scholarly journals Robust Identification Method for Transmission Line Parameters That Considers PMU Phase Angle Error

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 86962-86971 ◽  
Author(s):  
Ancheng Xue ◽  
Feiyang Xu ◽  
Kenneth E. Martin ◽  
Hongyu You ◽  
Jingsong Xu ◽  
...  
Keyword(s):  
Transmission Line ◽  
Phase Angle ◽  
Angle Error ◽  
Robust Identification ◽  
Identification Method

scholarly journals A New Robust Identification Method for Transmission Line Parameters Based on ADALINE and IGG Method

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 132960-132969
Author(s):  
Ancheng Xue ◽  
He Kong ◽  
Yongzhao Lao ◽  
Quan Xu ◽  
Yuehuan Lin ◽  
...  
Keyword(s):  
Transmission Line ◽  
Robust Identification ◽  
Identification Method

Study of an accurate electronic power measurement technique using modified current transformer and potential transformer

2019 ◽  
Vol 41 (13) ◽  
pp. 3666-3678
Author(s):  
Sirshendu Saha ◽  
Saikat Kumar Bera ◽  
Hiranmoy Mandal ◽  
Pradip Kumar Sadhu ◽  
Satish Chandra Bera
Keyword(s):  
Phase Angle ◽  
Measurement Errors ◽  
Light Emitting Diode ◽  
Current Transformer ◽  
Power Measurement ◽  
Measurement Unit ◽  
Measurement Circuit ◽  
Angle Error ◽  
Ratio Error ◽  
High Tension

In high tension power measurement, potential transformer (PT) and current transformer (CT) are used in order to reduce high tension voltage and current, respectively. But both PT and CT suffer from ratio error and phase angle error, which may produce severe error in power measurement. In the present paper, modified designs of PT and CT are combined to develop an electronic power measurement circuit in order to reduce the measurement errors. The modified PT and CT have reduced phase angle error and ratio error. In the power measurement circuit, the instantaneous product of the outputs of these PT and CT is determined by using a simple light emitting diode (LED)-light dependent register (LDR) or LED-LDR-based product circuit. The operation of the proto type power measurement unit designed in the present work has been experimentally tested and the measured outputs are compared with the readings of laboratory standard wattmeter. The experimental results are reported in the paper. Very good linear characteristics are observed.

scholarly journals External Breaking Vibration Identification Method of Transmission Line Tower Based on Solar-Powered RFID Sensor and CNN

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 519
Author(s):  
Fangming Deng ◽  
Kaiyun Wen ◽  
Zhongxin Xie ◽  
Huafeng Liu ◽  
Jin Tong
Keyword(s):  
Transmission Line ◽  
Radio Frequency Identification ◽  
Descent Method ◽  
Identification Accuracy ◽  
Batch Size ◽  
Optimum Number ◽  
Gradient Descent Method ◽  
Super Capacitor ◽  
Identification Method ◽  
Solar Powered

This paper proposes an external breaking vibration identification method of transmission line tower based on a radio frequency identification (RFID) sensor and deep learning. The RFID sensor is designed to obtain the vibration signal of the transmission line tower. In order to achieve long-time monitoring and longer working distance, the proposed RFID sensor tag employs a photovoltaic cell combined with a super capacitor as the power management module. convolution neural network (CNN) is adopted to extract the characteristics of vibration signals and relevance vector machine (RVM) is then employed to achieve vibration pattern identification. Furthermore, the Softmax classifier and gradient descent method are used to adjust the weights and thresholds of CNN, so as to obtain a high-precision identification structure. The experiment results show that the minimum sensitivity of the proposed solar-powered RFID sensor tag is −29 dBm and the discharge duration of the super capacitor is 63.35 h when the query frequencies are 5/min. The optimum batch size of CNN is 5, and the optimum number of convolution cores in the first layer and the second layer are 2 and 4, respectively. The maximum number of iterations is 10 times. The vibration identification accuracy of the proposed method is over 99% under three different conditions.

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