Fast Discrimination of Transformer Magnetizing Current From Internal Faults: An Extended Kalman Filter-Based Approach

2018 ◽  
Vol 33 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Farshid Naseri ◽  
Zahra Kazemi ◽  
Mohammad Mehdi Arefi ◽  
Ebrahim Farjah
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Magnetizing Current ◽  
Internal Faults

scholarly journals Sensorless Voltage Observer for a Current-Fed High Step-Up DC-DC Converter Using Extended Kalman Filter

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2066
Author(s):  
Karim Haadi ◽  
Amirhossein Rajaei ◽  
Mahdi Shahparasti ◽  
Akbar Rahideh
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Output Voltage ◽  
Good Precision ◽  
Voltage Transformer ◽  
Control Techniques ◽  
Parasitic Parameters ◽  
Magnetizing Current ◽  
The Cost ◽  
A Current

In high voltage applications, sensorless voltage control techniques can reduce the cost and increase the reliability of DC-DC converters. In this paper, a sensorless voltage observer for a current fed Cockcroft-Walton voltage multiplier is designed. The first step is to derive the converter model. Since any inaccuracy in the derived model can result in a discrepancy between the observed voltage and the actual output voltage, an accurate model is derived, which incorporates the influential elements. Then, two voltage observers based on the extended Kalman filter (EKF) are designed and used to estimate the output voltage, transformer magnetizing current and inductor current for two different configurations of the high step-up DC-DC converter. Experimental and simulation results of the system show the efficiency of the observers. The proposed observers represent good precision as the main parasitic parameters are considered in the converter model.

scholarly journals Discrimination of Transformer Inrush Currents and Internal Fault Currents Using Extended Kalman Filter Algorithm (EKF)

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6020
Author(s):  
Sunil Kumar Gunda ◽  
Venkata Samba Sesha Siva Sarma Dhanikonda
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Threshold Level ◽  
Transformer Protection ◽  
Protection Scheme ◽  
Fault Currents ◽  
Internal Fault ◽  
Absolute Residual ◽  
Inrush Currents ◽  
Internal Faults

The discrimination of inrush currents and internal fault currents in transformers is an important feature of a transformer protection scheme. The harmonic current restrained feature is used in conventional differential relay protection of transformers. A literature survey shows that the discrimination between the inrush currents and internal fault currents is still an area that is open to research. In this paper, the classification of internal fault currents and magnetic inrush currents in the transformer is performed by using an extended Kalman filter (EKF) algorithm. When a transformer is energized under normal conditions, the EKF estimates the primary side winding current and, hence, the absolute residual signal (ARS) value is zero. The ARS value will not be equal to zero for internal fault and inrush phenomena conditions; hence, the EKF algorithm will be used for discriminating the internal faults and inrush faults by keeping the threshold level to the ARS value. The simulation results are compared with the theoretical analysis under various conditions. It is also observed that the detection time of internal faults decreases with the severity of the fault. The results of various test cases using the EKF algorithm are presented. This scheme provides fast protection of the transformer for severe faults.

scholarly journals Performance evaluation of GPS / BDS combined single-point positioning based on RTKLIB

2020 ◽  
Vol 165 ◽  
pp. 03009
Author(s):  
Li Yan-yi ◽  
Huang Jin ◽  
Tang Ming-xiu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Single Point ◽  
Least Square Method ◽  
Least Square ◽  
Filter Method ◽  
Single System ◽  
Positioning Error ◽  
Dual Mode ◽  
Kalman Filter Method

In order to evaluate the performance of GPS / BDS, RTKLIB, an open-source software of GNSS, is used in this paper. In this paper, the least square method, the weighted least square method and the extended Kalman filter method are respectively applied to BDS / GPS single system for data solution. Then, the BDS system and GPS system are used for fusion positioning and the positioning results of the two systems are compared with that of the single system. Through the comparison of experiments, on the premise of using the extended Kalman filter method for positioning, when the GPS signal is not good, BDS data is introduced for dual-mode positioning, the positioning error in e direction is reduced by 36.97%, the positioning error in U direction is reduced by 22.95%, and the spatial positioning error is reduced by 16.01%, which further reflects the advantages of dual-mode positioning in improving a system robustness and reducing the error.

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