基于模块多电平换流器的高压直流输电技术(High Voltage Direct Current Transmission Technology Based on Modular Multilevel Converte,MMC-HVDC)因开关频率低、运行损耗小及易于扩展多端网络等优点被广泛应用。直流侧短路故障因短...基于模块多电平换流器的高压直流输电技术(High Voltage Direct Current Transmission Technology Based on Modular Multilevel Converte,MMC-HVDC)因开关频率低、运行损耗小及易于扩展多端网络等优点被广泛应用。直流侧短路故障因短路电流大,故障电流上升速率快且难以抑制,对MMC-HVDC的发展造成了严重困扰。提出一种MMC-HVDC直流侧短路故障穿越控制方法,该方法基于对称双极接线的全桥型MMC-HVDC,且在直流侧采用高阻接地及金属回线,在发生直流侧短路故障时利用全桥型模块多电平换流器及时反转输出直流电压极性,实现故障电流抑制。同时利用金属回线构建成新的功率回路,快速恢复故障期间的有功功率传输。所提出的故障穿越策略,可以有效消除MMC-HVDC系统在发生直流侧短路故障时换流设备受到的故障电压及电流应力,同时避免换流器闭锁,防止功率缺失。最后,利用PSCAD/EMTDC仿真验证了所提出的直流侧短路故障穿越控制方法的有效性。展开更多
Partial label learning aims to learn a multi-class classifier,where each training example corresponds to a set of candidate labels among which only one is correct.Most studies in the label space have only focused on t...Partial label learning aims to learn a multi-class classifier,where each training example corresponds to a set of candidate labels among which only one is correct.Most studies in the label space have only focused on the difference between candidate labels and non-candidate labels.So far,however,there has been little discussion about the label correlation in the partial label learning.This paper begins with a research on the label correlation,followed by the establishment of a unified framework that integrates the label correlation,the adaptive graph,and the semantic difference maximization criterion.This work generates fresh insight into the acquisition of the learning information from the label space.Specifically,the label correlation is calculated from the candidate label set and is utilized to obtain the similarity of each pair of instances in the label space.After that,the labeling confidence for each instance is updated by the smoothness assumption that two instances should be similar outputs in the label space if they are close in the feature space.At last,an effective optimization program is utilized to solve the unified framework.Extensive experiments on artificial and real-world data sets indicate the superiority of our proposed method to state-of-art partial label learning methods.展开更多
文摘基于模块多电平换流器的高压直流输电技术(High Voltage Direct Current Transmission Technology Based on Modular Multilevel Converte,MMC-HVDC)因开关频率低、运行损耗小及易于扩展多端网络等优点被广泛应用。直流侧短路故障因短路电流大,故障电流上升速率快且难以抑制,对MMC-HVDC的发展造成了严重困扰。提出一种MMC-HVDC直流侧短路故障穿越控制方法,该方法基于对称双极接线的全桥型MMC-HVDC,且在直流侧采用高阻接地及金属回线,在发生直流侧短路故障时利用全桥型模块多电平换流器及时反转输出直流电压极性,实现故障电流抑制。同时利用金属回线构建成新的功率回路,快速恢复故障期间的有功功率传输。所提出的故障穿越策略,可以有效消除MMC-HVDC系统在发生直流侧短路故障时换流设备受到的故障电压及电流应力,同时避免换流器闭锁,防止功率缺失。最后,利用PSCAD/EMTDC仿真验证了所提出的直流侧短路故障穿越控制方法的有效性。
基金supported by the National Natural Science Foundation of China(62176197,61806155)the National Natural Science Foundation of Shaanxi Province(2020GY-062).
文摘Partial label learning aims to learn a multi-class classifier,where each training example corresponds to a set of candidate labels among which only one is correct.Most studies in the label space have only focused on the difference between candidate labels and non-candidate labels.So far,however,there has been little discussion about the label correlation in the partial label learning.This paper begins with a research on the label correlation,followed by the establishment of a unified framework that integrates the label correlation,the adaptive graph,and the semantic difference maximization criterion.This work generates fresh insight into the acquisition of the learning information from the label space.Specifically,the label correlation is calculated from the candidate label set and is utilized to obtain the similarity of each pair of instances in the label space.After that,the labeling confidence for each instance is updated by the smoothness assumption that two instances should be similar outputs in the label space if they are close in the feature space.At last,an effective optimization program is utilized to solve the unified framework.Extensive experiments on artificial and real-world data sets indicate the superiority of our proposed method to state-of-art partial label learning methods.
