Abstract

The operation of Flexible AC Transmission System Controllers (FACTS) in the power transmission system pose a challenge to the distance relaying scheme. This paper suggests an adaptive scheme for estimating the trip boundaries of a distance relay in presence of a Unified Power Flow Controller (UPFC), utilizing a Generalized Regression Neural Network (GRNN). Initially, the impact of the UPFC on the relay's trip boundary is studied for its automatic power flow control mode as well as bypass mode of operation. The GRNN has been trained off-line with the data generated from a detailed performance analysis of the power system for various faults considering the effects of the UPFC, fault resistance, and system loading conditions on the trip boundaries. This work has also proposed a strategy that computes the control parameters of the UPFC on-line, namely, series voltage and reactive current injections, utilizing the synchronized phasor measurements from Phasor Measurement Units (PMUs). Pre-fault system states, including the control parameters of the UPFC and the apparent impedance measured by the relay unit have been utilized by the GRNN for predicting the trip boundaries of the relay. The proposed scheme has considered Single Line-to-Ground (SLG), Double Line-to-Ground (LLG) and Three Phase-to-Ground (LLLG) faults and the effectiveness of the scheme has been tested on 39-bus New England system and also on a 17-bus system, a reduced equivalent of practical Northern Regional Power Grid (NRPG) system in India.

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