Electric Power Systems Research最新文献

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Single-stage boosting inverter with differential power processor for photovoltaic system 光伏系统差分功率处理器单级升压逆变器

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-17 DOI: 10.1016/j.epsr.2026.112752

Ben Zhao , Haoran Cui , Na Yan , Yigeng Huangfu

The partial shading of photovoltaic (PV) modules caused by factors such as trees, clouds, and dust, as well as varying degrees of aging among PV modules, will lead to mismatched electrical characteristics of series PV modules and result in a significant power loss in the PV system. Differential power processing (DPP) converters can be employed to improve the power generation under partial shading conditions for a PV system. Nevertheless, a DPP converter is usually an additional device to the existing PV system and will introduce extra power losses and expense. In this paper, a single-stage boosting inverter (SSBI) integrated with a multi-winding type DPP converter is proposed. The functions of maximum power point tracking (MPPT), voltage step-up, inversion, and power equalization are achieved in one power stage. Only four switches are employed to achieve the above functions, resulting in a simple circuit and low cost. The feasibility of the proposed topology is verified by simulations and experiments. The experimental results show that, compared with SSBI without an integrated DPP structure, the proposed topology can have 12.83 % and 60.51 % power increment under two different partial shading conditions and good quality sinusoidal output with total harmonic distortion (THD) of 4 %.

由于树木、云层、灰尘等因素造成的光伏组件部分遮阳，以及光伏组件之间不同程度的老化，会导致串联光伏组件的电气特性不匹配，造成光伏系统的严重功率损耗。差分功率处理（DPP）变流器可用于提高光伏系统在部分遮阳条件下的发电量。然而，DPP转换器通常是现有光伏系统的附加设备，并且会带来额外的功率损失和费用。提出了一种集成多绕组型DPP变换器的单级升压逆变器（SSBI）。在一个功率级内实现了最大功率点跟踪（MPPT）、升压、逆变和功率均衡等功能。仅使用4个开关即可实现上述功能，电路简单，成本低。仿真和实验验证了所提拓扑的可行性。实验结果表明，与没有集成DPP结构的SSBI相比，所提出的拓扑在两种不同的部分遮光条件下功率分别增加12.83%和60.51%，输出质量良好，总谐波失真（THD）为4%。

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引用次数: 0

Electricity price spike forecasting via multivariate adaptive visibility graph neural networks 基于多元自适应可见性图神经网络的电价峰值预测

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-16 DOI: 10.1016/j.epsr.2025.112695

Tianshu Bao , Nariman Mahdavi , Chris Mccarthy , Dana Rezazadegan

Accurate forecasting of electricity price spikes is critical for energy market risk management, as these rare yet disruptive events cause substantial financial losses and arise from complex interactions among multiple market variables. An enhanced Graph Neural Network (GNN) framework is proposed that captures interdependencies among these Multivariate variables via an Adaptive Visibility Graph (MAVG) network. A hierarchical Differentiable Pooling (DiffPool) GNN architecture is then applied to coarsen this graph and forecast the next-step price spike probability. To address the extreme class imbalance inherent in spike data, a novel oversampling method called the balanced epoch sampler is also introduced. The proposed MAVG-DiffPool framework with oversampling is validated using real electricity prices from Australia under multiple spike thresholds. The framework achieves an F1-score of 0.84 under the moderate threshold. Under the extreme threshold, the framework outperformed LSTM by achieving nearly double the F1-score, demonstrating its effectiveness and robustness in addressing the challenge of spike forecasting.

准确预测电价峰值对于能源市场风险管理至关重要，因为这些罕见但具有破坏性的事件会造成巨大的经济损失，并且源于多个市场变量之间复杂的相互作用。提出了一种增强的图神经网络（GNN）框架，通过自适应可见性图（MAVG）网络捕获这些多变量之间的相互依赖关系。然后应用分层可微分池（DiffPool） GNN架构对该图进行粗化，并预测下一步的价格峰值概率。为了解决尖峰数据固有的极端类不平衡问题，本文还引入了一种新的过采样方法——平衡历元采样器。采用多个峰值阈值下的澳大利亚实际电价验证了提议的带有过采样的MAVG-DiffPool框架。在中等阈值下，该框架的f1得分为0.84。在极端阈值下，该框架的表现优于LSTM，达到f1得分的近两倍，证明了其在应对尖峰预测挑战方面的有效性和鲁棒性。

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引用次数: 0

ZVZCS PSFB converter with minimized primary circulating losses and secondary voltage stresses using auxiliary winding and circuit ZVZCS PSFB变换器与最小的初级循环损耗和二次电压应力使用辅助绕组和电路

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-14 DOI: 10.1016/j.epsr.2026.112714

Zhenxing Zhao , Yujie He , Yuxing Dai , Jijia Zhu , Zishun Peng , Xinyan Huang , Kamal Al-Haddad , Yachao Yang

In order to solve the efficiency loss problem of phase shifting full bridge converters and maintain the excellent characteristics of wide range adjustment, this paper proposes an improved ZVZCS phase shifting full bridge converter. Through the auxiliary winding of the transformer and the secondary auxiliary circuit, the full-bridge converter achieves zero-voltage switching on the leading arm and zero-current turnoff on the lagging arm, minimizing the primary circulating current; the secondary rectifier diode achieves zero-current switching and minimizes the voltage stress of the rectifier diode; the energy transmission efficiency is significantly improved under the same effective duty cycle. Finally, a DC/DC experimental prototype with an input of 390VDC, an output of 120VDC, and a power of 1.2 kW was built to verify the above characteristics and the peak efficiency reached 97.44%.

为了解决移相全桥变换器的效率损耗问题，并保持其良好的宽量程调节特性，本文提出了一种改进型ZVZCS移相全桥变换器。全桥变换器通过变压器辅助绕组和二次辅助电路，实现超前臂的零电压开关和滞后臂的零电流关断，使一次循环电流最小；二级整流二极管实现零电流开关并使整流二极管的电压应力最小化；在相同的有效占空比下，能量传输效率显著提高。最后搭建了输入为390VDC、输出为120VDC、功率为1.2 kW的DC/DC实验样机，验证了上述特性，峰值效率达到97.44%。

引用次数: 0

Interaction of neural network and dung beetle optimizer for characterization of large power transformers considering through-fault protection capability 考虑过故障保护能力的大型电力变压器神经网络与屎壳虫优化器的交互作用

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-02-09 DOI: 10.1016/j.epsr.2026.112808

Abdelmonem Draz , Hossam Ashraf , Ahmed R. El Shamy , Attia A. El‑Fergany

Several computational methods aim to accurately identify unknown parameters of transformers (XFMRs) through appropriate objective functions, but there is a need for more accurate models for large power XFMRs in both normal and faulty conditions. This paper presents a novel approach for estimating unknown parameters of power XFMRs by combining metaheuristic optimization with artificial neural networks (ANN). Six unidentified parameters are determined using the dung beetle optimizer (DBO), whose effectiveness is validated against various challenging optimizers. The algorithms capture the steady-state fingerprints of test cases regarding voltage regulation and efficiency characteristics under varying loading conditions. Moreover, ANN is employed to assess XFMR operations in malfunctioning scenarios by predicting protection through-fault capabilities. This includes analyzing frequent fault characteristics due to mechanical damage and infrequent electrical degradation faults via actual measurements of XFMR parameters. The proposed method is applied to a real-case power XFMR of 40 MVA and a benchmark 4 kVA XFMR, confirming that frequent fault characteristics for the 40 MVA XFMR begin at 4.06 times the rated current. The findings illustrate the synergistic capabilities of ANN and DBO in characterizing key parameters and performance of power XFMRs.

目前已有一些计算方法旨在通过适当的目标函数准确识别变压器的未知参数，但对于大功率XFMRs，无论是在正常状态还是故障状态下，都需要更精确的模型。提出了一种将元启发式优化与人工神经网络相结合的功率xfmr未知参数估计方法。使用蜣螂优化器（DBO）确定了六个未确定的参数，其有效性针对各种具有挑战性的优化器进行了验证。该算法捕获了不同负载条件下电压调节和效率特性测试用例的稳态指纹。此外，通过预测故障保护能力，采用人工神经网络来评估故障场景下的XFMR操作。这包括通过实际测量XFMR参数来分析由于机械损伤引起的频繁故障特征和不常见的电气退化故障。将该方法应用于40 MVA的实际功率XFMR和4 kVA的基准XFMR，证实了40 MVA XFMR的频繁故障特征始于额定电流的4.06倍。研究结果说明了人工神经网络和DBO在表征功率xfmr的关键参数和性能方面的协同能力。

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引用次数: 0

Admittance modeling and oscillation analysis of hybrid GFL and GFM DFIGs under weak grid conditions 弱电网条件下GFL和GFM混合DFIGs的导纳建模及振荡分析

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-20 DOI: 10.1016/j.epsr.2026.112759

Xiaoju Lv, Ziwen Liu, Ziting Mei, Li Zhang, Feng Wu

With the development of Grid-Forming (GFM) wind turbine technology, dynamic uinteractions between hybrid Grid-Following Doubly-Fed Induction Generators (GFL DFIGs) and GFM DFIGs are intensifying, posing stability challenges, especially in weak grids. Therefore, this paper investigates the dynamic frequency coupling characteristics and instability mechanisms of hybrid systems composed of GFL and GFM DFIGs. Based on the dq coordinate system, a multiple-input multiple-output (MIMO) frequency-coupled admittance model is established for both GFL and GFM DFIGs, considering the dynamics of stator and rotor flux linkage and various control loops. Using the generalized Nyquist criterion, system oscillation mechanisms under weak grid conditions are assessed through eigenvalue trajectories of the frequency-domain loop gain matrix. The impact of different GFM configuration proportions on hybrid system stability is also explored. Finally, simulations in PSCAD validate the theoretical analysis, providing a foundation for parameter optimization and coordinated operation of hybrid GFL and GFM DFIG systems.

随着电网成形（GFM）风力发电技术的发展，混合式随网双馈感应发电机（GFL DFIGs）和GFM DFIGs之间的动态不相互作用日益加剧，对稳定性提出了挑战，特别是在弱电网中。因此，本文研究了由GFL和GFM DFIGs组成的混合系统的动态频率耦合特性和失稳机理。在dq坐标系下，考虑定子和转子磁链的动力学特性以及各种控制回路，建立了GFL和GFM两种dfig的多输入多输出频率耦合导纳模型。利用广义奈奎斯特准则，通过频域环增益矩阵的特征值轨迹评估了弱电网条件下系统的振荡机制。探讨了不同GFM构型比例对混合系统稳定性的影响。最后，在PSCAD上进行仿真验证了理论分析，为GFL和GFM混合DFIG系统的参数优化和协调运行提供了基础。

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引用次数: 0

Sparse mixture of experts enhanced transformer architecture for short-term hydroelectric reservoir volume prediction 稀疏混合专家改进了短期水电库容预测的变压器结构

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-21 DOI: 10.1016/j.epsr.2026.112754

Laio Oriel Seman , Kin-Choong Yow , Stefano Frizzo Stefenon

In hydroelectric-based systems, effective energy generation planning relies heavily on precise forecasting of reservoir water levels. This paper proposes a novel hybrid forecasting framework that integrates multiple preprocessing strategies with a sparse Mixture of Experts enhanced Transformer architecture for short-term reservoir volume prediction. When evaluated on 19 interconnected reservoirs across two major river basins in southern Brazil using real operational data from the Brazilian National System Operator, the proposed model achieves a mean squared error of 0.062 and a mean absolute error of 0.145. Comprehensive benchmarking against 18 state-of-the-art deep learning methods demonstrates that the proposed approach significantly outperforms existing methods while maintaining computational efficiency through sparse expert routing. Our results confirm that combining diverse preprocessing strategies with conditional computation mechanisms provides superior forecasting accuracy for reservoir management in hydroelectric power systems.

在以水力发电为基础的系统中，有效的发电规划在很大程度上依赖于对水库水位的精确预测。本文提出了一种新的混合预测框架，该框架将多种预处理策略与稀疏混合专家增强变压器结构相结合，用于短期储层体积预测。当使用巴西国家系统运营商的实际操作数据对巴西南部两个主要河流流域的19个相互连接的水库进行评估时，所提出的模型的均方误差为0.062，平均绝对误差为0.145。对18种最先进的深度学习方法的综合基准测试表明，该方法在通过稀疏专家路由保持计算效率的同时，显著优于现有方法。研究结果表明，将多种预处理策略与条件计算机制相结合，可以提高水电系统水库管理的预测精度。

引用次数: 0

Fault section identification method of hybrid cable transmission lines based on frequency-constrained independent component analysis 基于频率约束独立分量分析的混合电缆传输线故障区段识别方法

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-19 DOI: 10.1016/j.epsr.2026.112732

Danhui Hu , Zeqi Huang , Yafang Tong , Qiang Sheng

A method for identifying fault segments in hybrid cable transmission lines based on frequency-constrained independent component analysis has been proposed. By analyzing the traveling-wave characteristics of faults in such lines and the generation mechanism of natural frequencies in traveling-wave signals, fault segment identification for hybrid transmission lines is realized. A traveling-wave signal denoising algorithm based on frequency-constrained independent component analysis is employed to extract the effective components of the traveling-wave signal under low-frequency constraints. The denoised traveling-wave signals are decomposed using the empirical mode decomposition (EMD) algorithm, and the intrinsic mode function (IMF) components of the signals are extracted as the principal components of the natural frequencies. Based on the principal natural frequency components, the distance between the fault point and the measurement point is calculated for both single-branch and multi-branch hybrid cable transmission lines, thereby determining the fault segment in the hybrid cable transmission line. Experimental results demonstrate that the proposed method can accurately identify fault locations in hybrid transmission lines by utilizing the principal natural frequency components of traveling-wave signals and is applicable to various types of hybrid cable transmission lines.

提出了一种基于频率约束独立分量分析的混合电缆传输线故障段识别方法。通过分析混合输电线路故障的行波特征和行波信号中固有频率的产生机理，实现了混合输电线路故障段的识别。采用基于频率约束独立分量分析的行波信号去噪算法，提取低频约束下行波信号的有效分量。采用经验模态分解（EMD）算法对消噪后的行波信号进行分解，提取信号的本征模态函数（IMF）分量作为固有频率的主成分。根据主固有频率分量计算单支路和多支路混合电缆传输线故障点与测量点之间的距离，从而确定混合电缆传输线中的故障段。实验结果表明，该方法能够利用行波信号的主固有频率分量准确识别混合传输线的故障位置，适用于各种类型的混合电缆传输线。

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引用次数: 0

Wavelet transform-based adaptive single-pole auto-reclosing approach for power transmission lines considering shunt reactors 考虑并联电抗器的输电线路小波变换自适应单极自合闸方法

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-21 DOI: 10.1016/j.epsr.2026.112758

Ahmed R. Adly , Mohamed A. Tolba , Mahmoud M. Elgamasy , Omar F. Fadl , Mahmoud A. Elsadd

Identifying the fault types is an essential mission of the transmission line protective scheme. This paper introduces an innovative wavelet-based adaptive reclosing technique for transmission systems equipped with shunt reactors. This approach helps prevent costly blackouts and ensures the reliability of the electrical grid. Significantly, even and odd harmonic components in the voltage signal become prominent after breaker operation, during the secondary arc, and following arc extinction in transient fault conditions. To address these challenges, the proposed method utilizes the wavelet packet transform (WPT) with a recursive and short-windowing approach to effectively extract harmonic components of various orders. Two distinct energy coefficient indices are developed to distinguish between transient and permanent faults and to determine the arc extinction instant. Different configurations of the power system are utilized to examine the proposed protective scheme. Software ATP-EMTP (Simulation experiments) verified the feasibility of the presented scheme. To verify the capability and accuracy of presented scheme, it is examined by many fault scenarios such as different fault location, different arc models, different compensation levels, power swing situation, varying source impedances, varying operating voltage, varying operating frequency and noise effect. In addition, the validity of the presented scheme is compared with other protection directional schemes.

故障类型识别是输电线路保护方案的一项重要任务。介绍了一种新颖的基于小波的输电系统自适应重合闸技术。这种方法有助于防止代价高昂的停电，并确保电网的可靠性。值得注意的是，在断路器运行后，在二次电弧期间，以及在瞬态故障条件下电弧熄灭后，电压信号中的偶、奇谐波分量变得突出。为了解决这些问题，该方法利用小波包变换（WPT）的递归短窗方法有效地提取了不同阶次的谐波分量。提出了两种不同的能量系数指标来区分暂态故障和永久故障，并确定消弧瞬间。利用不同的电力系统配置来检验所提出的保护方案。软件ATP-EMTP（仿真实验）验证了该方案的可行性。为了验证所提方案的能力和准确性，在不同的故障位置、不同的电弧模型、不同的补偿水平、功率摆幅情况、不同的源阻抗、不同的工作电压、不同的工作频率和噪声影响等多种故障场景下进行了测试。此外，还与其他保护定向方案进行了有效性比较。

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引用次数: 0

Research on the topology and startup control method of diode series boost offshore DC transmission system 二极管串联升压离岸直流输电系统拓扑结构及启动控制方法研究

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-20 DOI: 10.1016/j.epsr.2026.112716

Jianqiang Liu , Sixu Liu , Jinda Li , Xinyu Tan , Tengfei Guo , Haokai Xie

Diode rectifiers in offshore wind power DC transmission systems have economic and reliability advantages. This paper proposes a topology circuit for a diode series boost-type offshore wind power collection and transmission system, investigates its operational mechanism, and analyzes issues like uneven voltage sharing in series diodes and harmonic suppression in diode rectifiers. The harmonic characteristics and current distribution from the diode rectifier are examined, and parameter design methods are developed, including for the diode rectifier, high-potential converter, and LC filter. Also, to address reverse power flow during startup, a corresponding control strategy is developed. Through phased startup, the wind farm achieves a transition from black start to stable operation. Finally, simulations verify the effectiveness of the proposed topology, parameter design methods, and control strategy.

二极管整流器在海上风电直流输电系统中具有经济、可靠的优点。提出了一种二极管串联升压式海上风电集输系统的拓扑电路，研究了其运行机理，分析了串联二极管电压分担不均匀、二极管整流器谐波抑制等问题。研究了二极管整流器的谐波特性和电流分布，提出了二极管整流器、高电位变换器和LC滤波器的参数设计方法。针对启动过程中的反向潮流问题，提出了相应的控制策略。通过分阶段启动，实现了风电场从黑启动到稳定运行的过渡。最后，通过仿真验证了所提出的拓扑结构、参数设计方法和控制策略的有效性。

引用次数: 0

A direct MPPT method using inductor-based I–V measurement in a critical conduction mode (CrCM) interleaved boost converter 在临界导通模式（CrCM）交错升压变换器中使用基于电感的I-V测量的直接MPPT方法

IF 4.2 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-02-02 DOI: 10.1016/j.epsr.2026.112783

N. Çetin Acar , S. Börekci

In this study, a novel maximum power point tracking (MPPT) technique is proposed for photovoltaic (PV) systems using an interleaved boost converter operated in critical conduction mode. Unlike conventional methods, the maximum power point (MPP) is detected by analyzing the instantaneous inductor current and PV voltage within a single switching period, enabling precise determination of MPP in the order of microseconds. The interleaved boost topology significantly reduces input current ripple, thereby minimizing power oscillations around the MPP and improving overall system efficiency. The developed algorithm continuously samples inductor current and PV voltage, calculates instantaneous power, and updates the switching frequency accordingly under varying irradiance and temperature conditions. Experimental validation with a 40 W PV panel demonstrates that the proposed method achieves an accuracy of up to 99.5% when the PV system operates above 65% of nominal power. Compared to the conventional variable resistive method, the proposed MPPT technique provides faster response, higher accuracy, and lower power fluctuation, offering an efficient solution for next-generation PV energy conversion systems.

在这项研究中，提出了一种新的光伏（PV）系统最大功率点跟踪（MPPT）技术，该技术使用在临界导通模式下工作的交错升压变换器。与传统方法不同，通过分析单个开关周期内的瞬时电感电流和PV电压来检测最大功率点（MPP），从而可以在微秒级内精确确定MPP。交错升压拓扑显著降低了输入电流纹波，从而最大限度地减少了MPP周围的功率振荡，提高了整体系统效率。该算法在不同辐照度和温度条件下连续采样电感电流和PV电压，计算瞬时功率，并相应地更新开关频率。在40w光伏面板上进行的实验验证表明，当光伏系统运行在标称功率的65%以上时，该方法的精度高达99.5%。与传统的变阻方法相比，MPPT技术具有响应速度快、精度高、功率波动小等优点，为下一代光伏能量转换系统提供了一种高效的解决方案。

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