Fault Model and Travelling Wave Matching Based Single Terminal Fault Location Algorithm for T-Connection Transmission Line: A Yunnan Power Grid Study

Shu, Hongchun; Han, Yiming; Huang, Ran; Tang, Yutao; Cao, Ping; Yang, Bo; Zhang, Yu

doi:10.3390/en13061506

Cited by 8 publications

(5 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 5 suggests that three readers can be used for tag positioning operations. The area where the intersection of the three circles with the positions of the three readers as the center converge is the position of the tag, where R 1 , R 2 , and R 3 are the radii of the three circles [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training

Zhang

Jiao

Hui

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Motion information collection technology is a means for measuring, tracking, and recording the movement traces of individuals in space. This method can complete the data collection of volleyball players and the ball trajectory and realize quantification and statistical analysis of the data to present a virtual model of the player’s movement trajectory. It is inseparable from the acquisition of information to complete the information collection. Therefore, this work uses the radio frequency identification (RFID) technology in the Internet of Things technology to build an information collection system and apply it to volleyball sports. The existing positioning system based on RFID has problems such as significant positioning errors and high system costs due to the arrangement of a large number of readers. This paper first introduces the theoretical knowledge of the RFID system, wireless network positioning technology, and RFID system positioning method in the Internet of Things. Besides, the theoretical framework of the volleyball movement information acquisition system is presented based on the Received Signal Strength Indication of the RFID system and Location Identification based on the Dynamic Active RFID Calibration (LANDMARC) algorithm. Then, the LANDMARC algorithm is improved through the Centroid Positioning algorithm, forming the CP-LANDMARC algorithm. Finally, a simulation experiment is conducted to test the system effect. The results demonstrate that: (1) the average error of the basic LANDMARC algorithm is 0.55 meters, and the average error of the CP-LANDMARC algorithm is 0.46 meters; (2) the average error of the CP-LANDMARC algorithm is 0.43 meters when the reference label is set to be evenly distributed in a square, and the average error of the optimized algorithm is 0.38 m when the reference label is set as an equilateral triangle; and (3) when the number of reference labels increases to 110, the average error decreases from 0.38 to 0.29. This paper aims to improve the quality of volleyball teaching and training by designing a relevant sports information acquisition system.

show abstract

Section: Methodsmentioning

confidence: 99%

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training

Zhang

Jiao

Hui

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Therefore, the protection of UHV transmission lines becomes paramount, highlighting the importance of fast and accurate fault diagnosis for the safe and stable operation of the UHVDC transmission systems. Based on this phenomenon, Niazy andSadeh (2013), Singh Brains et al (2017), Shu et al (2020) conducted certain research. At present, transient protection utilizing the boundary to the attenuation characteristics of high-frequency quantities is the development direction of UHVDC transmission line protection.…”

Section: Introductionmentioning

confidence: 99%

UHVDC transmission line diagnosis method for integrated community energy system based on wavelet analysis

Yuan,

Liang,

Zhang

et al. 2024

Front. Energy Res.

View full text Add to dashboard Cite

With the large-scale development of renewable energy power, China has faced with the challenges of the reverse regional distribution of wind and solar resources and power load, as well as the intermittency and randomness of renewable energy power. Therefore, China is vigorously developing ultra-high voltage direct current (UHVDC) transmission technology to solve the problem of insufficient flexibility caused by the uncertainty of renewable energy and the fluctuation of multi-energy loads in integrated community energy systems. UHVDC plays an increasingly pivotal role in the west-east transmission system in China’s power system due to its high transmission capacity and long transmission distance. Once the fault occurs in the ultra-high voltage direct (UHVD) transmission line, quick and accurate fault location identification is of great significance. Hence, this paper proposes a UHVDC transmission line diagnosis method based on wavelet analysis for integrated community energy systems. Wavelet transform (WT) is used to decompose the transient signal on a multi-scale, and then power systems computer-aided design (PSCAD) software is utilized for simulation calculation to obtain the singular spectrum entropy of each layer and facilitate wavelet transformations for signal denoising with advanced tools such as MATLAB. The prediction results can distinguish outside the rectification side fault, within the rectification side fault, and outside the inverter fault with an accuracy of 100%. A large number of simulations demonstrate that combining singular spectrum entropy with support vector machines (SVM) has emerged as a robust technique for integrated community energy systems, suggesting its potential as a standard method in UHVDC transmission line diagnosis. This study is of significant reference for realizing the complementarity of multiple types of power supply and ensuring a reliable power supply.

show abstract

“…These methods use a simplified equation for calculation by ignoring the capacitance and conductance of the transmission line to ground, which limits the accuracy of fault location [4]. Traveling wave-based methods determine the fault distance according to the reflection and refraction phenomenon of the voltage and current traveling wave at the fault point and terminals, and the traveling wave propagation speed [5,6]. Specifically, the single-ended traveling wave method does not require a global positioning system and communication equipment, showing a popular application in the fault location of the HVDC system [7,8].…”

Section: Introductionmentioning

confidence: 99%

A Single-Terminal Fault Location Method for HVDC Transmission Lines Based on a Hybrid Deep Network

Wang

2021

Electronics

View full text Add to dashboard Cite

High voltage direct current (HVDC) transmission systems play an increasingly important role in long-distance power transmission. Realizing accurate and timely fault location of transmission lines is extremely important for the safe operation of power systems. With the development of modern data acquisition and deep learning technology, deep learning methods have the feasibility of engineering application in fault location. The traditional single-terminal traveling wave method is used for fault location in HVDC systems. However, many challenges exist when a high impedance fault occurs including high sampling frequency dependence and difficulty to determine wave velocity and identify wave heads. In order to resolve these problems, this work proposed a deep hybrid convolutional neural network (CNN) and long short-term memory (LSTM) network model for single-terminal fault location of an HVDC system containing mixed cables and overhead line segments. Simultaneously, a variational mode decomposition–Teager energy operator is used in feature engineering to improve the effect of model training. 2D-CNN was employed as a classifier to identify fault segments, and LSTM as a regressor integrated the fault segment information of the classifier to achieve precise fault location. The experimental results demonstrate that the proposed method has high accuracy of fault location, with the effects of fault types, noise, sampling frequency, and different HVDC topologies in consideration.

show abstract

Fault Model and Travelling Wave Matching Based Single Terminal Fault Location Algorithm for T-Connection Transmission Line: A Yunnan Power Grid Study

Cited by 8 publications

References 40 publications

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training

Application of Internet of Things Combined with Wireless Network Technology in Volleyball Teaching and Training

UHVDC transmission line diagnosis method for integrated community energy system based on wavelet analysis

A Single-Terminal Fault Location Method for HVDC Transmission Lines Based on a Hybrid Deep Network

Contact Info

Product

Resources

About