22 DOI: 10.1109/OAJPE.2026.3686384

Tolulope David Makanju;Ali N. Hasan;Thokozani Shongwe

{"title":"Intelligent Coordination and Control of Distributed Energy Resources, OLTC, and SCB in Smart Grid Using X-DNN","authors":"Tolulope David Makanju;Ali N. Hasan;Thokozani Shongwe","doi":"10.1109/OAJPE.2026.3686384","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3686384","url":null,"abstract":"The introduction of distributed energy resources (DERs) into distribution networks has caused a lot of challenges, such as power flow imbalance, voltage fluctuation, and operation control of voltage regulation devices. The optimization techniques used in power systems to address these issues have disadvantages, such as slow computational speed. To this end, we developed a two-stage control strategy for modern power system networks, wherein an Explainable-Deep neural network (X-DNN) controller was developed and trained using the output responses of centralized multi-objective AC optimal power Flows. The first stage involved the use of offline optimization methods by embedding a controller to generate optimal set points of the grid-connected inverter (GCI) and voltage-regulating devices’ responses under the uncertainty of Photovoltaic (PV) power output and loading conditions, forming the training dataset for the X-DNN model. The trained X-DNN controller was deployed for real-time control, and the simulation of this approach was tested on the IEEE 69-bus system with a high penetration of PV grid-connected inverters (GCI), and compared with particle swarm optimization (PSO) and the genetic algorithim (GA). The results confirm that the X-DNN controller offers robust and efficient regulation, capable of maintaining system voltage stability by reducing the average voltage deviation by 34.7% and 56.69% compared to GA and PSO, respectively, and by 7.47% and 14.52% in active power losses for GA and PSO, respectively. Moreover, the X-DNN controller offers faster computational performance, making it a promising framework for smart power networks.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"321-332"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11493518","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rotor Speed Estimation of Synchronous Generators Based on PMU Data and Tuning of Linearized Swing Equation Coefficients 基于PMU数据和线性化摆动方程系数整定的同步发电机转子转速估计

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-03-14 DOI: 10.1109/OAJPE.2026.3693530

Thales Pedro S. Esperança;Tatiane Cristina C. Fernandes;Edson L. Geraldi;Guilherme G. Lage;Gustavo P. Eustáquio;Rodrigo A. Ramos

{"title":"Rotor Speed Estimation of Synchronous Generators Based on PMU Data and Tuning of Linearized Swing Equation Coefficients","authors":"Thales Pedro S. Esperança;Tatiane Cristina C. Fernandes;Edson L. Geraldi;Guilherme G. Lage;Gustavo P. Eustáquio;Rodrigo A. Ramos","doi":"10.1109/OAJPE.2026.3693530","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3693530","url":null,"abstract":"The rotor speed of Synchronous Generators (SGs) is a fundamental dynamic state that reflects the stored kinetic energy and the generator’s inertial response to system disturbances. Accurate rotor-speed estimation enables the detection of poorly damped electromechanical oscillations that may lead to instability. However, precise assessment of SG dynamics is often hindered by model inaccuracies and parametric uncertainties. With the increasing deployment of Phasor Measurement Units (PMUs), novel approaches have emerged to enhance post-event system diagnosis, particularly in low-inertia systems. This paper proposes a two-stage framework for estimating the rotor speed of SGs by tuning the coefficients of the linearized swing equation using data from PMUs, thus eliminating the need for the complete Electric Power System (EPS) model. In the first stage, the Morris sensitivity method identifies the most influential coefficients to refine the parameter-estimation domain. In the second stage, an Entropy-Based Genetic Algorithm (EB-GA) refines these coefficients by minimizing the mean squared error between measured EPS dynamics and the model response. Simulation results on the IEEE 68-bus system demonstrate that the proposed framework effectively captures SG rotor-speed dynamics, even under small perturbations and noisy PMU data. The EB-GA achieves more precise parameter tuning than conventional genetic algorithms, improving the representation of SG dynamics for post-event analysis and subsequent controller adjustment in EPSs.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"379-390"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11520323","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148003452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of the Frequency Support Provided by Grid-Forming DFIG-Based Wind Turbine on Power System Ultra-Low Frequency Oscillation 成网dfig型风力发电机组提供频率支撑对电力系统超低频振荡的影响

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-06-01 DOI: 10.1109/OAJPE.2026.3698446

Dong Wang;Jun Tian;Yunhui Huang;Wanning Zheng;Li Sun;Keliang Zhou

{"title":"Impact of the Frequency Support Provided by Grid-Forming DFIG-Based Wind Turbine on Power System Ultra-Low Frequency Oscillation","authors":"Dong Wang;Jun Tian;Yunhui Huang;Wanning Zheng;Li Sun;Keliang Zhou","doi":"10.1109/OAJPE.2026.3698446","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3698446","url":null,"abstract":"Ancillary frequency controls of wind turbines (WTs) bridge the dynamic interplay between turbine mechanics and the electrical grid, enabling WTs to influence low frequency range dynamics in power systems. This work examines the impact of frequency support by grid-forming (GFM) doubly-fed induction generator (DFIG) based WT on power system ultra-low frequency oscillations (ULFOs). Accounting for different wind speed operating regions, a reduced-order small-signal model is developed to characterize GFM-DFIG’s terminal power-frequency response behavior within ULFO frequency band. This model is then integrated into the system frequency response framework. Utilizing complex torque coefficients method, the effects of various control strategies—including virtual inertia, primary frequency control, and turbine blade pitching—on the ULFO mode’s frequency and damping characteristics are analytically derived and examined. The results confirm that while the frequency support improves system frequency response, it simultaneously deteriorates ULFO damping, with high primary frequency droop gain posing a risk of instability. Lastly, simulation studies with a modified IEEE 10-machine 39-bus system are conducted to validate the theoretical findings.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"448-459"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11541104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Measuring Impedance Spectra in Distribution Feeders Using GridSweep 网格扫描法测量配电馈线阻抗谱

IF 2.8

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1109/OAJPE.2026.3727558

Lingling Fan;Zhixin Miao;Jason S. MacDonald;Alex Mceachern

{"title":"Measuring Impedance Spectra in Distribution Feeders Using GridSweep","authors":"Lingling Fan;Zhixin Miao;Jason S. MacDonald;Alex Mceachern","doi":"10.1109/OAJPE.2026.3727558","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3727558","url":null,"abstract":"Peaks and troughs in the subsynchronous impedance spectrum of a distribution feeder may be a useful indication of oscillation risk, or more importantly lack of oscillation risk, if inverter-based resource (IBR) deployments are increased on that feeder. This paper demonstrates that the impedance spectrum can be measured by GridSweep, an instrument device. GridSweep combines an active probing device that modulates a 120-volt 1-kW load sinusoidally at a user-selected GPS-phase locked frequency from 1.0 Hz to 40.0 Hz, and with a recorder that takes ultra-high-precision continuous point-on-wave (CPOW) 120-volt synchrowaveforms at 4 kHz. Our paper reveals that the measured voltage spectra by GridSweep correspond to the subsynchronous impedance spectra of distribution feeders. For demonstration, we construct an electromagnetic transient (EMT) simulation of a single-phase distribution feeder equipped with multiple IBRs. We include a model of the GridSweep probing device, then demonstrate the model’s capability of measuring the subsynchronous apparent impedance spectrum of the feeder. In addition, we show that peaks in that spectrum align with the system’s dominant oscillation modes caused by IBRs.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"739-750"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11667024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Thermal-Electrical Co-Optimization Framework for Active Distribution Grids With Electric Vehicles and Heat Pumps 基于电动汽车和热泵的有源配电网热电协同优化框架

IF 2.8

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1109/OAJPE.2026.3727423

Savvas Panagi;Chrysovalantis Spanias;Petros Aristidou

{"title":"A Thermal-Electrical Co-Optimization Framework for Active Distribution Grids With Electric Vehicles and Heat Pumps","authors":"Savvas Panagi;Chrysovalantis Spanias;Petros Aristidou","doi":"10.1109/OAJPE.2026.3727423","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3727423","url":null,"abstract":"The growing electrification of transportation and heating through Electric Vehicles (EVs) and Heat Pumps (HPs) introduces both flexibility and complexity to Active Distribution Networks (ADNs). These resources provide substantial operational flexibility but also create tightly coupled thermal–electrical dynamics that challenge conventional network management. This paper proposes a unified co-optimization framework that integrates a calibrated 3R2C grey-box building thermal model into a network-constrained Optimal Power Flow (OPF). The framework jointly optimizes EVs, HPs, and photovoltaic systems while explicitly enforcing thermal comfort, Distributed Energy Resource (DER) limits, and full power flow physics. To maintain computational tractability, Second-Order Cone Programming (SOCP) relaxations are evaluated on a realistic low-voltage feeder. The analysis shows that, despite network heterogeneity violating some theoretical exactness conditions, the relaxation remains exact in practice. Comparative assessments of convex DistFlow, bus injection, and branch flow formulations reveal that convex DistFlow achieves sub-second runtimes and near-optimal performance even at high DER penetration levels. Simulations confirm the effectiveness of the proposed methodology, achieving up to a 47% reduction in daily network losses while mitigating transformer aging, eliminating voltage violations, and reducing line and transformer loading. The proposed framework consistently outperforms representative price-based and active-power-only scheduling approaches.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"751-761"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11667004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148925865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computational Complexity Analysis of the Holomorphic Embedding Method and Parallel Optimization Strategies for Improving Efficiency 全纯嵌入方法的计算复杂度分析及提高效率的并行优化策略

IF 3.2

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-03-26 DOI: 10.1109/OAJPE.2026.3696776

Yongjian Luo;Chengxi Liu;Pengfei Tang;Zaiyu He

{"title":"Computational Complexity Analysis of the Holomorphic Embedding Method and Parallel Optimization Strategies for Improving Efficiency","authors":"Yongjian Luo;Chengxi Liu;Pengfei Tang;Zaiyu He","doi":"10.1109/OAJPE.2026.3696776","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3696776","url":null,"abstract":"The holomorphic embedding (HE) method has gained significant attention in power flow analysis. However, there is no consensus regarding its computational efficiency compared to the traditional Newton-Raphson (NR) method. This paper presents a comprehensive analysis of the computational complexity of the HE method focusing on key steps such as matrix factorization, higher-order power series calculation, and Padé approximation. A theoretical investigation of these steps is conducted, followed by the implementation of multi-core parallel computing using Numba to enhance performance. Case studies on test systems ranging from 300 to 25,000 buses are used to evaluate the parallel strategies for accelerating computation. The results show a significant improvement in the computational efficiency of the HEM, demonstrating its scalability and practical applicability for large-scale power flow calculations. This study provides both theoretical and practical foundations for the broader adoption of the HE method in power system analysis.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"437-447"},"PeriodicalIF":3.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11535451","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Integrated Generation–Transmission Expansion Planning With Uncertain Dynamic Line Ratings, Renewable Energy, and Electric Vehicles 具有不确定动态线路额定值、可再生能源和电动汽车的综合发电-输电扩展规划

IF 2.8

IEEE Open Access Journal of Power and Energy Pub Date : 2026-01-01 Epub Date: 2026-08-03 DOI: 10.1109/OAJPE.2026.3719563

Arash Baharvandi;Duong Tung Nguyen

{"title":"Integrated Generation–Transmission Expansion Planning With Uncertain Dynamic Line Ratings, Renewable Energy, and Electric Vehicles","authors":"Arash Baharvandi;Duong Tung Nguyen","doi":"10.1109/OAJPE.2026.3719563","DOIUrl":"https://doi.org/10.1109/OAJPE.2026.3719563","url":null,"abstract":"This paper examines the integrated generation and transmission expansion planning (IGTEP) problem in the presence of increasing power system demand, high penetration of renewable energy sources (RES), and growing electric vehicle (EV) charging loads. The proposed framework jointly optimizes investment and operational costs for new generation units and transmission lines, while considering the environmental benefits of RES integration and the impact of EV charging on grid operation. The inherent uncertainties in load demand, EV charging, and renewable generation are addressed through a hybrid stochastic-robust optimization approach. Dynamic thermal line rating (DTLR) is incorporated through a physics-based heat balance model to capture time-varying transmission limits driven by environmental conditions. The framework also tackles the uncertainty in DTLR, incorporating a heuristic linearization technique to reduce model complexity. Unlike conventional IGTEP approaches that rely on static line ratings or treat uncertainties independently, the proposed framework provides a unified and scalable formulation that jointly captures multi-source uncertainties, including renewable variability, EV demand, and weather-driven line ratings. The effectiveness of the proposed approach is demonstrated on the IEEE 6-bus and IEEE 118-bus systems.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"13 ","pages":"606-618"},"PeriodicalIF":2.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11640834","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148748792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0