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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1563-1574页

作者： Chenxi Fan kaishun xiahou Lei Wang Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

This paper presents a long short-term memory(LSTM)-based fault detection method to detect the multiple open-circuit switch faults of modular multilevel converter(MMC)systems with full-bridge sub-modules(FB-SMs).Eighteen sensor signals of grid voltages,grid currents and capacitance voltages of MMC for single and multi-switch faults are collected as sampling *** output signal characteristics of four types of single switch faults of FB-SM,as well as double switch faults in the same and different phases of MMC,are analyzed under the conditions of load variations and control command changes.A multi-layer LSTM network is devised to deeply extract the fault characteristics of MMC under different faults and operation conditions,and a Softmax layer detects the fault *** results have confirmed that the proposed LSTM-based method has better detection performance compared with three other methods:K-nearest neighbor(KNN),naive bayes(NB)and recurrent neural network(RNN).In addition,it is highly robust to model uncertainties and Gaussian *** validity of the proposed method is further demonstrated by experiment studies conducted on a hardware-in-the-loop(HIL)testing platform.

关键词： Fault detection long short-term memory(LSTM) modular multilevel converter(MMC) open circuit fault

Detection of false data injection attacks on power systems using graph edge-conditioned convolutional networks

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Protection and Control of Modern Power Systems 2023年第2期8卷 1-12页

作者： Bairen Chen Q.H.Wu Mengshi Li kaishun xiahou School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

State estimation plays a vital role in the stable operation of modern power systems,but it is vulnerable to cyber *** data injection attacks(FDIA),one of the most common cyber attacks,can tamper with measure-ment data and bypass the bad data detection(BDD)mechanism,leading to incorrect results of power system state estimation(PSSE).This paper presents a detection framework of FDIA for PSSE based on graph edge-conditioned convolutional networks(GECCN),which use topology information,node features and edge *** deep graph architecture,the correlation of sample data is effectively mined to establish the mapping relationship between the estimated values of measurements and the actual states of power *** addition,the edge-conditioned convolution operation allows processing data sets with different graph *** studies are undertaken on the IEEE 14-bus system under different attack intensities and degrees to evaluate the performance of *** results show that GECCN has better detection performance than convolutional neural networks,deep neural net-works and support vector ***,the satisfactory detection performance obtained with the data sets of the IEEE 14-bus,30-bus and 118-bus systems verifies the effective scalability of GECCN.

关键词： Power system state estimation(PSSE) Bad data detection(BDD) False data injection attacks(FDIA) Graph edge-conditioned convolutional networks(GECCN)

Equivalent Hamiltonian Equations Modelling and Energy Function Construction for MMC-HVDC in Hybrid AC/DC Power Systems

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CSEE Journal of Power and Energy Systems 2021年第4期7卷 821-831页

作者： Yang Liu Zehui Lin kaishun xiahou Yuqing Lin Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

This paper proposes an equivalent Hamiltonian equations model for the modular multilevel converter-based high-voltage direct-current(MMC-HVDC)transmission system,and constructs an energy function for multi-machine power systems with MMC-HVDC transmission *** equivalent Hamiltonian equations model is verified to be able to track the power output dynamics of the full model of an MMC-HVDC transmission *** theoretical and numerical studies have been undertaken to validate that the energy function proposed for hybrid AC/DC systems satisfies the conditions of an energy *** work of this paper bridges the gap between the well-developed direct methods of transient stability analysis and power systems with MMC-HVDC transmission lines.

关键词： Energy function equivalent Hamiltonian equations model hybrid AC/DC power system MMC-HVDC transient stability

Constructing an Energy Function for Power Systems with DFIGWT Generation Based on a Synchronous-generator-mimicking Model

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 64-75页

作者： Yang Liu Chenying Xu Zehui Lin kaishun xiahou Q.H.Wu the School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

In this paper we construct an energy function for multi-machine power systems with doubly-fed induction generator-based wind turbine(DFIGWT)according to a synchronous-generator-mimicking(SGM)model of the *** SGM model is proposed to approximate the dynamics of a *** to the modelling of a synchronous generator(SG),the internal dynamics of a DFIGWT are also described with differential equations of newly constructed virtual rotor angle and internal electromotive force(EMF)in the SGM ***,the power flow of a DFIGWT is expressed by nonlinear functions of its virtual rotor angle and internal *** SGM model bridges the gap between the irregular and complex modelling of DFIGWTs and the well-developed energy function construction techniques for SG *** on the SGM model,a numerical energy function is constructed for power systems with DFIGWT *** theoretical analysis and numerical studies were undertaken to validate that the proposed energy function satisfies the necessary conditions for an energy function of a power system.

关键词： DFIGWT energy function multi-machine power systems synchronous-generator-mimicking model

Robust Bang-Bang Control of Disturbed Nonlinear Systems Based on Nonlinear Observers

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CSEE Journal of Power and Energy Systems 2020年第1期6卷 193-202页

作者： Yang Liu kaishun xiahou Q.H.Wu Hui Pang Guangfu Tang School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China State Key Laboratory of Advanced Transmission Technology Global Energy Interconnection Research InstituteBeijing 102202China

This paper proposes a robust bang-bang controller(RBC)based on the high-gain nonlinear observer for a nonlinear system with intermittent *** intermittent distur-bances are able to model the system faults and sudden changes of operating conditions of practical nonlinear systems.A bang-bang constant funnel controller(BCFC)is employed,and the largest control capabilities of the control system is explored to stabi-lize the nonlinear system against the *** BCFC functions with the estimates of tracking error of control target and its derivatives estimated with a high-gain state observer,which eliminates the requirement on the derivative calculations of the system output tracking *** error convergence of the observer is *** closed-loop stability of the RBC is proved in a bounded-input bounded-state *** studies are undertaken with a single-machine infinite-bus(SMIB)power system to test the performance of the RBC.

关键词： Bang-bang constant funnel controller disturbed nonlinear system high-gain observer

On the State-dependent Switched Energy Functions of DFIG-based Wind Power Generation Systems

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CSEE Journal of Power and Energy Systems 2020年第2期6卷 318-328页

作者： Yang Liu Zehui Lin kaishun xiahou Mengshi Li Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

This paper proposes a novel state-dependent switched energy function(SdSEF)for general nonlinear autonomous systems,and constructs an SdSEF for doubly-fed induction generator(DFIG)-based wind power generation systems(WPGSs).Different from the conventional energy function,SdSEF is a piece-wise continuous function,and it satisfies the conditions of conventional energy functions on each of its continuous *** is designed to bridge the gap between the well-developed energy function theory and the description of system energy of complex nonlinear systems,such as power electronics converter *** stability criterion of nonlinear autonomous systems is investigated with SdSEF,and mathematical proof is *** SdSEF of a typical DFIGbased WPGS is simulated in the whole processes of a grid fault and fault *** results verify the negativeness of the derivative of each continuous segment of the SdSEF.

关键词： Doubly-fed induction generator state-dependent switched energy function wind power generation system

基于深度置信网络的双馈风机变换器开路故障诊断

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电力工程技术 2021年第1期40卷 188-194页

作者：夏候凯顺李波华南理工大学电力学院广东广州510641 国网江苏省电力有限公司电力科学研究院江苏南京211103

双馈风机的定子与电网直接连接,转子通过转子侧变换器和网侧变换器与电网进行功率交换。变换器的电力电子开关容易发生开路故障,影响双馈风机的安全稳定运行。文中针对双馈风机常见的变换器开路故障,提出一种基于深度置信网络的故障诊... 详细信息

双馈风机的定子与电网直接连接,转子通过转子侧变换器和网侧变换器与电网进行功率交换。变换器的电力电子开关容易发生开路故障,影响双馈风机的安全稳定运行。文中针对双馈风机常见的变换器开路故障,提出一种基于深度置信网络的故障诊断方法。首先分析了双馈风机在转子侧变换器和网侧变换器的单个和双个开关管故障下的输出响应。基于双馈风机的变换器开路故障数据,构造多层受限玻尔兹曼机结构,充分利用深度置信网络优异的模式识别能力,深度提取不同故障条件和运行工况下转子电流和网侧电流的信号特征,提高算法准确度。仿真结果表明,该故障诊断方法能够准确识别单开关和双开关的多类型复杂故障。

关键词：双馈风机转子侧变换器网侧变换器故障诊断深度学习

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基于双目云台相机的目标跟踪系统建模与仿真

系统仿真学报 2015年第2期27卷 362-368页

作者：夏候凯顺陈善星邬依林华南理工大学自动化科学与工程学院广州510640 广东第二师范学院计算机科学系广州510310

对双目云台相机目标跟踪系统的各个环节建立数学模型。采用扩展Kalman滤波(Extended Kalman Filter,EKF)作为定位跟踪算法,利用双目云台相机在水平方向、垂直方向转动角及其相对位置估计出目标实时位置;针对云台相机建模过程中相机外部... 详细信息

对双目云台相机目标跟踪系统的各个环节建立数学模型。采用扩展Kalman滤波(Extended Kalman Filter,EKF)作为定位跟踪算法,利用双目云台相机在水平方向、垂直方向转动角及其相对位置估计出目标实时位置;针对云台相机建模过程中相机外部参数随云台旋转发生变化的问题,提出一种云台相机实时标定方法;利用云台相机模型将目标估计位置投影到相机图像平面,提取出目标的图像特征作为视觉伺服系统的反馈信息控制云台旋转跟踪目标轨迹。在Matlab/Simulink环境下搭建仿真模型,仿真结果证实了方案的可行性和有效性,为视觉伺服控制器进一步设计提供了仿真平台。

关键词：云台相机双目立体视觉目标跟踪 EKF 视觉伺服

基于数据驱动的电力系统虚假数据注入攻击防御框架的研究

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电测与仪表 2024年第12期61卷 10-16页

作者：陈柏任夏候凯顺李梦诗华南理工大学电力学院广州510641

电力系统状态估计(power system state estimation,PSSE)在现代智能电网的稳定运行中起着至关重要的作用,但它也容易遭受网络攻击。虚假数据注入攻击(false data injection attacks,FDIA)是最常见的网络攻击方式之一,它可以篡改量测数... 详细信息

电力系统状态估计(power system state estimation,PSSE)在现代智能电网的稳定运行中起着至关重要的作用,但它也容易遭受网络攻击。虚假数据注入攻击(false data injection attacks,FDIA)是最常见的网络攻击方式之一,它可以篡改量测数据并绕过不良数据检测(bad data detection,BDD)机制,从而导致不正确的状态估计结果。文中提出一种基于数据驱动的针对PSSE的FDIA防御框架,该框架包含异常检测子框架和数据恢复子框架。异常检测部分采用改进的图卷积网络(improved graph convolutional network,IGCN)模型,该模型采用动态的边缘条件滤波器作用于图结构中,有效利用电力系统的拓扑信息、节点特征和边特征,从而检测出异常值。数据恢复部分采用变分自编码器(variational auto-encoder,VAE)模型,该模型将深度学习思想与贝叶斯推理相结合,可以有效地将异常数据恢复到在正常运行情况下的数值。针对不同攻击强度和攻击程度下的IEEE 14系统进行案例研究,以评估防御框架的检测与恢复性能。仿真结果表明,基于IGCN的异常检测子框架性能优于常规的数据驱动模型框架,其总体精确率为99.348%,召回率为99.331%,F1值为99.324%,基于VAE的数据恢复子框架的总体平均绝对误差为0.00534 p.u.,证明了防御框架优异的检测与恢复性能。

关键词：电力系统状态估计虚假数据注入攻击数据驱动改进图卷积网络变分自编码器

基于Kalman滤波的无线传感器网络多目标跟踪

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中山大学学报（自然科学版） 2014年第2期53卷 18-22页

作者：夏候凯顺严娟叶小朋余辉荣邬依林华南理工大学自动化科学与工程学院广东广州510640 广东第二师范学院计算机科学系广东广州510310

设计无线传感器网络多目标跟踪系统,分析系统跟踪性能的影响因素,提出基于单点观测的扩展卡尔曼滤波(Extended Kalman Filter,EKF)算法和基于Kalman滤波算法预测功能的节点自适应调度策略,并引入多种事件辅助机制。实验结果表明,该算法... 详细信息

设计无线传感器网络多目标跟踪系统,分析系统跟踪性能的影响因素,提出基于单点观测的扩展卡尔曼滤波(Extended Kalman Filter,EKF)算法和基于Kalman滤波算法预测功能的节点自适应调度策略,并引入多种事件辅助机制。实验结果表明,该算法和调度策略能够实现多目标实时跟踪,且具有减少计算量、缩短测量周期、降低能量消耗、提高跟踪精度等优点。

关键词：无线传感器网络目标跟踪自适应节点调度