This paper introduces the characteristics of VSC and MMC-MTDC and discusses the effects of different kinds of faults in HVDC systems. Special attention is given to the comparison between a pole-to-pole fault and a pol...This paper introduces the characteristics of VSC and MMC-MTDC and discusses the effects of different kinds of faults in HVDC systems. Special attention is given to the comparison between a pole-to-pole fault and a pole-to-ground fault occurring in the middle of the line or at the terminal of a VSC. Simulations using MATLAB are provided in this article which show the difference effects clearly when faults occur in a VSC-MTDC system or in a MMC-MTDC system. Understanding of such fault characteristics and the influence of the control system on them are important prerequisites on the way to MTDC systems.展开更多
In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management...In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.展开更多
Compressed sensing(CS)has been successfully applied to realize image reconstruction.Neural networks have been introduced to the CS of images to exploit the prior known support information,which can improve the reconst...Compressed sensing(CS)has been successfully applied to realize image reconstruction.Neural networks have been introduced to the CS of images to exploit the prior known support information,which can improve the reconstruction quality.Capsule Network(Caps Net)is the latest achievement in neural networks,and can well represent the instantiation parameters of a specific type of entity or part of an object.This study aims to propose a Caps Net with a novel dynamic routing to embed the information within the CS framework.The output of the network represents the probability that the index of the nonzero entry exists on the support of the signal of interest.To lead the dynamic routing to the most likely index,a group of prediction vectors is designed determined by the information.Furthermore,the results of experiments on imaging signals are taken for a comparation of the performances among different algorithms.It is concluded that the proposed capsule network(Caps Net)creates higher reconstruction quality at nearly the same time with traditional Caps Net.展开更多
文摘This paper introduces the characteristics of VSC and MMC-MTDC and discusses the effects of different kinds of faults in HVDC systems. Special attention is given to the comparison between a pole-to-pole fault and a pole-to-ground fault occurring in the middle of the line or at the terminal of a VSC. Simulations using MATLAB are provided in this article which show the difference effects clearly when faults occur in a VSC-MTDC system or in a MMC-MTDC system. Understanding of such fault characteristics and the influence of the control system on them are important prerequisites on the way to MTDC systems.
基金Project supported by the National Key R&D Program of China(No.2018AAA0101504)the Science and Technology Project of the State Grid Corporation of China:Fundamental Theory of Human in-the-Loop Hybrid-Augmented Intelligence for Power Grid Dispatch and Control。
文摘In this paper,we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation(HM-KA)as the technical mechanism of hybrid augmented intelligence(HAI)based complex system cognition,management,and control(CMC).We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence.The need for using human-machine HAI in complex systems is then explained in detail.The concept of“mutually trustworthy HM-KA”mechanism is proposed to tackle the CMC challenge,and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch.It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.
基金supported by the Research Fund Project of Beijing Information Science and Technology University(2021XJJ44 and 2021XJJ69).
文摘Compressed sensing(CS)has been successfully applied to realize image reconstruction.Neural networks have been introduced to the CS of images to exploit the prior known support information,which can improve the reconstruction quality.Capsule Network(Caps Net)is the latest achievement in neural networks,and can well represent the instantiation parameters of a specific type of entity or part of an object.This study aims to propose a Caps Net with a novel dynamic routing to embed the information within the CS framework.The output of the network represents the probability that the index of the nonzero entry exists on the support of the signal of interest.To lead the dynamic routing to the most likely index,a group of prediction vectors is designed determined by the information.Furthermore,the results of experiments on imaging signals are taken for a comparation of the performances among different algorithms.It is concluded that the proposed capsule network(Caps Net)creates higher reconstruction quality at nearly the same time with traditional Caps Net.
