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Grid Inertia Support of Long-Distance MMC-HVDC System Integrating Hydropower Considering Communication Delay 考虑通信延迟的远距离MMC-HVDC集成水电系统的电网惯性支持
IF 3.7 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/TPWRD.2025.3648585
Junjie Lin;Wang Xiang;Haobo Zhang;Zhu Guo;Weihuang Huang;Jinyu Wen
With the increasing integration scale of renewable energy, the receiving-end power grids are suffering from low inertia and weak support problems. It is desired that the large-capacity modular multilevel converter-based high-voltage direct current (MMC-HVDC) systems could provide inertia support for the receiving grids. However, current analysis mainly focuses on the inertia support of wind farms/photovoltaic plants integrated MMC-HVDC systems. This paper studied the inertia support of MMC-HVDC systems transmitting large-scale hydropower. Firstly, the inertia support capability of the MMC-HVDC system integrating hydropower is analyzed, considering the communication delay and the support strategies of different devices. Then, an inertia boost control scheme was proposed for the sending-end MMC, which maximizes the inertia support of the hydropower generator and MMC's capacitor energy. Furthermore, a method for assessing the inertia support performance of the MMC-HVDC system is proposed, which approximates the system's time-varying inertia as piecewise constants. Finally, simulations are performed in a two-terminal MMC-HVDC system to verify the effectiveness of the proposed analysis method and control strategy.
随着可再生能源并网规模的不断扩大,接收端电网存在惯性低、支撑能力弱的问题。期望基于大容量模块化多电平变换器的高压直流(MMC-HVDC)系统能为接收电网提供惯性支撑。然而,目前的分析主要集中在风电场/光伏电站集成MMC-HVDC系统的惯性支持上。本文研究了MMC-HVDC输电系统的惯性支撑问题。首先,在考虑通信延迟和不同设备支持策略的情况下,分析了MMC-HVDC集成水电系统的惯性支持能力。然后,针对发送端MMC,提出了一种最大限度地利用水力发电机的惯性支撑和MMC电容器能量的惯性升压控制方案。在此基础上,提出了一种将MMC-HVDC系统时变惯量近似为分段常数的惯性支撑性能评估方法。最后,在双端MMC-HVDC系统中进行了仿真,验证了所提出的分析方法和控制策略的有效性。
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引用次数: 0
Real-Time Energy Management for Urban Rail Transit with Reversible Substations Based on Deep Reinforcement Learning 基于深度强化学习的可逆变电站城市轨道交通实时能量管理
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648855
Wei Liu, Dingxin Xia, Qian Xu, Juxia Ding, Xiaodong Zhang, Haonan Liu, Haotian Deng
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引用次数: 0
Prescribed Performance Voltage Regulation in Islanded Microgrids: An Event-Triggered Fault Compensation Approach 孤岛微电网规定性能电压调节:一种事件触发故障补偿方法
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648841
Panpan Wang, Dongni Li, Zhiming Xu, Jiayue Sun
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引用次数: 0
Decoupled Detailed Equivalent Model for Parallel and Multi-Rate EMT-Type Simulation of Modular Multilevel Converter With Battery Energy Storage 电池储能模块化多电平变换器并联多速率emt型仿真解耦详细等效模型
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648650
Walid Hatahet, Hengyu Li, Liwei Wang, Wei Li
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引用次数: 0
Data and Model Hybrid Driven Non-Intrusive Wideband Impedance Measurement for LCC-HVDC Systems LCC-HVDC系统数据与模型混合驱动非侵入式宽带阻抗测量
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648375
Dan Wang, Yong Li, Jinjie Lin, Zichen Hu, Yi Zhang
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引用次数: 0
Exact Lower Bound for Equitable Harmonic Hosting Capacity 均衡谐波承载能力的精确下界
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648618
Tom Van Acker, Hakan Ergun
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引用次数: 0
Does Series Compensation Improve the Transient Stability of Inverter-Based Resources? 串联补偿能提高逆变器资源的暂态稳定性吗?
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3646938
Mohamad-Amin Nasr, Ali Hooshyar
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引用次数: 0
Waveform Distortions During Power Frequency Testing of Metal Oxide Varistors: Their Origin and Effect on Average Power Dissipation 金属氧化物压敏电阻工频测试中波形畸变的原因及其对平均功耗的影响
IF 3.7 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/TPWRD.2025.3648940
Eric P. Nied;Stephen F. Poterala;Xingniu Huo;Dustin L. Sullivan
While it is well known that a Metal Oxide Varistor (MOV) heavily distorts the voltage wave of a high-current lightning impulse, less has been said about waveform distortions observed during power frequency testing. This paper shows that significant distortions are likely produced by practical generators during power frequency testing of MOVs, with the effect that average power dissipation of MOVs and surge arresters is severely impacted by generator setup. Four distribution transformer configurations with different output impedances were used to apply 60 Hz voltage waves to a conducting, 5 kV-rated MOV at six peak current levels. Distortion was found to be a function of generator impedance and current magnitude. In one typical experiment, even a slight distortion (Vrms / (Vpeak / √2) = 1.014) led to ∼33% decrease in average power dissipation compared to that of a distortion-free wave of the same rms voltage. Without consideration of these effects, seemingly minor differences in procedure can cause parts to erroneously pass or fail tests prescribed in IEEE C62.11 (2020) or IEC 60099-4 ed. 3.0, leading to arresters not meeting manufacturers’ 60 Hz TOV claims. A method is also outlined to correct for waveform distortion, enabling calculation of distortion-free average power dissipation.
众所周知,金属氧化物压敏电阻(MOV)会严重扭曲大电流雷电脉冲的电压波,但在工频测试中观察到的波形扭曲却很少被提及。研究表明,在动动器工频测试中,实际发电机可能会产生较大的畸变,发电机设置严重影响动动器和避雷器的平均功耗。采用四种具有不同输出阻抗的配电变压器配置,在六个峰值电流水平下向导电的5 kv额定MOV施加60 Hz电压波。发现畸变是发电机阻抗和电流大小的函数。在一个典型的实验中,即使是轻微的失真(Vrms / (Vpeak /√2)= 1.014),与相同均方根电压的无失真波相比,也会导致平均功耗降低约33%。如果不考虑这些影响,看似微小的程序差异可能导致部件错误地通过或不通过IEEE C62.11(2020)或IEC 60099-4 ed. 3.0规定的测试,导致避雷器不符合制造商的60 Hz TOV声明。本文还提出了一种校正波形失真的方法,使计算无失真平均功耗成为可能。
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引用次数: 0
Robust Loop-Shaping Control for Medium-High Frequency Oscillations Mitigation in Grid-Connected Converters with Effective Hardware Implementation 并网变流器中高频振荡抑制的鲁棒环整形控制及有效硬件实现
IF 4.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/tpwrd.2025.3648950
Veeranna Kuruva, Amir H. Abolmasoumi, Vinu Thomas, Bogdan Marinescu
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引用次数: 0
A Machine Learning-Enhanced System for Rapid Detection of Lightning-Impacted Wind Turbines 雷击风力涡轮机快速检测的机器学习增强系统
IF 3.7 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2025-12-26 DOI: 10.1109/TPWRD.2025.3648739
Chanaka Keerthisinghe;Aijun Deng;Xueyin Yu;Rosebud J. Lambert;Fernando Freitas
Lightning is a leading cause of wind turbine blade failures in the United States and globally, resulting in significant financial losses for the industry. Rapid detection of turbine strikes is essential to reduce these costs. While nearby lightning strikes can be detected with high accuracy, confirming whether a specific turbine was struck remains challenging. Current confirmation relies on manual inspections with drones, which may take hours to years if damage develops slowly during operation. This work presents a scalable, three-step framework for lightning strike confirmation that integrates lightning measurements, turbine alarms, and supervisory control and data acquisition (SCADA) based machine-learning anomaly detection. The first step analyzes the magnitude (kA) and proximity of nearby lightning strikes. The second step evaluates historical alarm patterns associated with lightning-induced damage. The third step applies machine learningbased anomaly detection to post-event SCADA signals, focusing on rotor speed, wind speed, and pitch angle behavior. The framework was evaluated using 26 U.S. wind turbines with confirmed lightning strikes between 2021 and 2024, together with 1650 turbines that experienced nearby strikes without direct impact. This timealigned dataset enables robust model training and validation. The proposed approach is designed for fleet-wide deployment and demonstrates strong scalability. At the highest confidence level, recall and precision were 96% and 86% at the next level, 100% and 81%. Deployment across Vestas' U.S. fleet could conservatively save over ${$}$ 16 million annually in avoided blade repair costs, excluding additional benefits from reduced turbine downtime, thereby contributing to lower wind energy costs.
闪电是美国和全球风力涡轮机叶片故障的主要原因,给该行业造成了重大的经济损失。快速检测涡轮机撞击对降低这些成本至关重要。虽然附近的雷击可以被高精度地探测到,但确认某个特定的涡轮机是否被击中仍然具有挑战性。目前的确认依赖于无人机的人工检查,如果在操作过程中损坏进展缓慢,可能需要数小时到数年的时间。这项工作提出了一个可扩展的三步雷击确认框架,该框架集成了闪电测量、涡轮机警报以及基于机器学习异常检测的监控和数据采集(SCADA)。第一步分析附近雷击的震级(kA)和接近度。第二步评估与雷击致损相关的历史报警模式。第三步将基于机器学习的异常检测应用于事件后SCADA信号,重点关注转子速度、风速和俯仰角行为。该框架使用了26台美国风力涡轮机进行评估,这些涡轮机在2021年至2024年期间被确认有雷击,以及1650台经历过附近雷击但没有直接影响的涡轮机。这个时间对齐的数据集支持稳健的模型训练和验证。该方法适用于舰队范围内的部署,具有很强的可扩展性。在最高置信水平下,召回率和准确率分别为96%和86%,下一级为100%和81%。在维斯塔斯的美国机队中部署该系统,保守估计每年可节省超过1600万美元的叶片维修成本,这还不包括减少涡轮机停机时间带来的额外好处,从而有助于降低风能成本。
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引用次数: 0
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IEEE Transactions on Power Delivery
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