International Journal of Electrical Power & Energy Systems最新文献_第6页

Multi-time scale coordinated dispatch of integrated electricity-hydrogen-heat microgrids with waste heat recovery 带余热回收的电-氢-热一体化微电网多时间尺度协同调度

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

International Journal of Electrical Power & Energy Systems

Pub Date : 2026-02-01 DOI: 10.1016/j.ijepes.2026.111634

Lihua Zhong , Feiwei Li , Junwei Zhang , Bozheng Yuan , Jie Chen , Weijia Yang , Yongjian Zhao

Hydrogen energy plays a crucial role in integrating renewable, reducing carbon emissions, and boosting the operational flexibility of multi-energy microgrids (MEMG), owing to its substantial storage capacity and clean characteristics. However, a key challenge arises in the coordinated dynamic dispatch between power flows and the multi-stage hydrogen value chain, which includes production, conversion, utilization, and waste heat recovery. To address this, we introduce a novel multi-time scale operational framework for MEMG that considers electricity-hydrogen coupling and encompass the entire hydrogen process chain. This framework operates on a three-phase model: day-ahead scheduling aimed at minimizing daily operating costs; intraday rolling optimization every 15 min to adjust for renewable energy fluctuations; and real-time adjustments to fine-tune key conversion devices. Additionally, a carbon emission flow is integrated into the day-ahead phase to guide the dispatch of hydrogen and electricity towards low-carbon operations. Case studies demonstrate that our proposed framework lowers total operating costs by 6.64% and cuts carbon emissions by 13.06% compared to traditional day-ahead scheduling. This work offers a practical, system-level operational strategy to enhance both the economic and environmental performance of future flexible energy systems.

氢能由于其巨大的存储容量和清洁特性，在整合可再生能源、减少碳排放和提高多能源微电网（MEMG）的运行灵活性方面发挥着至关重要的作用。然而，在电力流和多级氢价值链（包括生产、转化、利用和余热回收）之间的协调动态调度中出现了一个关键挑战。为了解决这个问题，我们为MEMG引入了一种新的多时间尺度操作框架，该框架考虑了电-氢耦合，并涵盖了整个氢工艺链。该框架以三个阶段的模型运行：日前调度，旨在最大限度地减少日常运营成本；每隔15分钟进行盘中滚动优化，调整可再生能源波动；并实时调整微调键转换设备。此外，碳排放流被整合到日前阶段，以指导氢和电向低碳运营的调度。案例研究表明，与传统的提前调度相比，我们提出的框架降低了6.64%的总运营成本，减少了13.06%的碳排放。这项工作提供了一个实用的系统级操作策略，以提高未来灵活能源系统的经济和环境绩效。

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引用次数: 0

A probabilistic analysis method for the impact of traction load and wind power on power grid voltage quality based on Shapley value incorporating spatial correlation and uncertainty 基于空间相关和不确定性相结合的Shapley值的牵引负荷和风电对电网电压质量影响概率分析方法

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.2026.111603

Yulong Che , Dengfeng Wang , Xianxian Qiu , Xumeng Zhang , Limiao Ren , Wentao Zhang

With the increasing integration of traction power supply systems (TPSS) and wind farms into power grids, existing assessment methods are difficult to apply for quantifying the interactive effects of multiple uncertainties on grid voltage quality. A probabilistic assessment method based on Shapley value is proposed to evaluate voltage quality impacts in regional power grids containing both railway traction systems and wind power. Firstly, a non-parametric probabilistic modeling method based on adaptive kernel density estimation (AKDE) is proposed for traction loads and wind power, with its accuracy being validated. Secondly, an improved Latin Hypercube Sampling (LHS) method incorporating equal probability transformation and Cholesky decomposition techniques is developed to enable efficient sampling of correlated random variables. Then, a three-phase probabilistic load flow (3PLF) model incorporating an asymmetric traction substation is established. The method for assessing the probabilistic impact of traction loads and wind power on regional power grid voltage quality is proposed by combining 3PLF with Shapley value theory. Finally, the case validation is conducted in a modified IEEE 14-bus three-phase system using measured traction load and wind power data. Results show that when the operating trains at the traction substation change from one HX_D1 to three HX_D2s, the probability of the three-phase voltage unbalance degree exceeding the limit at the traction load bus increases by 10 %. The research results provide a theoretical basis and decision-making tool for voltage quality management in regional power grids with high wind power penetration integrated with TPSS.

随着牵引供电系统（TPSS）与风电场并网程度的提高，现有的评估方法难以量化多种不确定因素对电网电压质量的交互影响。提出了一种基于Shapley值的区域电网电压质量影响概率评估方法，用于既有铁路牵引系统又有风电的区域电网电压质量影响评估。首先，提出了一种基于自适应核密度估计（AKDE）的牵引负荷和风电非参数概率建模方法，并对其精度进行了验证。其次，提出了一种改进的拉丁超立方采样（LHS）方法，结合等概率变换和Cholesky分解技术，实现了相关随机变量的高效采样。然后，建立了考虑非对称牵引变电站的三相概率潮流模型。将3PLF理论与Shapley值理论相结合，提出了牵引负荷和风电对区域电网电压质量的概率影响评估方法。最后，利用实测的牵引负荷和风力数据，在改进的IEEE 14总线三相系统中进行了案例验证。结果表明，当牵引变电所运行列车由1列HXD1改为3列hxd2时，牵引负荷母线三相电压不平衡程度超过限值的概率增加10%。研究结果为结合TPSS的高风电场区域电网电压质量管理提供了理论依据和决策工具。

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引用次数: 0

Optimal preventive control for static voltage stability of integrated transmission and distribution networks under multiple N-1 contingencies considering uncertain renewables 考虑不确定可再生能源的多N-1突发事件下综合输配电网络静态电压稳定性的最优预防控制

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.2026.111617

Kaiyun Jiang, Shunjiang Lin, Yuerong Yang, Leyi Deng, Mingbo Liu

To maintain the secure operation of integrated transmission and distribution networks (ITDNs) with renewables, an optimal preventive control (OPC) method for static voltage stability of ITDNs under multiple N-1 contingencies considering uncertain renewables is proposed in this paper. In the OPC model, the uncertain power outputs of renewable energy stations are described as intervals, and the lower bounds of the static voltage stability margin (SVSM) intervals of ITDNs under both normal operation state and multiple N-1 contingencies are required to meet the allowable security thresholds. The original OPC model is a three-level optimization model including multiple bi-level optimization problems for computing the lower bounds of SVSM intervals, which is difficult to solve directly. To address this, the constraints of multiple SVSM intervals are simplified to the active constraints of the SVSM interval of the most severe state by introducing the fault parameters. Next, a simplification method based on Galerkin approximation is proposed to obtain the relationship between the injected power at the boundary connection bus and key variables of a distribution network (DN), and the operational constraints of each DN are simplified to several second-order cone inequality constraints. Then, the three-level optimization model is converted into a single-level optimization model through convex relaxation, dual convex programming, and Karush-Kuhn-Tucker condition construction. Thus, the preventive control scheme of ITDNs is obtained by solving the single-level optimization model. Case studies on a modified IEEE 39-33&69 bus ITDNs and an actual 2285-bus ITDNs demonstrate the correctness and effectiveness of the proposed method.

为了保证可再生能源综合输配网的安全运行，提出了一种考虑不确定可再生能源的N-1多事件下综合输配网静态电压稳定的最优预防控制方法。在OPC模型中，将可再生能源电站的不确定输出功率描述为区间，要求itdn在正常运行状态和多个N-1突发事件下的静态电压稳定裕度（SVSM）区间下界满足允许的安全阈值。原OPC模型是一个三层优化模型，包含多个计算SVSM区间下界的双层优化问题，难以直接求解。为了解决这一问题，通过引入故障参数，将多个支持向量机区间的约束简化为最严重状态下支持向量机区间的活动约束。其次，提出了一种基于伽辽金近似的简化方法，得到了配电网边界连接总线注入功率与关键变量之间的关系，并将各配电网的运行约束简化为若干二阶锥不等式约束。然后，通过凸松弛、对偶凸规划和Karush-Kuhn-Tucker条件构造，将三层优化模型转化为单层优化模型。因此，通过求解单级优化模型得到itdn的预防控制方案。对改进的IEEE 39-33&；69总线itdn和实际的2285总线itdn进行了实例研究，证明了所提出方法的正确性和有效性。

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引用次数: 0

Stability analysis and seamless mode transition for a hybrid battery formation and grading testing system 混合动力电池成形分级测试系统的稳定性分析及无缝模式转换

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.2026.111637

Di Xie , Longyun Kang , Jigang Yao , Liangliang Wang , Xiangzhen Yang , Zhipeng Yu , Pengpeng Zhou

The battery formation and grading testing system (BFGTS) is core equipment for battery activation, performance testing, and grading process. The grid-forming (GFM) inverters emerge as the promising solution for BFGTS to address instability issues induced by grid-following (GFL) inverters under weak grid conditions. Nevertheless, the stability of hybrid battery formation and grading testing system integrating both GFM and GFL inverters has become increasingly complex, presenting two critical challenges that demand urgent solutions: assessing the capacity ratio of GFM inverters for oscillation suppression and developing a seamless transition method between GFL and GFM mode under different current dynamics. Hence, a broadband sequence impedance considering the frequency coupling effect of the hybrid system is established and verified in this study. The influences of control parameters, capacity ratio and grid strength are analyzed in detail to reveal the stability mechanism. As the capacity ratio of GFM inverters increases, their low output impedance dominate the system, which effectively shrinks the capacitive negative damping region and thereby suppresses oscillations. However, an excessively high GFM ratio further increases the system’s stability risk under weak grid conditions. Additionally, a novel mode switching method integrating adaptive virtual impedance and feedforward control is proposed. Its advantage is that it can effectively suppress current surges and achieve seamless mode switching, even with different current loop structures and parameters between GFM and GFL control loops. Finally, simulation results of a BFGTS with six inverters validate the correctness of the stability analysis and the effectiveness of the proposed mode switching method.

电池形成与分级测试系统（BFGTS）是电池激活、性能测试和分级过程的核心设备。成网逆变器是解决弱电网条件下随网逆变器引起的不稳定问题的理想解决方案。然而，集成GFM和GFL逆变器的混合电池形成分级稳定性测试系统变得越来越复杂，提出了两个迫切需要解决的关键挑战：评估GFM逆变器抑制振荡的容量比，以及开发不同电流动态下GFL和GFM模式之间的无缝转换方法。因此，本文建立并验证了考虑混合系统频率耦合效应的宽带序列阻抗。详细分析了控制参数、容量比和网架强度对稳定性的影响，揭示了稳定机理。随着GFM逆变器容量比的增加，其低输出阻抗在系统中占主导地位，有效地缩小了电容负阻尼区域，从而抑制了振荡。然而，过高的GFM比率进一步增加了系统在弱电网条件下的稳定风险。此外，还提出了一种结合自适应虚拟阻抗和前馈控制的模式切换方法。其优点是即使GFM和GFL控制环之间的电流环结构和参数不同，也能有效抑制电流浪涌，实现无缝模式切换。最后，对6台逆变器组成的BFGTS进行了仿真，验证了稳定性分析的正确性和模式切换方法的有效性。

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引用次数: 0

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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