International Journal of Electrical Power & Energy Systems最新文献_第7页

Coordinated sizing of battery and charging systems for underground mining electric trucks 井下矿用电动卡车电池和充电系统的协调尺寸

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-02-01 DOI: 10.1016/j.ijepes.2026.111652

Seyed Nasrollah Hashemian, Hirad Assimi, Hossein Ranjbar, S. Ali Pourmousavi, Wen L. Soong

The heavy reliance on diesel-powered haul trucks in underground mines contributes substantially to CO₂ emissions and poses significant health risks to workers. Electrification of haul trucks offers a promising way to address these challenges, yet designing charging system in this constrained environment involves complex trade-offs between cost, productivity, and technical feasibility. This paper presents a novel optimisation-based framework for the coordinated sizing of onboard batteries and charging systems in underground operations, explicitly considering the interactions between battery size, payload capacity, charge rate, battery degradation, and regenerative braking. Three charging technologies, including fast charging, battery swapping, and trolley-assist, are systematically compared using tailored design models through rigorous net-present cost analysis over the mine’s operational life. The framework assesses how essential operational elements, such as the minimum viable battery capacity, frequency of charging cycles, length of the trolley, and motor efficiency, impact cost and productivity results. Simulation results for a hypothetical mine reveal distinct Pareto-optimal frontiers for each charging technology, highlighting how optimal choices shift under varying technical and economic conditions. This framework provides mining planners with a quantitative basis for selecting charging strategies that balance capital and operating costs with sustained productivity.

地下矿山严重依赖柴油动力运输卡车，这大大增加了二氧化碳的排放，并对工人的健康构成重大威胁。运输卡车的电气化为解决这些挑战提供了一条很有希望的途径，然而在这种受限的环境下设计充电系统需要在成本、生产率和技术可行性之间进行复杂的权衡。本文提出了一种新的基于优化的框架，用于协调地下运行中车载电池和充电系统的尺寸，明确考虑电池尺寸、有效载荷容量、充电速率、电池退化和再生制动之间的相互作用。通过严格的矿山运营寿命净现值成本分析，采用量身定制的设计模型，系统地比较了三种充电技术，包括快速充电、电池交换和手推车辅助。该框架评估了基本的操作要素，如最小可行电池容量、充电周期频率、小车长度和电机效率，如何影响成本和生产率结果。对一个假设矿山的模拟结果揭示了每种充电技术的不同帕累托最优边界，突出了最优选择在不同技术和经济条件下的变化。这一框架为采矿规划人员提供了选择收费战略的数量基础，以平衡资本和业务成本与持续生产力。

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引用次数: 0

Smart assessment of the unified power system efficiency in the context of smart grid: an ideal point–based multi-criteria method 智能电网背景下统一电力系统效率的智能评估：一种理想的基于点的多准则方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-02-01 DOI: 10.1016/j.ijepes.2026.111644

Iryna Bashynska , Viktoriia Kryvda , Vladyslav Suvorov , Liubov Niekrasova , Maksym Maksymov , Oleksii Maksymov

This article proposes a unified approach for assessing the operational efficiency of a Unified Power System (UPS) within the evolving Smart Grid environment. The method is based on an ideal-point evaluation framework that integrates the analysis of electricity supply volume, quality, and efficiency into a single generalized performance criterion. Instead of the previously used parameter convolution, the study employs a weighted L₁ norm–based distance to the ideal point, ensuring mathematical rigor and comparability with modern multi-criteria optimization techniques. The approach enables a comprehensive assessment of key performance indicators, including supply reliability, voltage stability, and consumption efficiency. The paper also provides numerical examples that illustrate the applicability of the proposed model and demonstrate its sensitivity to system-level parameters. The results confirm that the developed method can support decision-making for enhancing UPS operational efficiency and guiding Smart Grid modernization toward sustainable and resilient energy development.

本文提出了一种在不断发展的智能电网环境中评估统一电力系统（UPS）运行效率的统一方法。该方法基于一个理想点评估框架，该框架将供电量、质量和效率的分析整合到一个单一的通用性能标准中。与之前使用的参数卷积不同，该研究采用了加权的基于L1范数的理想点距离，确保了数学的严谨性和与现代多准则优化技术的可比性。该方法能够对关键性能指标进行全面评估，包括供电可靠性、电压稳定性和用电效率。文中还给出了数值算例，说明了所提模型的适用性和对系统级参数的敏感性。结果证实，所开发的方法可以支持提高UPS运行效率的决策，并指导智能电网现代化朝着可持续和有弹性的能源发展。

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引用次数: 0

Single-Phase high impedance ground fault location method based on transient directional characteristics 基于暂态方向特征的单相高阻抗接地故障定位方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-24 DOI: 10.1016/j.ijepes.2026.111621

Ao Li , Zengping Wang , Yufeng Zhao , Bo Wang , Tong Wang

After the single-phase high impedance fault (HIF) occurs in distribution networks, it is difficult to select the faulted feeder and locate the fault section due to the weak fault current and susceptibility to noise interference. To address this, a novel fault location method based on transient directional characteristics is proposed. Firstly, the phase-frequency characteristics of the zero-sequence equivalent impedance and nodal zero-sequence voltages are analytically derived using boundary conditions at the line terminal. Secondly, an adaptive time–frequency window for transient signals is selected through cross wavelet transform. By exploiting the correlation between local transient zero-sequence differential voltage and transient zero-sequence current, the transient direction discrimination method is proposed. Furthermore, considering the sensitivity degradation in section localization caused by weak transient zero-sequence current at line terminals, the transient energy criterion is constructed. The integration of transient directional and energy information enables precise faulted section localization. Finally, numerical simulations verify the sensitivity and reliability of the proposed method under both arc discharge and strong noise conditions. Crucially, the method requires lower sampling rates than traveling-wave protection, demonstrating substantial practical value.

配电网单相高阻故障发生后，由于故障电流较弱且易受噪声干扰，给故障馈线的选择和故障区段的定位带来困难。针对这一问题，提出了一种基于暂态方向特征的故障定位方法。首先，利用线端边界条件解析推导了零序等效阻抗和节点零序电压的相频特性；其次，通过交叉小波变换选择暂态信号的自适应时频窗；利用局部暂态零序差分电压与暂态零序电流之间的相关性，提出了暂态方向判别方法。此外，考虑到线路末端微弱瞬态零序电流引起的截面定位灵敏度下降，构造了瞬态能量判据。瞬态方向信息和能量信息的集成，使断层段定位更加精确。最后，通过数值仿真验证了该方法在电弧放电和强噪声条件下的灵敏度和可靠性。重要的是，该方法比行波保护需要更低的采样率，显示出很大的实用价值。

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引用次数: 0

An alienation-coefficient based fault detection method for DC microgrid 基于疏离系数的直流微电网故障检测方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-24 DOI: 10.1016/j.ijepes.2026.111626

Mohammad Amin Jarrahi , Mehdi Jabareh Nasero , Haidar Samet , Teymoor Ghanbari , Kamyar Mehran

This paper introduces an Alienation-Coefficient (AC)-based fault detection method for DC microgrids (DCMGs). In this approach, the measured currents from one end of the poles are first transformed into modal components. These modal currents are then processed using the concept of correlation. Subsequently, a signal termed the Protection Signal (PS) is defined by correlating the modal current with respect to the moving window theory. This signal exhibits negligible fluctuations during normal operation but experiences significant variations following a fault occurrence, making it suitable for indicating faults. The AC-based method is applied to the PS to characterize these changes, resulting in the formulation of a Fault Detection Index (FDI). Comparison of FDI with a predefined threshold allows for fault detection. Additionally, the FDI can differentiate between faulty conditions across various operational modes of the DCMG, accommodating a wide range of fault scenarios. To evaluate the performance of the developed scheme, a DCMG with different types of sources and loads is simulated in MATLAB/Simulink. The results demonstrate the speed and high accuracy of the proposed technique. Furthermore, the method is validated using an experimental laboratory small-scale test bench. Finally, a comparative study with recent fault detection methods is presented to highlight the method’s superiority.

介绍了一种基于疏离系数（AC）的直流微电网故障检测方法。在这种方法中，首先将两极一端的测量电流转换为模态分量。然后使用相关的概念对这些模态电流进行处理。随后，通过将模态电流与移动窗口理论相关联来定义一个称为保护信号（PS）的信号。该信号在正常运行时的波动可以忽略不计，但在故障发生后会发生显著变化，因此适用于指示故障。将基于交流的方法应用于PS来表征这些变化，从而形成故障检测指数（FDI）。FDI与预定义阈值的比较允许进行故障检测。此外，FDI可以在DCMG的各种运行模式中区分故障情况，适应各种故障场景。为了评估该方案的性能，在MATLAB/Simulink中对具有不同类型源和负载的DCMG进行了仿真。结果表明，该方法速度快，精度高。最后，在实验室小型试验台上对该方法进行了验证。最后，通过与现有故障检测方法的对比研究，突出了该方法的优越性。

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引用次数: 0

Data-driven coordinated dispatch of source-grid-load-storage systems with renewable energy resources and storage integration 可再生能源-储能一体化的源网负荷-储能系统数据驱动协同调度

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-23 DOI: 10.1016/j.ijepes.2026.111625

Jie Qian , Min Wei , Ping Wang , Weisheng He

In response to the global imperative of green energy transition, this paper investigates data-driven coordinated dispatch strategies for source-grid-load-storage (S-G-L-S) systems integrating distributed energy resources (DERs) and energy storage (ES). Traditional centralized power systems suffer from inefficiency and inflexibility, motivating data-driven coordination of DERs and ES to enhance operational reliability and renewable energy utilization. This paper proposes a comprehensive S-G-L-S coordinated dispatch framework to address key challenges such as renewable intermittency, load uncertainty, and multi-objective optimization. The contributions of this study are threefold. First, a three-tier power data analysis framework is developed by integrating Gaussian Mixture Model (GMM)–based anomaly detection, seasonal-trend decomposition with linear interpolation for data cleansing, and a long short-term memory (LSTM) network for time-series power data forecasting. Second, an improved salp swarm algorithm (ISSA) is introduced, incorporating hierarchical evaluation, re-update mechanism for suboptimal followers, and dynamic leader rotation to enhance DER-ES coordinated dispatch. Moreover, a multi-objective extension of ISSA, ISSA-MO, is developed by integrating Pareto non-dominated sorting and constraint-handling preferences to effectively balance trade-offs among energy loss, voltage stability, and grid dependency. Experimental validation on IEEE 33-, 69- and 119-node systems demonstrates that ISSA reduces active power loss by up to 98.11% and minimizes daily energy loss, while ISSA-MO generates well-distributed Pareto fronts for multi-objective S-G-L-S dispatch. The results demonstrate improvements in economic efficiency, operational reliability, and environmental sustainability, providing valuable insights for the development of global low-carbon power systems.

为应对全球绿色能源转型的迫切需要，本文研究了分布式能源（DERs）和储能（ES）集成的源-网-负荷-储能（S-G-L-S）系统的数据驱动协调调度策略。传统的集中式电力系统效率低下，缺乏灵活性，这促使数据驱动的DERs和ES协调，以提高运行可靠性和可再生能源的利用率。本文提出了一个综合的S-G-L-S协调调度框架，以解决可再生能源间歇性、负荷不确定性和多目标优化等关键挑战。这项研究的贡献有三个方面。首先，结合基于高斯混合模型（GMM）的异常检测、基于季节趋势分解的线性插值数据清洗和基于长短期记忆（LSTM）网络的时间序列电力数据预测，构建了一个三层电力数据分析框架。其次，引入改进的salp群算法（ISSA），结合分层评估、次优follower的重新更新机制和动态leader轮换，增强DER-ES协同调度；此外，通过整合帕累托非支配排序和约束处理偏好，开发了ISSA的多目标扩展ISSA- mo，以有效地平衡能量损失、电压稳定性和电网依赖性之间的权衡。在IEEE 33、69和119节点系统上的实验验证表明，ISSA可将有功功率损耗降低98.11%，使日能量损耗最小化，而ISSA- mo可生成分布良好的Pareto前线，用于多目标S-G-L-S调度。结果表明，在经济效率、运行可靠性和环境可持续性方面有所改善，为全球低碳电力系统的发展提供了有价值的见解。

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引用次数: 0

Short-term photovoltaic power forecasting under complex meteorological conditions: a physics-driven classification and hybrid deep learning framework 复杂气象条件下的短期光伏发电预测：物理驱动分类和混合深度学习框架

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-23 DOI: 10.1016/j.ijepes.2026.111600

Mao Yang , Zhenpeng Guo , Yitao Li , Da Wang , Xin Su

Existing classification methods often suffer from insufficient physical interpretability, and single prediction models exhibit weak generalization capabilities under complex scenarios. This paper proposes a short-term photovoltaic power forecasting (STPVPF) method based on a physically driven classification and hybrid deep learning framework. First, a Fluctuation Energy Loss Index (FELI) is proposed to quantify the degree of volatility, and four fluctuation scenario labels with explicit physical significance are established by combining the Jenks natural breaks algorithm. Second, the Hilbert-Huang Transform (HHT) is introduced to extract the nonlinear time–frequency features of Numerical Weather Prediction (NWP) data. A ShuffleNet module embedded with a Parallel Multi-dimensional Attention (PMDA) mechanism is then utilized to achieve high-precision identification of the target day’s scenario. Subsequently, a novel hybrid architecture, ResNet-CTformer, is constructed. This architecture effectively integrates the residual learning of ResNet, the local feature extraction of CNNs, and the global temporal modeling advantages of Transformers, thereby overcoming the bottleneck of network degradation and enhancing the robustness of long-sequence forecasting. Finally, an empirical study based on a PV power station in Jilin Province demonstrates that the proposed method possesses significant advantages in accuracy, with NRMSE and NMAE reduced by 16.91% and 14.59% on average compared to existing mainstream methods.

现有的分类方法往往存在物理可解释性不足的问题，单一的预测模型在复杂场景下泛化能力较弱。提出了一种基于物理驱动分类和混合深度学习框架的短期光伏功率预测（STPVPF）方法。首先，提出波动能量损失指数（FELI）来量化波动程度，并结合Jenks自然中断算法建立4个具有明确物理意义的波动场景标签。其次，引入Hilbert-Huang变换（HHT）提取数值天气预报资料的非线性时频特征。然后利用嵌入并行多维注意（PMDA）机制的ShuffleNet模块实现对目标日场景的高精度识别。随后，构建了一种新的混合架构ResNet-CTformer。该体系结构有效地融合了ResNet的残差学习、cnn的局部特征提取和Transformers的全局时序建模优势，从而克服了网络退化的瓶颈，增强了长序列预测的鲁棒性。最后，基于吉林省某光伏电站的实证研究表明，该方法在精度上具有显著优势，与现有主流方法相比，NRMSE和NMAE平均降低了16.91%和14.59%。

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引用次数: 0

Adaptive reclosing scheme for flexible HVDC grid with single-pole ground fault based on residual voltage zero-crossing detection 基于残压过零检测的单极接地故障柔性直流电网自适应重合闸方案

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-23 DOI: 10.1016/j.ijepes.2025.111519

Yue Dai , Hongchun Shu , Yutao Tang , Feng Gong

To avoid the issue of blind reclosing in conventional flexible high voltage direct current (HVDC) grid, investigating an adaptive reclosing scheme capable of identifying fault nature and duration is essential. This paper proposes a single-pole ground fault adaptive reclosing scheme based on residual voltage zero-crossing detection for flexible HVDC grid equipped with hybrid DC circuit breakers (HDCCB). First, the working principle of HDCCB and the expressions of residual voltage under different fault natures are analysed. Secondly, based on the zero-crossing detection principle, the differences in zero-crossing characteristics before and after the fault are used to identify the fault nature and calculate the fault duration. Finally, a flexible HVDC grid model is developed using the real-time digital simulator (RTDS) platform to verify the proposed scheme through simulation. The results demonstrate that the adaptive reclosing scheme accurately identifies fault nature and calculates fault duration with an error margin of less than 3 ms, exhibiting significant tolerance to fault resistance.

为了避免传统柔性高压直流（HVDC）电网的盲目重合闸问题，研究一种能够识别故障性质和持续时间的自适应重合闸方案至关重要。提出了一种基于剩余电压过零检测的单极接地故障自适应重合闸方案，该方案适用于带有混合直流断路器的柔性直流电网。首先，分析了HDCCB的工作原理和不同故障性质下的剩余电压表达式。其次，基于过零检测原理，利用故障前后过零特征的差异来识别故障性质并计算故障持续时间；最后，利用实时数字模拟器（RTDS）平台建立了一个灵活的高压直流电网模型，通过仿真验证了所提出的方案。结果表明，自适应重合闸方案能准确识别故障性质，计算故障持续时间，误差小于3 ms，对故障电阻有较好的容错性。

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引用次数: 0

A fuzzy-based dual-port virtual inertia controller for enhancing dynamic performance in hybrid microgrids 一种提高混合微电网动态性能的模糊双端口虚拟惯性控制器

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-23 DOI: 10.1016/j.ijepes.2025.111497

Yan Du, Jinxing Wang, Pengyu Chong, Xiangzhen Yang, Meiqin Mao

In hybrid microgrids (HMGs), reduced deviations and global power sharing can be expected by utilizing the interlinking converters (ILCs). However, the HMGs struggle to manage an optimal inertial response by interconnecting multiple AC/DC microgrids with the distinctive inertia requirements. Therefore, a dual-port virtual inertia controller is proposed in this paper by introducing normalized AC/DC inertia in ILCs. In order to transfer the virtual inertia without sacrificing the settling time and damping performance, a two-layer fuzzy logic incorporating a contraction factor is utilized to adjust the value of virtual inertia adaptively. The fuzzy logic is designed based on the constraints of power rating, damping ratio, settling time, and AC/DC microgrids inertia requirements, using a small-signal model of the HMGs. The proposed controller is validated under diverse operational conditions using a StarSim hardware-in-the-loop (HIL) experimental platform.

在混合微电网（hmg）中，可以通过使用互连转换器（ilc）来减少偏差和实现全局功率共享。然而，hmg很难通过连接多个具有独特惯性要求的交流/直流微电网来管理最佳惯性响应。因此，本文通过在ilc中引入归一化交直流惯量，提出了一种双端口虚拟惯量控制器。为了在不牺牲沉降时间和阻尼性能的前提下传递虚拟惯量，采用了一种包含收缩因子的双层模糊逻辑自适应调整虚拟惯量的值。基于微电网的小信号模型，基于额定功率、阻尼比、稳定时间和交直流微电网惯性要求的约束，设计了模糊逻辑。利用StarSim硬件在环（HIL）实验平台在不同的操作条件下对所提出的控制器进行了验证。

引用次数: 0

Hierarchical control optimization of AC systems in urban rail stations for regenerative energy use with start-stop constraints 带启停约束的城市轨道交通可再生能源交流系统层次控制优化

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-22 DOI: 10.1016/j.ijepes.2025.111446

Junjie Lin , Minghao Yang , Xiaofeng Jiang , Yachao Zhang , Shilong Cai , Chao Lu

To overcome the inefficiencies in regulating air conditioning (AC) systems in urban rail stations, which limit the effective absorption of megawatt-level regenerative braking energy (RBE) from the traction power supply system (TPSS), this paper introduces a robust and feasible hierarchical optimization control framework. The framework incorporates minimum start-stop time constraints while minimizing communication costs. At the cluster layer, response mechanisms for each AC are developed to maximize RBE utilization. At the aggregation layer, tailored regulation plans are designed to mitigate peak-to-valley variations in the energy supplied by the power grid to the AC loads. Finally, at the device layer, AC units strictly adhere to their individualized control plans, reducing switching frequency, optimizing RBE utilization, and minimizing energy fluctuations from the power grid. Case studies demonstrate that the proposed approach enhances RBE utilization by 17 % and reduces the standard deviation of grid-supplied energy to the AC systems by 33 %, thereby significantly contributing to energy savings in urban rail systems.

针对城市轨道交通车站空调系统调节效率低下，限制了从牵引供电系统（TPSS）中有效吸收兆瓦级再生制动能量的问题，提出了一种鲁棒可行的分层优化控制框架。该框架结合了最小的启停时间限制，同时最小化了通信成本。在集群层，为每个AC开发响应机制，以最大限度地利用RBE。在聚合层，量身定制的调节计划旨在减轻电网向交流负载提供的能量的峰谷变化。最后，在设备层，交流机组严格执行各自的个性化控制方案，降低开关频率，优化RBE利用率，最大限度地减少电网的能量波动。案例研究表明，所提出的方法将RBE利用率提高了17%，并将电网向交流系统提供的能源的标准偏差降低了33%，从而大大有助于城市轨道系统的节能。

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引用次数: 0

Preventive dispatch method for coordinated topology optimization of transmission and distribution networks 输配电网络协同拓扑优化的预防性调度方法

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-01-22 DOI: 10.1016/j.ijepes.2025.111537

Zheng Li, Juan Su

Extreme disasters, such as typhoons, can cause serious damage to lines, which poses a significant threat to the power supply of critical loads. An effective approach to enhance supply security is the flexible adjustment of the power system topology to redirect power flows and optimize load transfer. However, many studies have addressed optimal transmission switching (OTS) and distribution network reconfiguration (DNR) in isolation, with limited research on coordinated transmission and distribution topology optimization for improving resilience. This gap may result in overly conservative preventive dispatch strategies and an underestimation of resilience. To overcome these limitations, this paper incorporates coordinated topology optimization measures, including OTS, DNR, and post‑fault line repair, into a unified preventive scheduling framework to withstand disasters. An improved alternating direction method of multipliers (ADMM) algorithm, with a penalty multiplier updating strategy based on objective function deviation, is employed to solve the proposed preventive scheduling model. Finally, the proposed method is validated by two modified test systems. In the test system consisting of one IEEE-118 and five IEEE-33 bus systems, the results indicate an 8.91% reduction in load shedding and a 2.89% decline in total cost.

台风等极端灾害会对线路造成严重破坏，对关键负载的供电构成重大威胁。灵活调整电力系统拓扑结构，实现潮流重定向和负荷优化转移是提高供电安全的有效途径。然而，许多研究将最优输配电（OTS）和配网重构（DNR）孤立地进行了研究，而对提高电网弹性的协调输配电拓扑优化研究较少。这一差距可能导致过度保守的预防性调度策略和对复原力的低估。为了克服这些局限性，本文将OTS、DNR和故障后线路修复等协同拓扑优化措施纳入到统一的预防性调度框架中，以抵御灾害。采用改进的交替方向乘法器（ADMM）算法，结合基于目标函数偏差的惩罚乘法器更新策略，对所提出的预防性调度模型进行了求解。最后，通过两个改进的测试系统对所提方法进行了验证。在由1个IEEE-118总线系统和5个IEEE-33总线系统组成的测试系统中，结果表明减载减少了8.91%，总成本下降了2.89%。

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引用次数: 0