电力系统发生大面积复杂故障后,调度人员仅仅依靠来自数据采集与监视控制(supervisory control and data acquisition,SCADA)系统的保护和开关接点的变位信息难以做出准确的判断,来自故障录波装置记录的模拟量信息越来越成为故障诊断和...电力系统发生大面积复杂故障后,调度人员仅仅依靠来自数据采集与监视控制(supervisory control and data acquisition,SCADA)系统的保护和开关接点的变位信息难以做出准确的判断,来自故障录波装置记录的模拟量信息越来越成为故障诊断和系统恢复的重要依据。为了进一步提高超高压输电线路故障类型识别率和计算速度,文中利用提升小波和PNN网络构造了新的小波神经网络故障识别模型,应用bior3．1提升小波对故障电流进行分解,将分解到的 (0,375)Hz频率段的小波系数输入到PNN神经网络。通过 ATP仿真及华东电网实际故障录波数据的测试和比较结果表明:该模型具有很高的识别率和收敛速度,并有望将该模型应用到电网故障诊断系统。展开更多
An online TL （transmission line） impedance TPIS （transmission line parameter identification system） using PMU （phasor measurement unit） was recently developed and implemented at CSG （china southern power grid c...An online TL （transmission line） impedance TPIS （transmission line parameter identification system） using PMU （phasor measurement unit） was recently developed and implemented at CSG （china southern power grid company）, Traditional approaches for TL impedance calculation only approximate the effect of conductor sags and ignore the dependence of impedances on temperature variation. Utilizing PMU measurements may improve the accuracy of TL parameters calculation. The challenge is that the parameters identified are very sensitive to noise and errors in PMU measurements, which are difficult to quantify and can be uncertain under different system operating/loading condition, TPIS provides an innovative yet practical problem formulation for TL sequence parameter estimation based on least-squares with linear constraints. A bootstrapping-based resampling technique is developed and a new metric is proposed to determine the credibility of the estimated sequence impedances. This paper discusses the proposed methodologies, challenges, as well as implementation issues identified during the development of TPIS.展开更多
In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry,this work proposed a novel method of condition recognition by combining complex ne...In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry,this work proposed a novel method of condition recognition by combining complex network theory with phase space reconstruction.First,a condition-space with complete information was reconstructed based on phase space reconstruction,and each condition in the space was transformed into a node of a complex network.Second,the limited penetrable visibility graph method was applied to establish an undirected and un-weighted complex network for the reconstructed condition-space.Finally,the statistical properties of this network were calculated to recognize the different operating conditions.A case study of a real chemical plant was conducted to illustrate the analysis and application processes of the proposed method.The results showed that the method could effectively recognize the different conditions of electromechanical systems.A complex electromechanical system can be studied from the systematic and cyber perspectives,and the relationship between the network structure property and the system condition can also be analyzed by utilizing the proposed method.展开更多
文摘电力系统发生大面积复杂故障后,调度人员仅仅依靠来自数据采集与监视控制(supervisory control and data acquisition,SCADA)系统的保护和开关接点的变位信息难以做出准确的判断,来自故障录波装置记录的模拟量信息越来越成为故障诊断和系统恢复的重要依据。为了进一步提高超高压输电线路故障类型识别率和计算速度,文中利用提升小波和PNN网络构造了新的小波神经网络故障识别模型,应用bior3．1提升小波对故障电流进行分解,将分解到的 (0,375)Hz频率段的小波系数输入到PNN神经网络。通过 ATP仿真及华东电网实际故障录波数据的测试和比较结果表明:该模型具有很高的识别率和收敛速度,并有望将该模型应用到电网故障诊断系统。
文摘An online TL （transmission line） impedance TPIS （transmission line parameter identification system） using PMU （phasor measurement unit） was recently developed and implemented at CSG （china southern power grid company）, Traditional approaches for TL impedance calculation only approximate the effect of conductor sags and ignore the dependence of impedances on temperature variation. Utilizing PMU measurements may improve the accuracy of TL parameters calculation. The challenge is that the parameters identified are very sensitive to noise and errors in PMU measurements, which are difficult to quantify and can be uncertain under different system operating/loading condition, TPIS provides an innovative yet practical problem formulation for TL sequence parameter estimation based on least-squares with linear constraints. A bootstrapping-based resampling technique is developed and a new metric is proposed to determine the credibility of the estimated sequence impedances. This paper discusses the proposed methodologies, challenges, as well as implementation issues identified during the development of TPIS.
基金supported by the National Natural Science Foundation of China (Grant by No. 51175402)
文摘In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry,this work proposed a novel method of condition recognition by combining complex network theory with phase space reconstruction.First,a condition-space with complete information was reconstructed based on phase space reconstruction,and each condition in the space was transformed into a node of a complex network.Second,the limited penetrable visibility graph method was applied to establish an undirected and un-weighted complex network for the reconstructed condition-space.Finally,the statistical properties of this network were calculated to recognize the different operating conditions.A case study of a real chemical plant was conducted to illustrate the analysis and application processes of the proposed method.The results showed that the method could effectively recognize the different conditions of electromechanical systems.A complex electromechanical system can be studied from the systematic and cyber perspectives,and the relationship between the network structure property and the system condition can also be analyzed by utilizing the proposed method.
