Adaptive algorithm in distance relay with out of step blocking element compatible with smart grid requirements during sub-synchronous resonance in transmission line

Smart grid comprises utility system and dispersed renewable generations. It establishes bidirectional power transmission and communication among utility system, distributed generations and consumers. Sub-synchronous resonance (SSR) is a major concern in transmission line. Furthermore, impedance swing during SSR leads in operation of out of step blocking characteristic of distance relay. SSR brings about a significant rise in the magnitudes of voltage and current. It also raises probability of occurrence of ferroresonance. Here, the impact of SSR in utility system is analysed on operation of doubly-fed induction generator and distance relay with out of step blocking element is given here. Smart grid urge to establish a self-healing protection, hence, an adaptive algorithm based on sub harmonic and ferroresonance detection is proposed for distance relay. The algorithm discriminates ferroresonance from other nonlinearities by wavelet transform and neural network and utilises time domain analysis to distinguish between different types of ferroresonance. The algorithm is able to observe smart grid protection strategy. It is capable of receiving the commands according to protection strategy to take a correct decision in such conditions to enhance reliability of power electricity in smart grid. Finally, the proposed algorithm is examined in SSR condition to certify the correct operation.

Automated summary

The smart grid faces challenges related to sub-synchronous resonance (SSR) in transmission lines, affecting the operation of distance relays and doubly-fed induction generators. An adaptive algorithm based on sub harmonic and ferroresonance detection is proposed to improve smart grid protection strategy and enhance reliability of power electricity. The algorithm is capable of distinguishing between different types of ferroresonance using wavelet transform and neural network, and can take correct decisions to ensure proper operation under SSR conditions.