Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Changxi Yue"'
Publikováno v:
IEEE Access, Vol 12, Pp 10886-10892 (2024)
Sulfur hexafluoride gas (SF6) is widely used in various electrical insulating equipment in the electric power industry. In this paper, a novel mid-infrared hollow-core fiber (HCF) gas sensor based on infrared spectral absorption is proposed for low-c
Externí odkaz:
https://doaj.org/article/b810c993f74a4f578ba9fc8bcd9e7a48
Autor:
Jicheng Yu, Siyuan Liang, Yinglong Diao, Changxi Yue, Xiaodong Yin, Feng Zhou, Youhui Qiu, Jiangchao Qin
Publikováno v:
IEEE Access, Vol 11, Pp 109553-109563 (2023)
As the core equipment for AC/DC conversion in ultra-high voltage direct current (UHVDC) transmission systems, thyristor converter valves are the main source of losses in converter stations. However, it is difficult to directly measure the actual thyr
Externí odkaz:
https://doaj.org/article/bf960e7cc4c14705ad6debf013e114f4
Publikováno v:
IEEE Access, Vol 11, Pp 69939-69950 (2023)
Ultra-high voltage direct current (UHVDC) transmission systems have multiple inputs and multiple outputs, nonlinearity and strong coupling, making it challenging to accurately measure component and system losses using traditional methods based on sys
Externí odkaz:
https://doaj.org/article/ace9a59fd71344e6976f553a8c083987
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract Advanced sensor technology provides accurate information for transparent monitoring and real-time control of the power grid. Tunnel magnetoresistance (TMR) elements with high sensitivity and linearity provide a new technical means for curren
Externí odkaz:
https://doaj.org/article/6a55f50c360c489c82ab22262a31f5fe
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 52-61 (2022)
The medium-voltage direct-current (MVDC) electrical energy system has attracted increasing attention because of its high energy density and low carbon potential. Accurately characterizing, measuring, and monitoring the DC voltage and current are cruc
Externí odkaz:
https://doaj.org/article/38aa80ee0ef045e4983680aa90a88809
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 1011-1021 (2022)
This paper proposes an improved Long Short-Term Memory neural network (LSTM) for Capacitor Voltage Transformer (CVT) measurement error prediction. The proposed model introduces bidirectional memory, deep feature extraction, and multi-task learning st
Externí odkaz:
https://doaj.org/article/a496258020114cfb807855a29153a5d9
Publikováno v:
Frontiers in Energy Research, Vol 11 (2023)
Faced with the pressure of energy conservation and emission reduction, the power industry is urgently requires low-carbon transformation. The carbon flow calculation theory redistributes the actual carbon generated by the power plant to the branch an
Externí odkaz:
https://doaj.org/article/bae0dfef7fb7404aa81061bad0f7a3ac
Publikováno v:
Frontiers in Energy Research, Vol 11 (2023)
Harmonics brought about by a large number of impulsive and non-linear loads connected to the grid has led to new challenges in regional carbon emission management. The existence of harmonics increases the consumption of power equipment, and the trans
Externí odkaz:
https://doaj.org/article/c5f46e53359d43cdbde6b48ccfbeccba
Autor:
Jicheng Yu, Changxi Yue, Chengzhou Jiang, Dongdong Zhang, Xiaoning Huang, Chengshun Yang, Lei Li
Publikováno v:
Energy Reports, Vol 7, Iss , Pp 300-311 (2021)
As a new generation of magnetic sensors, tunnel magnetoresistive sensors have the advantages of good temperature characteristics and high sensitivity and have been extensively studied and applied in electric energy measurement. External magnetic fiel
Externí odkaz:
https://doaj.org/article/ac1662db0e054a059f34fa5d608797ff
Publikováno v:
Energy Reports, Vol 7, Iss , Pp 312-319 (2021)
DC high current measurement is one of the important supporting technologies of the power system. As an emerging current sensing technology, tunnel magnetoresistance (TMR) has attracted more and more attention due to its advantages of high sensitivity
Externí odkaz:
https://doaj.org/article/5281447a1c5e44199cb3ffd97903c040