A phasor-distance based faulty phase detection and fault classification technique for parallel transmission lines

Author(s):  
Nishant Kothari ◽  
Bhavesh R. Bhalja ◽  
Vivek Pandya ◽  
Pushkar Tripathi ◽  
Soumitri Jena

AbstractThis paper presents a phasor-distance based faulty phase detection and fault classification technique for parallel transmission lines. Detection and classification of faulty phase(s) have been carried out by deriving indices from the change in phasor values of current with a distance of one cycle. The derived indices have zero values during normal operating conditions whereas the index corresponding to the faulty phase exceeds the pre-defined threshold in case of occurrence of a fault. A separate ground detection algorithm has been utilized for the identification of involvement of ground in a faulty situation. The performance of the proposed technique has been evaluated for intra-circuit, inter-circuit and simultaneous faults with wide variations in system and fault conditions. The suggested technique has been evaluated for over 23,000 diversified simulated fault cases as well as 14 recorded real fault events. The performance of the proposed technique remains consistent under Current Transformer (CT) saturation as well as different amount and direction of power flow. Moreover, suitability to different power system network has also been studied. Also, faults having fault current less than pre-fault conditions have been detected accurately. The results obtained suggest that it is able to detect faulty phases as well as classify faults within quarter-cycle from the inception of fault with impeccable accuracy. Besides, as modern digital relays have been already equipped with phasor computation facility, phasor-based technique can be easily incorporated with relative ease. At last, a comparative evaluation suggests its superiority in terms of fault classification accuracy, fault detection time, diversify fault scenarios and computational requirement among other existing techniques.

Author(s):  
Nishant H. Kothari ◽  
Bhavesh R. Bhalja ◽  
Vivek Pandya ◽  
Pushkar Tripathi

Abstract This paper presents a new fault classification technique for Thyristor-Controlled Series-Compensated (TCSC) transmission lines using Support Vector Machine (SVM). The proposed technique is based on the utilization of post-fault magnitude of Rate-of-Change-of-Current (ROCC). Fault classification has been carried out by giving ROCC of three-phases and zero sequence current as inputs to SVM classifier. The performance of SVM as a binary-class, and multi-class classifier has been evaluated for the proposed feature. The validity of the suggested technique has been tested by modeling a TCSC based 400 kV, 300 km long transmission line using PSCAD/EMTDC software package. Based on the above model, a large number of diversified fault cases (41,220 cases) have been generated by varying fault and system parameters. The effect of window length, current transformer (CT) saturation, noise-signal, and sampling frequency have also been studied. It has been found that the proposed technique provides an accuracy of 99.98% for 37,620 test cases. Moreover, the performance of the suggested technique has also been found to be consistent upon evaluating in a 12-bus power system model consisting of a 365 kV, 60 Hz, 300 km long TCSC line. Comparative evaluation of the proposed SVM based technique with other recent techniques clearly indicates its superiority in terms of fault classification accuracy.


2020 ◽  
Vol 9 (5) ◽  
pp. 1755-1765
Author(s):  
Mohammed Y. Suliman ◽  
Mahmood T. Al-Khayyat

The power flow controlled in the electric power network is one of the main factors that affected the modern power systems development. The unified power flow controller (UPFC) is a FACTS powerful device that can control both active and reactive power flow of parallel transmission lines branches. In this paper, modelling and simulation of active and reactive power flow control in parallel transmission lines using UPFC with adaptive neuro-fuzzy logic is proposed. The mathematical model of UPFC in power flow is also proposed. The results show the ability of UPFC to control the flow of powers components "active and reactive power" in the controlled line and thus the overall power regulated between lines.


2015 ◽  
Vol 16 (5) ◽  
pp. 473-489
Author(s):  
Rahul Dubey ◽  
S. R. Samantaray ◽  
B. K. Panigrahi ◽  
G. V. Venkoparao

Abstract The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel transmission lines with complex mutual coupling. The test results, considering wide variations in operating conditions of the faulted power network, indicate that the proposed adaptive relay setting provides significant improvement in the relay performance.


Author(s):  
Mohammed Yahya Suliman

<p>The power flow controlled in the electric power network is one of the main factors that affected the modern power systems development. The Static Series Compensatior with storage energy, is a FACTS powerful device that can control the active power flow control of multiple transmission lines branches. In this paper, a simulation model of power control using static series compensator with parallel transmission lines is presented.  The control system using adaptive neuro-fuzzy logic is proposed. The results show the ability of static series compensator with storage energy to control the flow of powers components "active and reactive power" in the controlled line and thus the overall power regulated between lines. </p>


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