IET Energy Systems Integration最新文献

Experimental and model analysis of the thermoelectric characteristics of serial arc in prismatic lithium‐ion batteries 棱柱形锂离子电池串联电弧热电特性的实验和模型分析

IF 1.6 Q4 ENERGY & FUELS

IET Energy Systems Integration

Pub Date : 2024-07-24 DOI: 10.1049/esi2.12162

Wenqiang Xu, Languang Lu, Kai Zhou, Yalun Li, Bin Gao

Aiming at the electrical safety problems of lithium‐ion battery system due to series arc fault, a finite element simulation model of square battery under series arc fault is established based on the magnetohydro‐dynamic equations. The arc voltages at different electrode spacings are analysed, and the electric field distribution, magnetic field distribution, arc temperature and flow velocity around the arc are investigated to determine the maximum values and locations of the electric field strength, magnetic density, arc temperature and flow velocity at the time of the arc fault. Then, on the basis of the series arc experimental platform, determine the value of the arc starting voltage and the critical power supply voltage that produces a stable arc, analyse the evolution of the arc burning time with different loop currents, the evolution of the arc of the separation gap, and then summarise the effect of the disaster on the battery. Finally, the errors of simulation and experimental arc voltage and battery surface temperature are analysed to verify the accuracy of the model.

针对串联电弧故障引起的锂离子电池系统电气安全问题，基于磁流体动力学方程建立了串联电弧故障下方形电池的有限元仿真模型。分析了不同电极间距下的电弧电压，研究了电弧周围的电场分布、磁场分布、电弧温度和流速，确定了故障电弧发生时电场强度、磁密率、电弧温度和流速的最大值和位置。然后，在串联电弧实验平台的基础上，确定起弧电压值和产生稳定电弧的临界电源电压，分析不同环路电流下电弧燃烧时间的演变、分隔间隙电弧的演变，进而总结灾害对电池的影响。最后，分析了模拟与实验电弧电压和电池表面温度的误差，以验证模型的准确性。

引用次数: 0

Low‐carbon economic operation of multi‐energy microgrid based on multi‐level robust optimisation 基于多级鲁棒优化的多能源微电网低碳经济运行

IF 1.6 Q4 ENERGY & FUELS

IET Energy Systems Integration

Pub Date : 2024-07-21 DOI: 10.1049/esi2.12160

Wenwen He, Xiong Wu, Xiaofei Li, Mingkang He, Binrui Cao, Xiuli Wang

The economic and low‐carbon operation strategy of multi‐energy microgrids (MEM) has become an important research topic in smart grids. The operation of MEM is affected by uncertain factors from renewable energy and internal load. To handle uncertainties from both source and load sides, the authors propose a novel worst‐case‐and‐probability uncertainty sets and a novel worst‐expectation min‐max‐max‐min two‐stage four‐level robust optimisation (RO) model considering stepped carbon trading for MEM. This four‐level RO model is a more generalised model compared with the traditional two‐stage RO and distributionally robust optimisation based models. First, the unsolvable original four‐level model is decoupled into a master problem and a sub‐problem (SP). Second, Karush–Kuhn–Tucker condition is applied to convert SP into a solvable problem. Third, column and constraint generation (C&CG) algorithm is employed to solve the reformulated four‐level RO. Finally, the effectiveness of the proposed model and solution method is verified by case studies. The results indicate that the convergence behaviour of this solution method is excellent. The MEM operator can select appropriate robustness factors and comprehensive norms to control its conservatism level. Besides, MEM could reduce carbon emissions by participating in carbon trading and installing carbon capture devices.

多能源微电网（MEM）的经济和低碳运行策略已成为智能电网的一个重要研究课题。多能源微电网的运行受到可再生能源和内部负荷等不确定因素的影响。为了处理来自能源和负荷两方面的不确定性，作者提出了一种新的最坏情况和概率不确定性集，以及一种新的最坏预期最小-最大-最小两阶段四级鲁棒优化（RO）模型，其中考虑了针对 MEM 的阶跃碳交易。与传统的两阶段稳健优化模型和基于分布的稳健优化模型相比，该四级稳健优化模型是一个更具通用性的模型。首先，将无法解决的原始四级模型解耦为一个主问题和一个子问题（SP）。其次，应用 Karush-Kuhn-Tucker 条件将 SP 转换为可解问题。第三，采用列和约束生成（C&CG）算法求解重构的四级 RO。最后，通过案例研究验证了所提模型和求解方法的有效性。结果表明，这种求解方法的收敛性非常好。MEM 操作员可以选择适当的稳健性因子和综合规范来控制其稳健性水平。此外，MEM 还可以通过参与碳交易和安装碳捕获装置来减少碳排放。

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引用次数: 0

Anti‐interference lithium‐ion battery intelligent perception for thermal fault detection and localization 用于热故障检测和定位的抗干扰锂离子电池智能感知技术

IF 1.6 Q4 ENERGY & FUELS

IET Energy Systems Integration

Pub Date : 2024-07-08 DOI: 10.1049/esi2.12158

Luyu Tian, Chaoyu Dong, Rui Wang, Yunfei Mu, Hongjie Jia

Lithium‐ion batteries are widely employed in electric vehicles, power grid energy storage, and other fields. Thermal fault diagnostics for battery packs is crucial to preventing thermal runaway from impairing the safe operation and extended cycle service life of batteries. Therefore, a lithium‐ion battery thermal fault diagnosis model based on deep learning algorithms is presented, which includes three parts: autoencoder denoising network, coarse mask generator, and mask precise adjustment. Autoencoder denoising network can reduce data noise during thermal imaging acquisition, improve the anti‐interference ability of diagnostic models, and ensure the accuracy of thermal runaway diagnosis. A two‐stage diagnostic structure is then formulated by the coarse mask generator and mask precise adjustment, which enable quick identification, categorisation, and localisation of thermal fault battery cells. According to the test results, the segmentation boundary is more distinct and is capable of matching the original image's level. The recognition accuracy of the thermal diagnosis model for faulty batteries is close to 100%. After denoising by the autoencoder, the prediction results improved by 22% compared to non‐local mean denoising and by about 32% compared to noisy images.

锂离子电池广泛应用于电动汽车、电网储能和其他领域。电池组的热故障诊断对于防止热失控影响电池的安全运行和延长循环使用寿命至关重要。因此，本文提出了一种基于深度学习算法的锂离子电池热故障诊断模型，包括三个部分：自动编码器去噪网络、粗掩码生成器和掩码精确调整。自动编码器去噪网络可以降低热成像采集过程中的数据噪声，提高诊断模型的抗干扰能力，确保热失控诊断的准确性。然后，通过粗掩膜生成器和掩膜精确调整，形成两阶段诊断结构，从而实现对热故障电池单元的快速识别、分类和定位。测试结果表明，分割边界更加清晰，能够与原始图像的层次相匹配。热诊断模型对故障电池的识别准确率接近 100%。使用自动编码器去噪后，预测结果比非局部均值去噪提高了 22%，比噪声图像提高了约 32%。

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引用次数: 0

Estimation and prediction method of lithium battery state of health based on ridge regression and gated recurrent unit 基于脊回归和门控递归单元的锂电池健康状态估计和预测方法

IF 1.6 Q4 ENERGY & FUELS

IET Energy Systems Integration

Pub Date : 2024-07-02 DOI: 10.1049/esi2.12159

Ziwei Dai, Aikui Li, Wei Sun, Shenwu Zhang, Hao Zhou, Ren Rao, Quan Luo

The health state of lithium‐ion batteries is influenced by the operating conditions of energy storage stations and battery characteristics. It is challenging to obtain real‐time characterisation parameters like maximum discharge capacity and internal resistance. It is necessary to extract sensitivity indicators from electrical parameters such as voltage, current, and temperature. Utilising the Stanford‐MIT Research Institute battery dataset, this paper selects batteries with over 1000 cycles and five distinct charging and discharging strategies as samples. During the daily operation and maintenance of the energy storage station, health indicators are extracted from the voltage, current, and temperature curves within the state of charge range of 20%–80%. The ridge regression method is used to establish the health status estimation model. The gated recurrent unit (GRU) model is leveraged for health state prediction. Simulation results demonstrate that the proposed health indicators effectively assess lithium battery health, the health state estimation errors mean absolute error (MAE) and root mean squared error (RMSE) based on the ridge regression model are within 1.5% and 2%, and the health state prediction errors MAE and RMSE based on GRU model are within 1%. This approach exhibits stability, high accuracy, and strong generalisation capabilities.

锂离子电池的健康状态受到储能站运行条件和电池特性的影响。获取最大放电容量和内阻等实时特性参数具有挑战性。有必要从电压、电流和温度等电气参数中提取灵敏度指标。本文利用斯坦福-麻省理工学院研究所的电池数据集，选择了超过 1000 次循环和五种不同充放电策略的电池作为样本。在储能站的日常运行和维护过程中，从充电状态（20%-80%）范围内的电压、电流和温度曲线中提取健康指标。采用脊回归法建立健康状态估计模型。利用门控循环单元（GRU）模型进行健康状态预测。仿真结果表明，所提出的健康指标能有效评估锂电池的健康状况，基于脊回归模型的健康状态估计误差平均绝对误差（MAE）和均方根误差（RMSE）在 1.5% 和 2% 以内，基于 GRU 模型的健康状态预测误差平均绝对误差（MAE）和均方根误差（RMSE）在 1% 以内。这种方法具有稳定性、高准确性和强大的泛化能力。

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引用次数: 0

A reinforcement learning method for two‐layer shipboard real‐time energy management considering battery state estimation 考虑电池状态估计的双层舰载实时能源管理强化学习方法

IF 1.6 Q4 ENERGY & FUELS

IET Energy Systems Integration

Pub Date : 2024-07-02 DOI: 10.1049/esi2.12157

Huayue Zhang, Shuli Wen, Mingchang Gu, Miao Zhu, Huili Ye

Increasing global environmental concerns encourage a continuous reduction in carbon emissions from the shipping industry. It has become an irreversible trend to replace traditional fossil fuels with advanced energy storage technology. However, an improper energy management leads to not only energy waste but also undesired costs and emissions. Accordingly, the authors develop a two‐layer shipboard energy management framework. In the initial stage, a shipboard navigation planning problem is formulated that considers battery state estimation and is subsequently solved using particle swarm optimisation to obtain an optimal speed trajectory. To track the scheduled speed, a reinforcement learning method based on a deep Q‐Network is proposed in the second stage to realise real‐time energy management of the diesel generator and energy storage system. This approach ensures that the state of charge remains within a safe range and that the performance is improved, avoiding excessive discharge from the energy storage systems and further enhancing the efficiency. The numerical results demonstrate the necessity and effectiveness of the proposed method.

全球对环境的日益关注促使航运业不断减少碳排放。用先进的储能技术取代传统化石燃料已成为不可逆转的趋势。然而，不恰当的能源管理不仅会导致能源浪费，还会产生不必要的成本和排放。因此，作者开发了一个双层船上能源管理框架。在初始阶段，提出了一个考虑电池状态估算的船载导航规划问题，随后使用粒子群优化法进行求解，以获得最佳速度轨迹。为了跟踪预定速度，第二阶段提出了一种基于深度 Q 网络的强化学习方法，以实现柴油发电机和储能系统的实时能量管理。这种方法可确保充电状态保持在安全范围内，并提高性能，避免储能系统过度放电，进一步提高效率。数值结果证明了所提方法的必要性和有效性。

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引用次数: 0

Guest Editorial: Identification, stability analysis, control, and situation awareness of power systems with high penetrations of renewable energy resources 特邀社论：可再生能源高渗透率电力系统的识别、稳定性分析、控制和态势感知

IF 2.4 Q1 Engineering

IET Energy Systems Integration

Pub Date : 2024-06-09 DOI: 10.1049/esi2.12153

Tek Tjing Lie, Wenpeng Luan

It is with great pleasure that the authors introduce this special issue, commemorating the 8th Asia Conference on Power and Electrical Engineering held in Tianjin in 2023. This conference served as a nexus for researchers, practitioners, and industry experts from around the globe to convene and exchange cutting-edge insights, innovative ideas, and transformative advancements in the field of power and electrical engineering. The contributions featured in this special issue represent a diverse array of research endeavours, spanning from fundamental theories to practical applications, all aimed at addressing the myriad challenges and opportunities facing the power and electrical engineering domain. From novel methodologies in renewable energy integration to advancements in smart grid technologies, each article encapsulates the spirit of innovation and collaboration that characterised the conference. This special issue includes scientific investigations on topology modelling and virtual stability analysis methods for distribution networks with high penetration of renewable energy resources, monitoring and situation awareness on grid inertia and power-frequency evolution, novel voltage source converter control schemes, and reviews of low-carbon planning and operation of electricity, hydrogen fuel, and transportation networks.

作者非常高兴地介绍本特刊，以纪念 2023 年在天津举行的第八届亚洲电力与电气工程会议。本次会议为来自全球各地的研究人员、从业人员和行业专家提供了一个汇聚一堂的平台，共同交流电力与电气工程领域的前沿见解、创新思想和变革性进展。本特刊收录的论文代表了从基础理论到实际应用的各种研究成果，其目的都是为了应对电力和电气工程领域所面临的无数挑战和机遇。从可再生能源集成的新方法到智能电网技术的进步，每篇文章都体现了会议的创新与合作精神。本特刊包括对可再生能源高渗透率配电网拓扑建模和虚拟稳定性分析方法的科学研究、电网惯性和功率频率演变的监测和情况感知、新型电压源变流器控制方案，以及电力、氢燃料和交通网络的低碳规划和运行的综述。

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引用次数: 0

Analysis of voltage limit‐induced barrier for connecting inverter‐based distributed generators to medium voltage networks: Australian case studies 基于逆变器的分布式发电机与中压网络连接的电压极限诱发障碍分析：澳大利亚案例研究

IF 2.4 Q1 Engineering

IET Energy Systems Integration

Pub Date : 2024-06-04 DOI: 10.1049/esi2.12154

Mir Toufikur Rahman, M. Gu, Moudud Ahmed, Kazi N. Hasan, Lasantha Gunaruwan Meegahapola

Inverter‐based distributed generators (IBDGs), mainly solar photovoltaic, connected in medium‐voltage (MV) networks cause challenges, such as voltage limit violations, for distribution network service providers (DNSPs), and require advanced network management strategies to mitigate these challenges. A theoretical analysis of the voltage limit‐induced barrier to IBDG connection and their export limits due to the change in network characteristics is imperative for developing new strategies. The authors formulated a relationship between the network equivalent impedance and the IBDG's connection point in the network and further explored the link between the network equivalent impedance and voltage magnitude due to the IBDG connection point. The authors also assessed the voltage limit‐induced barrier to IBDG connections in MV networks and proposed solutions to overcome issues with the dynamic export limit of IBDGs. Four representative Australian MV networks are analysed in DIgSILENT PowerFactory under different scenarios, such as variation in IBDG location and static and dynamic export limits. The authors found that an IBDG connected at the end of the network can achieve better performance in supporting the network voltage. An IBDG with a dynamic export limit can export three times more energy than the static export limit, which benefits both the DNSPs and IBDG owners.

基于逆变器的分布式发电机（IBDGs），主要是太阳能光伏发电，连接到中压（MV）电网中会给配电网络服务提供商（DNSPs）带来挑战，如违反电压限制，因此需要先进的网络管理策略来缓解这些挑战。要制定新策略，就必须从理论上分析因网络特性变化而导致的电压极限引起的 IBDG 连接障碍及其出口限制。作者提出了网络等效阻抗与 IBDG 在网络中的连接点之间的关系，并进一步探讨了网络等效阻抗与 IBDG 连接点引起的电压幅值之间的联系。作者还评估了中压网络中由电压极限引起的 IBDG 连接障碍，并提出了克服 IBDG 动态输出极限问题的解决方案。在 DIgSILENT PowerFactory 中分析了澳大利亚四个具有代表性的中压电网在不同情况下的情况，如 IBDG 位置的变化以及静态和动态输出限制。作者发现，连接在电网末端的 IBDG 在支持电网电压方面能取得更好的性能。具有动态输出限制的 IBDG 输出的能量是静态输出限制的三倍，这对 DNSP 和 IBDG 所有者都有利。

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引用次数: 0

Transient overvoltage suppression of LCC-HVDC sending-end system based on DC current control optimisation 基于直流电流控制优化的 LCC-HVDC 送端系统瞬态过电压抑制

IF 2.4 Q1 Engineering

IET Energy Systems Integration

Pub Date : 2024-05-09 DOI: 10.1049/esi2.12150

Yang Wang, Jianhang Zhu, Yingbiao Li, Jiabing Hu, Shicong Ma, Tiezhu Wang

The receiving-end system AC fault of the line-commutated-converter-based high voltage direct current (LCC-HVDC) will lead to commutation failure of the inverter side. During the fault and its recovery, AC transient low voltage and transient overvoltage (TOV) will occur in the sending-end system. The TOV has the risk of triggering the disorderly off-grid of the nearby renewable power generations. Besides, in a serious situation, it will threaten the power system to maintain a secure and steady operation. Therefore, the authors analyse the mechanism involved in the AC transient voltage during the AC fault and the recovery period first. It reveals that the key factor causing the TOV of the sending-end system is the setting of the DC current reference value. Then, a DC current reference value limit method based on the AC TOV sampling value is proposed, which is used to accelerate DC current recovery and suppress the TOV of the sending-end system. Finally, the effectiveness of the designed control method has been confirmed through electromagnetic transient simulations using the CIGRE HVDC benchmark model and a ±800 kV HVDC transmission system model situated in Northwest China.

基于线路换向变流器的高压直流（LCC-HVDC）的接收端系统交流故障将导致变流器侧的换向故障。在故障及其恢复期间，发送端系统将出现交流暂态低电压和暂态过电压（TOV）。瞬态过电压有可能引发附近可再生能源发电的无序离网。此外，严重时还会威胁到电力系统的安全稳定运行。因此，作者首先分析了交流故障和恢复期间交流暂态电压的相关机理。结果表明，导致送端系统失压的关键因素是直流电流参考值的设置。然后，提出了一种基于交流 TOV 采样值的直流电流参考值限制方法，用于加速直流电流恢复和抑制发送端系统的 TOV。最后，通过使用 CIGRE 高压直流基准模型和位于中国西北地区的±800 千伏高压直流输电系统模型进行电磁暂态仿真，证实了所设计控制方法的有效性。

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引用次数: 0

Stability assessment of inverter‐based renewable energy sources integrated to weak grids 基于逆变器的可再生能源并入弱电网的稳定性评估

IF 2.4 Q1 Engineering

IET Energy Systems Integration

Pub Date : 2024-05-09 DOI: 10.1049/esi2.12151

M. I. Saleem, S. Saha, U. Izhar, L. Ang

The worldwide electricity network is undergoing a crucial transformation, shifting from traditional synchronous generators to inverter‐based renewable energy sources (IRESs). This shift is expected to reduce the grid's available fault level (AFL), potentially impacting grid functionality, particularly during the integration of IRESs into weak grids. This paper examines the challenges associated with weak grids, focusing on the steady‐state and dynamic stability of IRES when integrated into these systems. In the steady‐state analysis, the effects of AFL, injected power volume, and grid characteristics on the steady‐state voltage at the point of interconnection were explored. For dynamic stability, eigenvalue and H2 norm analyses are used for evaluation. Sensitivity analysis is conducted to assess the impact of these factors on the stability of IRESs connected to weak grids. A detailed case study using the IEEE 39 bus test power system is included to demonstrate our findings, where the steady‐state and dynamic stability of IRES connected to the test system are assessed using the proposed methods. The accuracy of these analyses is confirmed by extensive simulation studies on the OPAL‐RT real‐time digital simulator platform.

全球电网正在经历一场关键的变革，从传统的同步发电机转向基于逆变器的可再生能源（IRES）。预计这一转变将降低电网的可用故障水平（AFL），从而对电网功能造成潜在影响，尤其是在将 IRES 并入弱电网期间。本文探讨了与弱电网相关的挑战，重点关注集成到这些系统中的 IRES 的稳态和动态稳定性。在稳态分析中，探讨了 AFL、注入功率和电网特性对互联点稳态电压的影响。在动态稳定性方面，采用了特征值和 H2 准则分析进行评估。还进行了敏感性分析，以评估这些因素对连接到弱电网的 IRES 稳定性的影响。我们还利用 IEEE 39 总线测试电力系统进行了详细的案例研究，利用所提出的方法评估了连接到测试系统的 IRES 的稳态和动态稳定性。在 OPAL-RT 实时数字仿真器平台上进行的大量仿真研究证实了这些分析的准确性。

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引用次数: 0

Theoretical study on Stark effect of Rydberg atom in super low frequency electric field measurement 超低频电场测量中雷德贝格原子的斯塔克效应理论研究

IF 2.4 Q1 Engineering

IET Energy Systems Integration

Pub Date : 2024-04-14 DOI: 10.1049/esi2.12149

Hongtian Song, Yong Xiao, Shanshan Hu, Dongping Xiao, BaoShuai Wang, Zhuxin Shi, Huaiqing Zhang

Super low frequency electric field measurements are crucial in analysing electromagnetic compatibility, assessing equipment status, and other related fields. Rydberg atom-based super low frequency electric field measurements are performed by observing the Stark shift in the spectrum of the Rydberg state. In a specific range of field strength (E < E_avoid, where E_avoid is the threshold to avoid crossing electric fields), the Rydberg atomic spectrum experiences a quadratic frequency shift in relation to the field strength, with the coefficient being determined by the atomic polarisability α. The authors establish a dynamic equation for the interaction between the external electric field and the atomic system, and present the Stark structure diagram of the Caesium Rydberg atom. The mathematical formulae for α and E_avoid in different Rydberg states are also obtained: α = A × (n*)⁶ + B × (n*)⁷ and E_avoid = C/(n*)⁵ + D/(n*)⁷, where A(B) = 2.2503 × 10⁻⁹(7.49,948 × 10⁻¹¹) and C(D) = 1.68,868 × 10⁸(2.45,991 × 10⁹). The error of α and E_avoid compared with the experimental values does not exceed 8% and is even lower in the low Rydberg states. Accurately calculating the values of α and E_avoid is crucial in incorporating the Rydberg atom quantum coherence effect into super low frequency electric field measurements in new power systems.

超低频电场测量对于分析电磁兼容性、评估设备状态和其他相关领域至关重要。基于雷德贝格原子的超低频电场测量是通过观察雷德贝格态光谱中的斯塔克偏移来进行的。在特定的电场强度范围内（E < Eavoid，其中 Eavoid 是避免跨越电场的阈值），雷德贝格原子光谱会发生与电场强度相关的二次频移，其系数由原子极性 α 决定。作者建立了外部电场与原子系统之间相互作用的动态方程，并展示了铯雷德贝格原子的斯塔克结构图。同时还得到了不同雷德贝格态下 α 和 Eavoid 的数学公式：α = A × (n*)6 + B × (n*)7 和 Eavoid = C/(n*)5 + D/(n*)7, 其中 A(B) = 2.2503 × 10-9(7.49,948 × 10-11) 和 C(D) = 1.68,868 × 108(2.45,991 × 109)。与实验值相比，α 和 Eavoid 的误差不超过 8%，在低雷德贝格态甚至更低。准确计算 α 和 Eavoid 值对于将雷德贝格原子量子相干效应纳入新型电力系统的超低频电场测量至关重要。

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引用次数: 0