Electric Power Systems Research最新文献_第4页

A power quality enhancement using gradient descent-fuzzy logic controller in grid-connected PV system 基于梯度下降模糊控制器的并网光伏系统电能质量增强

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.2026.112746

Balaji Janapati, Nageswara Rao Pulivarthi

In recent years, the integration of renewable energy sources, particularly Photovoltaic (PV) systems into the power grid have introduced critical power quality issues. These issues primarily arise from the dynamic behavior of related power electronic converters and the intermittent nature of solar generation. Traditional standalone Maximum Power Point Tracking (MPPT) algorithms repeatedly suffered from poor adaptability, slow dynamic response under varying conditions, and insufficient harmonic reduction. These limitations degraded grid performance and inefficient energy withdrawal from PV systems. To overcome these challenges, this research proposes a novel hybrid approach that integrates Gradient Descent optimization with a Fuzzy Logic Controller (GD-FLC). The proposed controller is applied to a 100-kW grid connected PV system, incorporating an LC filter and MPPT-based boost converter to adjust voltage and improve power quality. The proposed GD-FLC attains fastest MPPT tracking time (0.29 s) under irradiance variation, and (0.28 s) under load variation, along with the lowest average rise time (0.0117 s). Similarly, it achieved output energy (160.72KJ) under step variation and 150.49KJ under ramp variation, clearly outperforming existing MPPT techniques. The GD-FLC controller offers an effective solution for grid-connected PV systems by attaining 89.82 kW for grid load and 80.09 kW for non-linear load respectively.

近年来，将可再生能源，特别是光伏（PV）系统并入电网带来了关键的电能质量问题。这些问题主要来自相关电力电子转换器的动态行为和太阳能发电的间歇性。传统的单机最大功率点跟踪（MPPT）算法存在自适应性差、动态响应慢、谐波抑制不足等问题。这些限制降低了电网性能，降低了光伏系统的能量提取效率。为了克服这些挑战，本研究提出了一种将梯度下降优化与模糊逻辑控制器（GD-FLC）相结合的新型混合方法。该控制器应用于100kw并网光伏系统，结合LC滤波器和基于mpt的升压变换器来调节电压并改善电能质量。在辐照度变化和负载变化条件下，GD-FLC的MPPT跟踪时间最短（0.29 s），平均上升时间最短（0.0117 s）。同样，它在阶跃变化下的输出能量为160.72KJ，在斜坡变化下的输出能量为150.49KJ，明显优于现有的MPPT技术。GD-FLC控制器为光伏并网系统提供了有效的解决方案，电网负荷和非线性负荷分别达到89.82 kW和80.09 kW。

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引用次数: 0

A novel CDPFC for harmonic resonance suppression in offshore wind farms 一种用于海上风电场谐波抑制的新型CDPFC

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-24 DOI: 10.1016/j.epsr.2026.112763

Qingchuan Fan , Yu Deng , Yanhong Jiang , Yongjie Zhang , Yong Xu , Qiuqin Sun

Offshore wind farms (OWFs) are prone to harmonic resonance problems as it is delivered via submarine cables. Existing methods for harmonic resonance are mostly limited to specific conditions, and may fail when the operating condition of system changes. In this paper, a novel topology based on cascaded distributed power flow controller (CDPFC) is proposed. Its harmonic suppression effect is analyzed by connecting it in series to the OWFs. Optimization of DPFC units using cascaded H-bridge topology to improve harmonic tracking fitting capability. Using the harmonic voltages collected by Hanning-windowed discrete Fourier transform (DFT) as a reference, a dual-vector model predictive control (MPC) strategy with the objective of minimizing the voltage envelopment area is proposed. The method not only suppresses the resonance amplification problem caused by background harmonics, but also optimizes the power quality of the grid in multiple frequency bands. The harmonic content of the grid-connected voltage is greatly reduced through the precise control of the harmonic components.

海上风电场（owf）由于通过海底电缆输送，容易出现谐波共振问题。现有的谐波谐振方法大多局限于特定条件，当系统运行条件发生变化时可能失效。提出了一种基于级联分布式潮流控制器（CDPFC）的新型拓扑结构。通过将其串联到owf上，分析了其谐波抑制效果。采用级联h桥拓扑优化DPFC单元以提高谐波跟踪拟合能力。以汉宁窗离散傅立叶变换（DFT）采集的谐波电压为参考，提出了一种以电压包络面积最小为目标的双矢量模型预测控制策略。该方法不仅抑制了背景谐波引起的谐振放大问题，而且在多个频段优化了电网的电能质量。通过对谐波分量的精确控制，大大降低了并网电压的谐波含量。

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引用次数: 0

A multi-objective evolutionary algorithm with Pre-selection and self-adjusting mechanism for fault reconstruction in multi-load independent power distribution system 多负荷独立配电系统故障重构的多目标预选择自适应进化算法

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-24 DOI: 10.1016/j.epsr.2026.112770

Tianhao Gong, Dazhi Wang, Yupeng Zhang, Tianyi Li

Fault reconstruction is vital for the stability of expanding multi-load independent distribution systems. This paper presents an enhanced multi-objective optimization algorithm for fault reconstruction in multi-load independent distribution systems. The method improves upon existing algorithms by integrating a pre-selection mechanism for a superior initial population and self-adjusting strategies for efficient convergence. Combined with a novel network encoding technique, it accurately and efficiently identifies optimal reconstruction schemes. Validation results demonstrate that the approach efficiently determines optimal reconstruction schemes with higher accuracy.

故障重构对于扩容型多负荷独立配电系统的稳定运行至关重要。针对多负荷独立配电系统的故障重构问题，提出了一种改进的多目标优化算法。该方法在现有算法的基础上进行了改进，集成了优选初始种群的预选择机制和有效收敛的自调整策略。结合一种新颖的网络编码技术，准确、高效地识别出最优重构方案。验证结果表明，该方法能有效地确定最优重建方案，具有较高的精度。

引用次数: 0

A simultaneous wireless power and signal transfer system based on dual-frequency channel and power allocation 一种基于双频信道和功率分配的无线电力与信号同步传输系统

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.2026.112838

Xue-Jian Ge , Yi-Wen Wang , Ding-Qiang Ren , Ming-Hao Tang , Lei Wang

In wireless power transfer systems, communication between the transmitting and receiving sides is generally required to achieve efficient and stable power transmission. In this paper, a simultaneous wireless power and signal transfer system is proposed based on the dual-frequency channel power transfer topology. Under the premise of ensuring the stability of the total transmission power, the simultaneous transmission of signal is realized by changing the ratio between the fundamental and harmonic power, which does not require additional signal transmission channel and can simplify the structure of the system. This paper first introduces the topology structure of the proposed system and its power transmission principle, and then analyzes the operating principle of signal transmission, as well as modulation and demodulation methods. Considering the stability of power transmission, the signal transmission rate is analyzed. To reduce the mutual interference between power and signal transmission, the system parameters are designed and optimized. Based on the theoretical analysis, a simulation model is established to verify the simultaneous signal transmission. Finally, an experimental prototype is set up and tested. The experimental results verify that the proposed system can achieve stable simultaneous transmission of power and signal, with a signal transmission rate of up to 5kbps.

在无线电力传输系统中，为了实现高效、稳定的电力传输，通常需要发射端和接收端之间的通信。本文提出了一种基于双频信道功率传输拓扑的无线功率与信号同步传输系统。在保证总传输功率稳定的前提下，通过改变基波功率与谐波功率的比值来实现信号的同时传输，不需要额外的信号传输通道，可以简化系统结构。本文首先介绍了所提出系统的拓扑结构及其功率传输原理，然后分析了信号传输的工作原理，以及调制解调方法。考虑电力传输的稳定性，对信号传输速率进行了分析。为了减少功率和信号传输之间的相互干扰，对系统参数进行了设计和优化。在理论分析的基础上，建立了仿真模型，验证了信号的同步传输。最后，建立了实验样机并进行了测试。实验结果表明，该系统可以实现功率和信号的稳定同时传输，信号传输速率可达5kbps。

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引用次数: 0

Optimal capacity allocation for wind farm grid-forming units based on Markov transition field and soft actor-critic algorithm 基于马尔可夫过渡场和软行为者评判算法的风电场并网机组最优容量分配

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-08 DOI: 10.1016/j.epsr.2025.112689

Xinglong Fang , Yang Hu , Ziqiu Song , Jizhen Liu

With the increasing penetration of renewable energy in power system,grid-forming (GFM) control has become an important method to improve system stability. Nevertheless, the optimal allocation of GFM units that harmonizes dynamic performance with system stability has not yet been adequately addressed. To this end, this paper focuses on the optimization of the proportion of GFM units in wind farms. First, a modeling method based on the Markov transition field-based (MTF) is proposed to represent the dynamic evolution of wind farms under multi-stationary operating conditions. Second, a composite capacity evaluation indicator that jointly accounts for system stability and economic cost is introduced, providing a quantitative basis for assessing the grid-support capability of GFM units and guiding optimal capacity allocation. Finally, the Soft Actor-Critic (SAC) algorithm in reinforcement learning (RL) for capacity allocation is introduced and verified under typical disturbance conditions such as voltage dips and sudden changes in grid strength. Experimental results demonstrate that the proposed method effectively reduces voltage and frequency fluctuations by more than 7% and accelerates system response time, enabling faster frequency recovery and superior voltage regulation.

随着可再生能源在电力系统中的渗透程度不断提高，并网控制已成为提高系统稳定性的重要手段。然而，协调动态性能和系统稳定性的GFM单元的最佳分配尚未得到充分解决。为此，本文重点研究了GFM机组在风电场中的比例优化问题。首先，提出了一种基于马尔可夫过渡场（MTF）的多平稳运行条件下风电场动态演化建模方法。其次，引入了综合考虑系统稳定性和经济成本的综合容量评价指标，为评价GFM机组的并网能力和指导容量优化分配提供了定量依据。最后，介绍了用于容量分配的强化学习（RL）中的软行为者-批评家（SAC）算法，并在电压下降和电网强度突变等典型干扰条件下进行了验证。实验结果表明，该方法有效地降低了电压和频率波动7%以上，加快了系统响应时间，实现了更快的频率恢复和优越的电压调节。

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引用次数: 0

A mathematical analysis combined with machine-learning optimal control method for bidirectional converter devices of urban rail transit system 城市轨道交通系统双向变换器装置数学分析与机器学习相结合的最优控制方法

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-16 DOI: 10.1016/j.epsr.2026.112715

Jiajun Duan , Leipeng Hao , Yongtao Wang , Xiuming Han , Xiong Wei , Tingting Wang

This study proposes a Mathematical Analysis combined with Machine Learning (MAcML) optimal control method for bidirectional converters (BCs) in urban rail transit (URT) systems. To avoid the potential additional costs of a communication system, the MAcML method is designed for localized control of BCs. First, a mathematical analysis is performed to establish the underlying control mechanism—specifically, clustering URT daily operations into typical periods (e.g., workday peak, weekend flat) and reducing the BC control action space via a decoupled fast-search method. Subsequently, a machine learning approach is employed to predict unmeasured total energy consumption using local BC measurements. Finally, a dynamic model is constructed in a Controller-Hardware-in-the-Loop test bed to generate an optimal control-action table. Field tests on a real Chinese URT segment demonstrate that the proposed method achieves a 17.8 % reduction in net energy consumption compared to the natural droop control of BCs.

针对城市轨道交通（URT）系统中的双向变流器（bc），提出了一种结合数学分析和机器学习（MAcML）的最优控制方法。为了避免通信系统的潜在额外成本，MAcML方法被设计为局部控制bc。首先，进行数学分析以建立底层控制机制-具体而言，将URT日常操作聚类到典型时间段（例如，工作日高峰，周末平坦），并通过解耦快速搜索方法减少BC控制动作空间。随后，采用机器学习方法使用本地BC测量来预测未测量的总能耗。最后，在控制器-硬件在环试验台上建立了动态模型，生成了最优控制-动作表。在真实的中国轨道交通路段上进行的现场测试表明，与自然下垂控制相比，该方法实现了17.8%的净能耗降低。

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引用次数: 0

Analysis of PV hosting capacity in distribution grids considering users’ voltage-regulation responsibility under dynamic Time-of-Use pricing 动态分时电价下考虑用户调压责任的配电网光伏装机容量分析

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-10 DOI: 10.1016/j.epsr.2026.112713

Jun Qi, Yi Xu, Da Jiang, Dan Zhou

Due to the inherent intermittency and variability of solar energy, the increasing penetration of photovoltaic (PV) generation brings significant challenges to distribution grid operation. To enhance PV hosting capacity, it is crucial to fully leverage user-side flexible resources (FRs) within Internet of Things (IoT) environments. This paper proposes a dynamic time‑of‑use (TOU) pricing mechanism designed to guide demand response (DR) and mitigate PV power fluctuations by emphasizing user-side responsibility and advantages in voltage regulation. A Stackelberg game framework between the distribution system operator (DSO) and users is established, and a power fluctuation penalty (PFP) term reflecting voltage-regulation responsibility (VRR) is incorporated into user-side objective functions. When user-side FRs adjust their electricity consumption according to day-ahead dynamic TOU tariffs, voltage violations that limit PV hosting capacity can be effectively alleviated. Simulation results demonstrate that power fluctuations can be smoothed by considering user-side VRR, and the PV hosting capacity will be significantly raised by dynamic TOU, compared with constant or peak-valley pricing schemes.

由于太阳能固有的间歇性和可变性，光伏发电的日益普及给配电网的运行带来了巨大的挑战。为了提高光伏主机容量，在物联网环境中充分利用用户侧灵活资源（FRs）至关重要。本文提出了一种动态使用时间（TOU）定价机制，旨在通过强调用户侧责任和电压调节优势来引导需求响应（DR）并缓解光伏发电的波动。建立了配电系统运营商与用户之间的Stackelberg博弈框架，并将反映调压责任（VRR）的功率波动惩罚（PFP）项引入用户侧目标函数。当用户侧FRs根据日前动态分时电价调整其用电量时，可以有效缓解限制光伏主机容量的电压违规。仿真结果表明，考虑用户侧VRR的动态分时电价方案可以平滑电力波动，与固定电价或峰谷电价方案相比，动态分时电价方案可以显著提高光伏托管容量。

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引用次数: 0

Temporary measures for distribution network restoration after natural disasters 自然灾害后配电网恢复临时办法

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-30 DOI: 10.1016/j.epsr.2026.112788

Anmar Arif

Natural disasters can cause significant damage to distribution networks, resulting in power outages and widespread disruptions. To expedite power restoration under these conditions, utilities commonly employ temporary measures such as portable generators and temporary distribution lines. However, deciding when and where to implement these measures can be both complex and costly. In this paper, we present a mixed-integer linear programming (MILP) model that optimizes the selection and deployment of portable power sources and temporary lines for repairing and restoring unbalanced distribution systems following natural disasters. Our approach features a pre-processing step that systematically identifies potential (i.e., candidate) lines and buses suitable for temporary measures, thereby confining the main optimization to a tractable set of possibilities. Through case studies on the IEEE 123-bus distribution system, we demonstrate that the proposed formulation yields cost-effective and timely post-disaster restoration plans, integrating portable substations, generators, temporary lines, crew routing, and network reconfiguration.

自然灾害会对配电网造成重大破坏，导致停电和大范围的破坏。为了在这种情况下加快电力恢复，公用事业公司通常采用临时措施，如便携式发电机和临时配电线路。然而，决定何时何地实施这些措施既复杂又昂贵。本文提出了一种混合整数线性规划（MILP）模型，该模型可以优化移动电源和临时线路的选择和部署，以用于自然灾害后不平衡配电系统的修复和恢复。我们的方法具有一个预处理步骤，系统地识别适合临时措施的潜在（即候选）线路和总线，从而将主要优化限制在一组可处理的可能性上。通过对IEEE 123总线配电系统的案例研究，我们证明了所提出的方案可以产生成本效益高且及时的灾后恢复计划，包括便携式变电站、发电机、临时线路、机组路由和网络重构。

引用次数: 0

Coordinated power smoothing control for wind storage integrated system with physics-informed deep reinforcement learning 基于物理信息深度强化学习的风力存储集成系统功率平滑协调控制

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-01-09 DOI: 10.1016/j.epsr.2025.112707

Shuyi Wang , Huan Zhao , Yuji Cao , Zibin Pan , Guolong Liu , Gaoqi Liang , Junhua Zhao

The Wind Storage Integrated System with Power Smoothing Control (PSC) has emerged as a promising solution for efficient and reliable wind energy generation. However, existing PSC strategies exhibit several limitations. Many fail to capture the cooperative interactions and distinct control frequencies between wind turbines and battery energy storage systems (BESSs). In addition, the impacts of wake effects and battery degradation costs are often overlooked. This paper proposes a novel multi-agent coordinated control framework to address these challenges, which explicitly integrates a wake model and a battery degradation model to construct a more realistic operating environment. The problem is formulated as a multi-agent Markov decision process (MMDP), where the wind farm and the BESS agents pursue complementary objectives to achieve optimal control. Furthermore, a Physics-informed Neural Network-assisted Multi-agent Deep Deterministic Policy Gradient (PAMA-DDPG) algorithm is introduced, embedding a partial differential equation of power fluctuation as a physics-guided loss term to accelerate learning and enhance physical consistency. Simulations using WindFarmSimulator (WFSim) in four scenarios demonstrate that the proposed method outperforms benchmark approaches, achieving an 11% increase in total profit and a 19% reduction in power fluctuation. These results effectively address the dual objectives of economic efficiency and grid reliability.

具有功率平滑控制（PSC）的风力存储集成系统已成为高效可靠的风力发电的一种有前途的解决方案。然而，现有的PSC策略显示出一些局限性。许多方法未能捕捉到风力涡轮机和电池储能系统（BESSs）之间的合作相互作用和不同的控制频率。此外，尾流效应和电池退化成本的影响往往被忽视。本文提出了一种新的多智能体协调控制框架来解决这些挑战，该框架明确地集成了尾流模型和电池退化模型，以构建更真实的操作环境。该问题被表述为一个多智能体马尔可夫决策过程（MMDP），其中风电场和BESS智能体追求互补目标以实现最优控制。此外，还引入了一种基于物理的神经网络辅助多智能体深度确定性策略梯度（pma - ddpg）算法，该算法将功率波动的偏微分方程嵌入到物理指导的损失项中，以加速学习并增强物理一致性。使用WindFarmSimulator （WFSim）在四个场景中进行的仿真表明，所提出的方法优于基准方法，实现了总利润增加11%，功率波动减少19%。这些结果有效地解决了经济效率和电网可靠性的双重目标。

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引用次数: 0

Parameter optimization design of bidirectional CLLC resonant converter under variable frequency control 变频控制下双向CLLC谐振变换器参数优化设计

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

Electric Power Systems Research

Pub Date : 2026-06-01 Epub Date: 2026-02-10 DOI: 10.1016/j.epsr.2026.112834

Dangshu Wang , Zelong Hou , Licong Zhao , Guangzhen Wu , Nongke Li , Pengpeng Xie , Xinxia Wang

The bidirectional CLLC resonant converter exhibits the capability for bidirectional energy flow, along with significant advantages of high efficiency and high power density. However, traditional parameter design methods suffer from complex procedures and high computational difficulty. To address this issue, this paper employs the Fundamental Harmonic Analysis (FHA) method to model the CLLC resonant converter, deriving its voltage gain characteristics and the conditions required for achieving soft-switching. Based on the gain characteristics and soft-switching constraints, a simplified resonant network parameter design methodology integrating mathematical analytical expressions and graphical analysis is proposed. This method optimizes the design process and significantly reduces the complexity of parameter design. A 500 W laboratory prototype was built using the optimized parameters. Experimental results demonstrate that the prototype meets the voltage gain requirements while achieving soft-switching operation, with a forward power transmission efficiency of up to 97.6%, thereby validating the correctness of the theoretical analysis and the practical feasibility of the parameter optimization design.

双向CLLC谐振变换器具有双向能量流动的能力，具有显著的高效率和高功率密度的优点。但传统的参数设计方法程序复杂，计算难度大。为了解决这一问题，本文采用基谐波分析（FHA）方法对CLLC谐振变换器进行建模，推导出其电压增益特性和实现软开关所需的条件。基于增益特性和软开关约束，提出了一种结合数学解析表达式和图形分析的简化谐振网络参数设计方法。该方法优化了设计过程，显著降低了参数设计的复杂度。利用优化后的参数建立了500w的实验室样机。实验结果表明，样机在实现软开关工作的同时满足了电压增益要求，前向功率传输效率高达97.6%，从而验证了理论分析的正确性和参数优化设计的实际可行性。

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引用次数: 0