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2022 4th International Conference on Power and Energy Technology (ICPET)最新文献

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A CL-MDT Method of Multi-energy Load Forecasting in Integrated Energy System 综合能源系统多能量负荷预测的CL-MDT方法
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918348
T. Zheng, Gang Liu, Wei Cheng, Pingzhao Hu, Y. Wang
Source-load scheduling is based on multi-energy-load forecasting. The integrated energy system mainly includes three types of energy: electricity, cooling and heating. Studying the correlation among electricity, cooling and heating may improve the accuracy of multi-energy-load forecasting. This paper considers the correlation of three energy sources, fully analyzes the correlation, and applies the correlation of the three in the forecasting model. This paper proposes a CL-MDT (CNN-LSTM-Multi-Decoder-Transformer) model for multi-energy-load forecasting. The model is based on the Transformer, and the Multi-Head Attention part in the Encoder is replaced by a 2dimensional 3*3 CNN (Convolutional Neural Network) feature extraction module for feature extraction of data. And a 1dimensional CNN feature extraction module and LSTM structure are added to the Decoder. The structure of single Encoder and multiple Decoders is used in this paper to realize the application of the correlation of the three in the forecasting model. Finally, the model is tested on public datasets and the forecasting results of CL-MDT are compared with that of LSTM model for multi-energy-load joint forecasting. The results show that the CL-MDT model proposed in this paper has better forecasting accuracy.
源负荷调度是基于多能负荷预测的。综合能源系统主要包括三种能源:电、冷、热。研究电、冷、热三者之间的相关性,可以提高多能负荷预测的准确性。本文考虑了三种能源的相关性,充分分析了三者的相关性,并将三者的相关性应用于预测模型中。本文提出了一种用于多能负荷预测的CL-MDT (CNN-LSTM-Multi-Decoder-Transformer)模型。该模型基于Transformer,将编码器中的多头注意力部分替换为二维3*3 CNN(卷积神经网络)特征提取模块,对数据进行特征提取。在解码器中加入一维CNN特征提取模块和LSTM结构。本文采用单编码器和多解码器的结构,实现三者的相关性在预测模型中的应用。最后,在公共数据集上对模型进行了测试,并将CL-MDT模型与LSTM模型的多能负荷联合预测结果进行了比较。结果表明,本文提出的CL-MDT模型具有较好的预测精度。
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引用次数: 0
Generator Damping Evaluation Considering Different Forced Oscillation Sources 考虑不同强迫振荡源的发电机阻尼评估
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918472
Dongrong Jiang, Junjie Zhang, Wentao Zhang, Chao Yang, Y. Jia
The frequency range of forced oscillation is wide distributed due to various types of disturbances, thus the evaluation of generator damping under different forced oscillation is crucial for the stable operation of modern power system. This paper is intended to explore the damping characteristics of generator under forced oscillation with different oscillation frequencies. Firstly, the energy dissipation of the generator was analyzed based on the oscillating energy flow method. Secondly, the energy dissipation of generator components such as excitation control system, governor control system and other windings of the generator was further investigated. Finally, three scenarios considering internal or external disturbance locations were tested in the dual-machine system to explore the energy dissipation variation of each generator component at different frequencies. Simulation results show that the generator with disturbance inside may provide positive damping at a certain frequency, however, the energy emitted by the source device is much larger than other non-source device, which can be used as an indication for the precise location of oscillation source.
由于各种类型的干扰,强迫振荡的频率范围分布很广,因此评估不同强迫振荡下发电机的阻尼对现代电力系统的稳定运行至关重要。本文旨在探讨发电机在不同振动频率的强迫振动下的阻尼特性。首先,基于振荡能量流法对发电机的能量耗散进行了分析。其次,进一步研究了发电机励磁控制系统、调速器控制系统和发电机其他绕组等发电机部件的耗能问题。最后,在双机系统中测试了三种考虑内部或外部扰动位置的场景,探讨了发电机各部件在不同频率下的能量耗散变化。仿真结果表明,内部有扰动的发生器在一定频率下可以提供正阻尼,但源装置发射的能量远大于其他非源装置,这可以作为振荡源精确定位的指示。
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引用次数: 0
Numerical Study on Transient Magnetic Field inside Ultra High-Rise Building during Lightning Stroke 雷击时超高层建筑内部瞬变磁场数值研究
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918423
Qibin Zhou, Jingjie Ye, Yanyong Mao, Zhen Yang
Transient electromagnetic field will endanger the safety and normal operation of personnel and equipment inside the an ultra high-rise building when lightning strikes at it. The electromagnetic field method is more efficient to analyze the electromagnetic environment of lightning strike at large and complex buildings. By adopting the finite element method (FEM) in the frequency domain, the electromagnetic field method is used to evaluate the magnetic field in a building and validated by comparing with experiment results. With this method, a simplified model of the 488.9m ultra high-rise building, Chengdu Zhonghai Tower, is established and the magnetic field distribution inside this building is evaluated and analyzed. The simulation results are valuable for optimizing the installation of sensitive equipment in this building and can also give guidelines for improving the design of the lightning protection system (LPS) of ultra high-rise buildings.
超高层建筑被雷击时,会产生瞬变电磁场,危及建筑物内人员和设备的安全及正常运行。电磁场法对大型复杂建筑物雷击的电磁环境分析更为有效。采用频域有限元法,将电磁场法应用于某建筑物的磁场评估,并与实验结果进行对比验证。利用该方法建立了488.9m超高层建筑成都中海大厦的简化模型,并对该建筑内部的磁场分布进行了评价和分析。仿真结果对该建筑敏感设备的优化安装具有一定的参考价值,也可为超高层建筑防雷系统的改进设计提供指导。
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引用次数: 0
Safety Warning of Lithium-Ion Battery Energy Storage Cabin by Image Recogonition 基于图像识别的锂离子电池储能舱安全预警
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918364
Kangyong Yin, Feng Tao, Wei Liang, Zhechen Huang
Lithium-ion battery will emit gas-liquid escapes from the safety valve when it gets in an accident. The escapes contains a large amount of visible white vaporized electrolyte and some colorless gas. Effective identification of the white vaporized electrolyte and an early warning can greatly reduce the risk of fire, even an explosion in the energy storage power stations. In this paper, an early warning method of lithium-ion battery fire is proposed, which is based on gas-liquid escape image recognition. Firstly, an image recogonition algorithm based on the YOLOv3 is proposed. The original Darknet53 feature extraction network in the algorithm is replaced with a lightweight ReXNet feature extraction network, considering the safety requirements of fast and accurate identification of the storage. In addition, the K-means clustering algorithm is used to obtain appropriate initialized anchor boxes to speed up the convergence of the model. Finally, the multi-scale feature fusion is combined with the path aggregation network to improve the detection accuracy of the model, so that the model can achieve good recognition of both large and small targets. The results show that the method shows a good effect in identifying the vaporized electrolyte of the actual lithium-ion battery storage. The model prediction speed tested on the GTX1650 graphics card can reach 65 frames per second, and the average accuracy is 84.35%. It basically meets the needs of practical applications. The research in this paper can further improve the safety of lithium-ion battery energy storage power stations and promote the healthy development of electrochemical energy storage.
锂离子电池在发生事故时,会从安全阀中释放出气液逃逸物。逸出液中含有大量可见的白色蒸发电解质和一些无色气体。有效识别白色蒸发电解质并进行早期预警,可以大大降低储能电站发生火灾甚至爆炸的风险。本文提出了一种基于气液逃逸图像识别的锂离子电池火灾预警方法。首先,提出一种基于YOLOv3的图像识别算法。考虑到存储快速准确识别的安全要求,算法中原有的Darknet53特征提取网络被替换为轻量级的ReXNet特征提取网络。此外,采用K-means聚类算法获得合适的初始化锚盒,加快模型的收敛速度。最后,将多尺度特征融合与路径聚合网络相结合,提高模型的检测精度,使模型无论对大目标还是小目标都能实现较好的识别。结果表明,该方法对实际锂离子电池存储的汽化电解质具有较好的识别效果。在GTX1650显卡上测试的模型预测速度可以达到65帧/秒,平均准确率为84.35%。基本满足实际应用的需要。本文的研究可以进一步提高锂离子电池储能电站的安全性,促进电化学储能的健康发展。
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引用次数: 0
System Harmonic Impedance Calculation Method Based on Complex Linear Regression and Data Filtering 基于复线性回归和数据滤波的系统谐波阻抗计算方法
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918207
Liu Ke, Yan Han, Wang Xin, Wang Xuan, Yang Fangnan, Li Jianwu, Zhu Xuenian, Cen Baoyi
Because of the fluctuation of the system background harmonic, it is difficult to obtain the system harmonic impedance accurately. According to characteristics of the dominant fluctuation, linearity and continuity of the system harmonic impedance, a novel system harmonic impedance calculation method has been developed, combined with a fluctuation filtering technique, linear correlation test and outlier elimination technique. Field test results show that the proposed method is practical and accurate so that it can be used to determine the system impedance.
由于系统背景谐波的波动,很难准确地获得系统谐波阻抗。根据系统谐波阻抗的主导波动、线性和连续性特点,结合波动滤波技术、线性相关检验和离群值消除技术,提出了一种新的系统谐波阻抗计算方法。现场测试结果表明,该方法实用、准确,可用于系统阻抗的确定。
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引用次数: 0
Research on Fast Power Flow Calculation Method for Multiple Faults Based on Double Line Outage Distribution Factors 基于双线停电分布因子的多故障快速潮流计算方法研究
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918367
Wang Miao, Y. Yijun, S. Lue, Sun Bo, Huang Haiyu
With the continuous expansion of the power grid scale, the power grid is more prone to multiple faults, resulting in more serious power outages. Based on the distribution factor of N-1 single branch, the line outage distribution factor of N-2 double branch power flow transfer is derived. Based on the DC power flow model, the active power flow transfer after two branches are broken at the same time is quickly calculated. The simulation results of IEEE 39 bus system show that the fast power flow calculation method of double line outage distribution factor N-2 contingency in this paper has good accuracy and practicability, and can be applied to the screening of N-2 expected faults and the rapid safety verification of power generation plan or market clearing results.
随着电网规模的不断扩大,电网更容易出现多重故障,造成更严重的停电。在N-1单支路分配系数的基础上,推导出N-2双支路潮流输送的线路停电分配系数。基于直流潮流模型,快速计算了两支路同时断开后的有功潮流转移。IEEE 39母线系统的仿真结果表明,本文提出的双线停电分配因子N-2突发事件的快速潮流计算方法具有较好的准确性和实用性,可用于N-2预期故障的筛选和发电计划或市场出清结果的快速安全验证。
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引用次数: 1
Capacitor Voltage Observation for Series-Connected-Double Submodule based Modular Multilevel Converter 基于串联双子模块的模块化多电平变换器电容电压观测
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918284
Hu Yinghong, Song Peng, Guo Qing, Cao Yu
Due to the high modularity and easy scalability for voltage and power, modular multilevel converter (MMC) has been the most appropriate converter in the high voltage direct current (HVDC) transmission system. The series-connected-double submodule (SCDSM) based MMC not only own the ability of the dc fault blocking but also features simple topology and control strategy. Then, the SCDSM based MMC has a promising application in the HVDC system. In the MMC system, the number of the submodules and capacitors is very large, which means the number of the voltage sensors is also huge. Reduced voltage sensors could decrease the cost of the MMC and improve the reliability of the MMC system. Based on the topology of the SCDSM, this paper proposes a novel arrangement of the voltage sensors and Kalman filter based capacitor voltage observer. Compared with the traditional arrangement of the voltage sensors, the number of the voltage sensors in this paper is halved. The simulation and experimental results verify the effectiveness of the proposed strategy in this paper.
模块化多电平变换器(MMC)由于其高度模块化和易于对电压和功率进行扩展,已成为高压直流输电系统中最合适的变换器。基于串联双子模块(SCDSM)的MMC不仅具有直流故障阻断的能力,而且具有简单的拓扑结构和控制策略。因此,基于MMC的SCDSM在高压直流系统中具有广阔的应用前景。在MMC系统中,子模块和电容器的数量非常大,这意味着电压传感器的数量也非常庞大。减少电压传感器可以降低MMC的成本,提高MMC系统的可靠性。基于SCDSM的拓扑结构,提出了一种新颖的电压传感器和基于卡尔曼滤波的电容电压观测器的排列方式。与传统的电压传感器布置方式相比,本文所设计的电压传感器数量减少了一半。仿真和实验结果验证了本文所提策略的有效性。
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引用次数: 0
Research on Distributed Power Flow Controller and Application 分布式潮流控制器的研究与应用
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918390
Dian-hua Zhang, Donglai Zhao, Fangling Li, Qingqing Zheng, Fan Zhang, Li Yang, Qingtao Wang, Wang Liu, Weixiang Di
The distributed power flow controller (DPFC) works to increase or reduce the reactance of the transmission line by injecting series compensation voltage. The DPFC control system, including DPFC centralized control device and valve layer controller, is designed based on the analysis of DPFC main circuit topology, control architecture, control strategy and protection configuration. It is verified by engineering application that the device can regulate power flow, and effectively solve the problem of the limit-exceeding of the power supply section of the power grid.
分布式潮流控制器(DPFC)通过注入串联补偿电压来增大或减小输电线路的电抗。在分析DPFC主电路拓扑结构、控制体系结构、控制策略和保护组态的基础上,设计了DPFC控制系统,包括DPFC集中控制装置和阀层控制器。经工程应用验证,该装置能有效调节潮流,有效解决电网供电段超限问题。
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引用次数: 1
Evaluating the Importance of Samples in Deep Learning Based Transient Stability Assessment 基于深度学习的暂态稳定性评估中样本的重要性评估
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918314
Le Zheng, Zheng Wang, Yanhui Xu
Deep learning based transient stability assessment has achieved big success in power system analysis. However, it is still unclear that how much of the data is superfluous and which samples are important for training. In this work, we introduce the latest technique from the computer science community to evaluate the importance of the samples used in deep learning model for transient stability assessment. From empirical experiments, it is found that nearly 80% of the low importance samples can be pruned without affecting the testing performance at early training stages, thus saving much computational time and effort. We also observe that the samples with fault clearing time close to the critical clearing time often have higher importance scores, indicating that the decision boundary learned by the deep network is the transient stability boundary. This is intuitive, but to the best of our knowledge, this work is the first to analyze the connection from sample importance aspects. The ultimate goal of the study is to create a tool to generate and evaluate some benchmark datasets for power system transient stability assessment analysis, so that various algorithms can be tested in a unified and standard platform which could verify and compare the performance of the algorithms.
基于深度学习的暂态稳定评估在电力系统分析中取得了巨大成功。然而,目前还不清楚有多少数据是多余的,哪些样本对训练很重要。在这项工作中,我们引入了计算机科学界的最新技术来评估深度学习模型中用于暂态稳定性评估的样本的重要性。从实证实验中发现,在不影响测试性能的前提下,近80%的低重要性样本可以在训练早期被修剪掉,从而节省了大量的计算时间和精力。我们还观察到,故障清除时间接近临界清除时间的样本往往具有更高的重要性得分,这表明深度网络学习的决策边界是暂态稳定边界。这是直观的,但据我们所知,这项工作是第一次从样本重要性方面分析联系。本研究的最终目标是创建一个工具来生成和评估电力系统暂态稳定评估分析的一些基准数据集,使各种算法可以在一个统一的标准平台上进行测试,从而验证和比较算法的性能。
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引用次数: 1
Mechanism of Transformer Magnetic Bias Caused by Sub-synchronous Resonance of Wind Farm Cluster 风电场群次同步共振引起变压器偏磁的机理
Pub Date : 2022-07-28 DOI: 10.1109/ICPET55165.2022.9918220
Jianchun Cao, Qian Li, Yingjing He, Keping Zhu, Yangqing Dan
When sub-synchronous resonance (SSR) occurs in wind power clusters, the main transformers of wind farms will produce abnormal noise and increased vibration, which brings potential risks to the security and stability of power system. By analyzing the fault records and the equivalent circuit of the system, it is proposed that the injection of more than a certain amount of SSR current into the system causes transformer core saturation, which leads to the increase of the main transformer excitation current, strange noise and vibration. When SSR occurs in the transmission system of the wind farm cluster through the FSC, the primary transformer voltage contains considerable sub-synchronous frequency component and result in corresponding fluctuation of magnetic flux in transformer core. As a result, the core of the transformer is periodically alternating positive and negative magnetic bias, and repeatedly enters the saturation state, and then periodically appears a large peak excitation current spike. The degree of partial magnetic saturation of the transformer core is determined by the magnitude of the power frequency flux and the sub-synchronous flux. When the system with higher operating voltage resonates, the core of the transformer is more prone to magnetic bias saturation. This result is verified by Real Time Digital Simulator (RTDS) simulation and physical transformer low-voltage model experiments. Appropriate reduction of the system voltage can reduce the saturation level and the harm of the main transformer and damping of SSR is the ultimate solution to solve the above problems.
当风电集群发生次同步共振时,风电场主变压器会产生异常噪声和振动加剧,给电力系统的安全稳定带来潜在风险。通过对故障记录和系统等效电路的分析,提出在系统中注入超过一定数量的SSR电流会导致变压器铁心饱和,从而导致主变压器励磁电流增大,产生奇怪的噪声和振动。当风电场集群的输电系统通过FSC发生SSR时,变压器一次电压中含有相当大的次同步频率分量,导致变压器铁心磁通相应波动。因此,变压器铁心周期性地交变正、负偏磁,并反复进入饱和状态,然后周期性地出现较大的峰值励磁电流尖峰。变压器铁心局部磁饱和的程度由工频磁通和次同步磁通的大小决定。当工作电压较高的系统发生谐振时,变压器铁心更容易发生偏磁饱和。通过实时数字模拟器(RTDS)仿真和物理变压器低压模型实验验证了这一结果。适当降低系统电压可以降低饱和水平和对主变压器的危害,对SSR的阻尼是解决上述问题的最终解决方案。
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引用次数: 0
期刊
2022 4th International Conference on Power and Energy Technology (ICPET)
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