Global Energy Interconnection最新文献_第7页

Self-reduction multi-head attention module for defect recognition of power equipment in substation 变电站电力设备缺陷识别自缩多头关注模块

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.11.016

Yifeng Han, Donglian Qi, Yunfeng Yan

Safety maintenance of power equipment is of great importance in power grids, in which image-processing-based defect recognition is supposed to classify abnormal conditions during daily inspection. However, owing to the blurred features of defect images, the current defect recognition algorithm has poor fine-grained recognition ability. Visual attention can achieve fine-grained recognition with its ability to model long-range dependencies while introducing extra computational complexity, especially for multi-head attention in vision transformer structures. Under these circumstances, this paper proposes a self-reduction multi-head attention module that can reduce computational complexity and be easily combined with a Convolutional Neural Network (CNN). In this manner, local and global features can be calculated simultaneously in our proposed structure, aiming to improve the defect recognition performance. Specifically, the proposed self-reduction multi-head attention can reduce redundant parameters, thereby solving the problem of limited computational resources. Experimental results were obtained based on the defect dataset collected from the substation. The results demonstrated the efficiency and superiority of the proposed method over other advanced algorithms.

在电网中，电力设备的安全维护非常重要，而基于图像处理的缺陷识别则需要对日常检查中的异常情况进行分类。然而，由于缺陷图像的模糊特征，目前的缺陷识别算法的细粒度识别能力较差。视觉注意以其对远程依赖关系建模的能力实现了细粒度识别，但也带来了额外的计算复杂度，特别是对于视觉转换结构中的多头注意。在这种情况下，本文提出了一种自约简多头注意力模块，该模块可以降低计算复杂度，并且易于与卷积神经网络（CNN）相结合。通过这种方式，我们提出的结构可以同时计算局部和全局特征，从而提高缺陷识别的性能。具体而言，本文提出的自约简多头注意力可以减少冗余参数，从而解决了计算资源有限的问题。基于从变电站收集的缺陷数据集，得到了实验结果。结果表明，该方法与其他先进算法相比具有效率和优越性。

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引用次数: 0

Technical and economic feasibility assessment for hybrid energy system electricity and hydrogen generation: A case study 电力和氢气混合能源系统的技术和经济可行性评估：一个案例研究

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2025.01.001

Paul C. Okonkwo , Samuel Chukwujindu Nwokolo , El Manaa Barhoumi , Ibrahim B. Mansir , Usman Habu Taura , Barun Kumar Das , Ahmed Bahgat Radwan , Wilfred Emori , Ephraim Bonah Agyekum , Khalid Al Kaaf

Hydrogen is emerging as a promising alternative to fossil fuels in the transportation sector.This study evaluated the feasibility of establishing hydrogen refueling stations in five cities in Oman, Duqm, Haima, Sur, Al Buraymi, and Salalah, using Hybrid Optimization of Multiple Electric Renewables (HOMER) software. Three hybrid energy systems, photovoltaic-wind turbine-battery, photovoltaic-battery, and wind turbine-battery were analyzed for each city. Results indicated that Duqm offers the lowest net present cost (NPC), levelized cost of energy, and levelized cost of hydrogen, making it the most cost-effective location. Additionally, Sensitivity analysis showed that as the life of electrolyzer increases during operation, the initial capital expenditure is distributed over a longer operational period, leading to a reduction in the NPC. More so, renewable energy systems produced no emissions which supports Oman’s mission target. This comprehensive analysis confirms the feasibility of establishing a hydrogen refueling station in Duqm, Oman, and highlights advanced optimization techniques’ superior capability in designing cost-effective, sustainable energy systems.

氢正在成为运输部门化石燃料的一个有前途的替代品。本研究评估了在阿曼、杜库姆、海马、苏尔、Al Buraymi和Salalah五个城市建立加氢站的可行性，使用多种电力可再生能源的混合优化（HOMER）软件。针对每个城市分别对光伏-风力发电机组-电池、光伏-电池和风力发电机组-电池三种混合能源系统进行了分析。结果表明，Duqm提供最低的净现值成本（NPC）、能源平准化成本和氢平准化成本，使其成为最具成本效益的地点。此外，敏感性分析表明，随着电解槽在运行期间寿命的增加，初始资本支出分布在更长的运行期内，导致NPC减少。更重要的是，可再生能源系统不产生任何排放，这支持了阿曼的任务目标。这项综合分析证实了在阿曼Duqm建立加氢站的可行性，并强调了先进的优化技术在设计具有成本效益的可持续能源系统方面的卓越能力。

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引用次数: 0

Integrated paralleling of NPC inverters with suppressed circulating current for high-power renewable energy conversion 抑制环流的NPC逆变器集成并联用于大功率可再生能源转换

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.12.001

Weiwei Li , Guoxiang Hua , Xing Huang , Xueguang Zhang

The development of renewable energy power generation for carbon neutrality and energy transition has been increasing worldwide, leading to an increasing demand for high-power conversion. Compared with traditional interleaved paralleling, the integrated paralleling of three-level inverters can further reduce the output harmonics. Moreover, a well-designed switching sequence ensures that the average circulating current is zero, which provides a superior and feasible solution to satisfy the demands of high-power operations. However, a large instantaneous loop current exists between shunt converters, which leads to disadvantages such as higher switching device stress and loss. In this study, by utilizing the state-distribution redundancy provided by the integrated modulation process, a new design for switching sequences is suggested for the integrated modulation of shunt three-level converters. This design aims to reduce the circulating current while better preserving the same output current harmonics than traditional parallel methods. The proposal includes an in-depth analysis and explanation of the implementation process. Finally, the proposed method is validated through simulations and prototype experiments. The results indicate that compared with traditional methods, the adoption of the improved switching sequence presented in this study leads to an average reduction of 3.2 % in the total harmonic distortion of the inverter’s output and an average decrease of 32 % in the amplitude of the circulating current. Both the output harmonics and circulating currents are significantly suppressed across various modulation indices.

在世界范围内，为实现碳中和和能源转型而发展的可再生能源发电不断增加，导致对大功率转换的需求不断增加。与传统的交错并联相比，三电平逆变器集成并联可以进一步降低输出谐波。此外，设计良好的开关顺序确保了平均循环电流为零，为满足大功率运行需求提供了优越可行的解决方案。然而，并联变换器之间存在较大的瞬时回路电流，导致开关器件应力和损耗增大等缺点。本文利用集成调制过程提供的状态分布冗余，提出了一种并联三电平变换器集成调制的开关序列设计方法。与传统的并联方式相比，该设计旨在减少循环电流，同时更好地保持相同的输出电流谐波。该建议包括对执行过程的深入分析和解释。最后，通过仿真和样机实验对所提方法进行了验证。结果表明，与传统方法相比，采用改进的开关顺序可使逆变器输出总谐波失真平均降低3.2%，循环电流幅值平均降低32%。在不同的调制指数下，输出谐波和循环电流都得到了明显的抑制。

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引用次数: 0

Flexible region aggregation of adjustable loads via an adaptive convex hull strategy 基于自适应凸包策略的可调负荷柔性区域聚合

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.11.015

Yisha Lin , Zongxiang Lu , Ying Qiao , Ruijie Chen

Increasing interest has been directed toward the potential of heterogeneous flexible loads to mitigate the challenges associated with the increasing variability and uncertainty of renewable generation. Evaluating the aggregated flexible region of load clusters managed by load aggregators is the crucial basis of power system scheduling for the system operator. This is because the aggregation result affects the quality of the scheduling schemes. A stringent computation based on the Minkowski sum is NP-hard, whereas existing approximation methods that use a special type of polytope exhibit limited adaptability when aggregating heterogeneous loads. This study proposes a stringent internal approximation method based on the convex hull of multiple layers of maximum volume boxes and embeds it into a day-ahead scheduling optimization model. The numerical results indicate that the aggregation accuracy can be improved compared with methods based on one type of special polytope, including boxes, zonotopes, and homothets. Hence, the reliability and economy of the power system scheduling can be enhanced.

随着可再生能源发电的变异性和不确定性的增加，人们对异构柔性负荷的潜力越来越感兴趣。对负荷聚合器管理的负荷集群的聚合柔性区域进行评估是电力系统调度的重要依据。这是因为聚合结果会影响调度方案的质量。基于Minkowski和的严格计算是np困难的，而现有的使用特殊类型多面体的近似方法在聚合异构负载时表现出有限的适应性。本文提出了一种基于多层最大容积箱凸包的严格内逼近方法，并将其嵌入到日前调度优化模型中。数值结果表明，与基于一种特殊多面体的方法相比，该方法的聚集精度可以得到提高，包括盒形多面体、带形多面体和同源多面体。从而提高电力系统调度的可靠性和经济性。

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引用次数: 0

Distribution network gray-start and emergency recovery strategy with pumped storage unit under a typhoon 台风下抽水蓄能机组配电网灰启动及应急恢复策略

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.07.002

Zhenguo Wang , Hui Hou , Chao Liu , Shaohua Wang , Zhengtian Li , Xiangning Lin , Te Li

Typhoons can cause large-area blackouts or partial outages of distribution networks. We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework. A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first stage. This provides guidance for second-stage post-disaster emergency recovery scheduling. The emergency recovery scheduling model is established in the second stage, and this model is supported by a thermal power-generating unit, mobile emergency generators, and distributed generators. Distributed generation includes wind power generation, photovoltaics, fuel cells, etc. Simultaneously, we consider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery strategy. This model is validated on the improved IEEE 33 node system, which utilizes data from the 2022 super typhoon “Muifa” in Zhoushan, Zhejiang, China. Simulations indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.

台风会造成大面积停电或配电网部分中断。将配电网局部停电状态定义为灰色状态，提出了灰色启动策略和两阶段配电网应急恢复框架。第一阶段提出了台风灾害期间风电和光伏发电的相空间重建叠加综合预测模型。这为第二阶段灾后紧急恢复调度提供了指导。第二阶段建立应急恢复调度模型，该模型以火电机组、移动应急发电机和分布式发电机为支撑。分布式发电包括风力发电、光伏发电、燃料电池等。同时，我们认为基于抽水蓄能机组的灰启动是应急恢复策略中重要的第一步。该模型在改进的IEEE 33节点系统上进行了验证，该节点系统利用了2022年中国浙江舟山的超级台风“梅花”的数据。仿真结果表明了抽水蓄能机组灰色启动的优越性和提出的应急恢复策略。

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引用次数: 0

Hash-based FDI attack-resilient distributed self-triggered secondary frequency control for islanded microgrids 孤岛微电网基于哈希的FDI抗攻击分布式自触发二次频率控制

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.07.001

Xing Huang , Yulin Chen , Donglian Qi , Yunfeng Yan , Shaohua Yang , Ying Weng , Xianbo Wang

Given the rapid development of advanced information systems, microgrids (MGs) suffer from more potential attacks that affect their operational performance. Conventional distributed secondary control with a small, fixed sampling time period inevitably causes the wasteful use of communication resources. This paper proposes a self-triggered secondary control scheme under perturbations from false data injection (FDI) attacks. We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants. Subsequently, a hash-based defense mechanism (HDM) is designed for detecting and eliminating malicious data infiltrated in the MGs. With the aid of HDM, a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks. Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.

随着先进信息系统的快速发展，微电网面临越来越多的潜在攻击，影响其运行性能。传统的小采样周期、固定采样周期的分布式二次控制不可避免地造成通信资源的浪费。提出了一种在假数据注入（FDI）攻击扰动下的自触发二次控制方案。我们为每个DG设计了一个线性时钟，以在非周期和间歇时刻触发其控制器。随后，设计了一种基于哈希的防御机制（HDM），用于检测和消除恶意数据渗透。在HDM的帮助下，即使存在FDI攻击，自触发控制方案也能实现次要控制目标。严格的理论分析和仿真结果表明，引入的二次控制方案显著降低了通信成本，提高了mgg在FDI攻击下的恢复能力。

引用次数: 0

A coherent generator group identification algorithm under extreme conditions 一种极端条件下相干发电机组识别算法

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2025.01.002

Yizhe Zhu , Yulin Chen , Li Li , Donglian Qi , Jinhua Huang , Xudong Song

With the rapid development of large-scale regional interconnected power grids, the risk of cascading failures under extreme conditions, such as natural disasters and military strikes, has increased significantly. To enhance the response capability of power systems to extreme events, this study focuses on a method for generator coherency detection. To overcome the shortcomings of the traditional slow coherency method, this paper introduces a novel coherent group identification algorithm based on the theory of nonlinear dynamical systems. By analyzing the changing trend of the Euclidean norm of the state variable derivatives in the reduced system, the algorithm can accurately identify the magnitude of the disturbances. Based on the slow coherency methods, the algorithm can correctly recognize coherent generator groups by analyzing system characteristics under varying disturbance magnitudes. This improvement enhances the applicability and accuracy of the coherency detection algorithm under extreme conditions, providing support for emergency control and protection in the power system. Simulations and comparison analyses on IEEE 39-bus system are conducted to validate the accuracy and superiority of the proposed coherent generator group identification method under extreme conditions.

随着大规模区域互联电网的快速发展，在自然灾害和军事打击等极端条件下发生级联故障的风险显著增加。为了提高电力系统对极端事件的响应能力，本文研究了一种发电机相干检测方法。为了克服传统慢相干方法的不足，提出了一种基于非线性动力系统理论的相干群识别算法。通过分析化简后系统中状态变量导数欧氏范数的变化趋势，该算法可以准确识别扰动的大小。该算法基于慢相干方法，通过分析系统在不同扰动强度下的特性，能够正确识别出相干发电机组。这一改进提高了极端条件下相干检测算法的适用性和准确性，为电力系统的应急控制和保护提供了支持。通过对IEEE 39总线系统的仿真和对比分析，验证了该方法在极端条件下相干发电机组识别的准确性和优越性。

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引用次数: 0

A transient stability assessment method for power systems incorporating residual networks and BiGRU-attention 考虑残差网络和bigru注意的电力系统暂态稳定评估方法

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.09.001

Shan Cheng , Qiping Xu , Haidong Wang , Zihao Yu , Rui Wang , Tao Ran

The traditional transient stability assessment (TSA) model for power systems has three disadvantages: capturing critical information during faults is difficult, aperiodic and oscillatory unstable conditions are not distinguished, and poor generalizability is exhibited by systems with high renewable energy penetration. To address these issues, a novel ResGRU architecture for TSA is proposed in this study. First, a residual neural network (ResNet) is used for deep feature extraction of transient information. Second, a bidirectional gated recurrent unit combined with a multi-attention mechanism (BiGRU-Attention) is used to establish temporal feature dependencies. Their combination constitutes a TSA framework based on the ResGRU architecture. This method predicts three transient conditions: oscillatory instability, aperiodic instability, and stability. The model was trained offline using stochastic gradient descent with a thermal restart (SGDR) optimization algorithm in the offline training phase. This significantly improves the generalizability of the model. Finally, simulation tests on IEEE 145-bus and 39-bus systems confirmed that the proposed method has higher adaptability, accuracy, scalability, and rapidity than the conventional TSA approach. The proposed model also has superior robustness for PMU incomplete configurations, PMU noisy data, and packet loss.

传统的电力系统暂态稳定评估（TSA）模型存在三个缺点：故障时的关键信息捕获困难，不区分非周期和振荡不稳定状态，可再生能源渗透率高的系统泛化能力差。为了解决这些问题，本研究提出了一种新的TSA ResGRU架构。首先，利用残差神经网络（ResNet）对瞬态信息进行深度特征提取；其次，采用双向门控循环单元结合多注意机制（BiGRU-Attention）建立时间特征依赖关系。它们的组合构成了一个基于ResGRU架构的TSA框架。该方法预测了三种瞬态条件：振荡不稳定、非周期不稳定和稳定。在离线训练阶段，采用热重启（SGDR）优化算法的随机梯度下降法对模型进行离线训练。这大大提高了模型的泛化性。最后，在IEEE 145总线和39总线系统上进行了仿真测试，验证了该方法比传统的TSA方法具有更高的适应性、准确性、可扩展性和快速性。该模型对PMU不完全配置、PMU噪声数据和丢包具有较好的鲁棒性。

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引用次数: 0

Optimal power extraction of PV-TEG hybrid system via fitness-distance-balance-based beluga whale optimization 基于健身-距离-平衡的白鲸优化PV-TEG混合系统的最佳功率提取

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.10.014

Bo Yang , Boxiao Liang , Shaocong Wu , Hongbiao Li , Dengke Gao , Lin Jiang , Jingbo Wang

This study integrates the individual photovoltaic (PV) and thermoelectric generator (TEG) systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational reliability. However, stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules, which negatively affect the output characteristics of the system, thus presenting a significant challenge to maintaining their optimal performance. To address these challenges, a novel fitness-distance-balance-based beluga whale optimization (FDBBWO) strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenarios. A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO. For this, real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy. Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output, with a remarkable increase of up to 134.25 % with minimal power fluctuations. For instance, the energy obtained by FDBBWO is 47.45 % and 58.34 % higher than BWO and perturb and observe methods, respectively, in the winter season.

本研究将单独的光伏（PV）和热电发电机（TEG）系统整合为一个PV-TEG混合系统，通过再利用光伏发电过程中产生的余热来提高其整体功率输出，以提高其运行可靠性。然而，随机环境条件通常会导致PV-TEG模块的部分遮阳条件和不均匀的热分布，这对系统的输出特性产生负面影响，从而对保持其最佳性能提出了重大挑战。为了解决这些问题，研究人员设计了一种基于适应度-距离平衡的新型白鲸优化（FDBBWO）策略，以最大化PV-TEG混合动力系统在动态运行场景下的功率输出。在个案研究中考虑了更广泛的复杂和真实的业务情况，以审查FDBBWO的有效性和可行性。为此，我们使用了在香港不同季节收集的真实数据集来验证建议策略的实际可行性。仿真结果表明，基于FDBBWO的最大功率点跟踪技术在功率波动最小的情况下实现了最高的能量输出，显著提高了134.25%。在冬季，FDBBWO法比BWO法、摄动法和观测法获得的能量分别高出47.45%和58.34%。

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引用次数: 0

Security distance analysis of active distribution network considering energy hub demand response 考虑能源枢纽需求响应的有源配电网安全距离分析

IF 1.9 Q4 ENERGY & FUELS

Global Energy Interconnection

Pub Date : 2025-02-01 DOI: 10.1016/j.gloei.2024.10.013

Rui Ma , Qi Zhou , Shengyang Liu , Qin Yan , Mo Shi

This study proposes a method for analyzing the security distance of an Active Distribution Network (ADN) by incorporating the demand response of an Energy Hub (EH). Taking into account the impact of stochastic wind-solar power and flexible loads on the EH, an interactive power model was developed to represent the EH’s operation under these influences. Additionally, an ADN security distance model, integrating an EH with flexible loads, was constructed to evaluate the effect of flexible load variations on the ADN’s security distance. By considering scenarios such as air conditioning (AC) load reduction and base station (BS) load transfer, the security distances of phases A, B, and C increased by 17.1 %, 17.2 %, and 17.7 %, respectively. Furthermore, a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm, the NSGA-II multi-objective optimization algorithm, and the maximum satisfaction method. The simulation results of the IEEE33 node system example demonstrate that after optimization, the total energy cost for one day is reduced by 0.026 %, and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA. This method effectively enhances the security distance, facilitates BS load transfer and AC load reduction, and contributes to the energy-saving, economical, and safe operation of the power system.

本研究提出一种纳入能源枢纽（EH）需求响应的有源配电网（ADN）安全距离分析方法。考虑随机风力-太阳能发电和柔性负荷对EH的影响，建立了代表EH在这些影响下运行的交互功率模型。此外，构建了集成EH和柔性负荷的ADN安全距离模型，以评估柔性负荷变化对ADN安全距离的影响。考虑空调减载、基站转移等场景，A、B、C相安全距离分别增长17.1%、17.2%、17.7%。建立了多目标最优潮流模型，并采用前向-后向潮流算法、NSGA-II多目标优化算法和最大满意度法进行求解。IEEE33节点系统实例的仿真结果表明，优化后的ADN一天总能耗降低0.026%，三相总安全距离限制提高0.1 MVA。该方法有效地增大了安全距离，有利于BS负荷的转移和交流负荷的减少，有利于电力系统的节能、经济、安全运行。

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引用次数: 0