WAMS-based Hierarchical Active Power Differential Signal Algorithm for Backup Protection of a FACTS Compensated Transmission Network

Venugopal, Sreelekha; Asok, Prince; Arya, Sabha Raj

doi:10.15598/aeee.v20i4.4512

Cited by 1 publication

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“…It has the advantages of adaptation capability, nonlinear ability, and rapid learning capacity. A generalized backup protection scheme based on Wide Area Measurement System (WAMS) data that utilizes the power dierential values of the lines is used for faulty line identication [40]- [41]. The algorithm rst identies the buses near a fault with sequence components of bus voltages and then uses the hierarchial magnitudes of dierential active power signals to identify the faulty line.…”

Section: Introductionmentioning

confidence: 99%

ANFIS-Based Fault Distance Locator With Active Power Differential-Based Faulty Line Identification Algorithm for Shunt and Series Compensated Transmission Line Using WAMS

Sreelekha,

Prince

2023

IEEE Access

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In power systems, it is challenging to identify the faulty line and fault distance when compensating devices are present in the system. This work presents a fault locator using an Adaptive-Network-based Fuzzy Inference System (ANFIS) that accurately estimates the fault location on a compensated line in conjunction with an active power dierential-based backup protection algorithm for faulty line identication. Both the faulty line identication algorithm and the ANFIS-based fault locator utilise the positive and negative sequence voltage and current phasors generated by the Phasor Measurement units (PMUs) placed in the system. The ANFISbased fault locator is trained and tested using the simulated fault data obtained with a MATLAB Simulink model of a modied WSCC 9 bus system. The training data is generated by varying the fault distance in steps of 10 km. The line-to-line resistance (Rf) of 0.01 Ω, 0.1 Ω & 1 Ω, and the line-to-ground resistance (Rg) 1 Ω, 10 Ω & 100 Ω are used with dierent types of faults (LG, LLG, LLLG, LL& LLL) for training. Two ANFIS structures are trained for the fault distance estimation in compensated line -one for Static Synchronous Compensator (STATCOM) and the other for Static Synchronous Series Compensator (SSSC). Simulation results show the fault locator estimates the fault location accurately with a 5% tolerance in all the fault conditions simulated.

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Section: Introductionmentioning

confidence: 99%