A Hybrid Intelligent System for Protection of Transmission Lines Connected to PV Farms based on Linear Trends

TL;DR

This paper proposes a hybrid intelligent protection system combining fuzzy logic and random forest algorithms to detect and locate faults in transmission lines connected to PV farms, addressing challenges posed by inverter-based resources.

Contribution

It introduces a novel hybrid method using linear trend attributes and RF feature selection for fault detection and location in PV-connected transmission lines.

Findings

Effective fault detection across various system conditions

Robust performance with noise and high impedance faults

Versatile applicability to different system configurations

Abstract

Conventional relays face challenges for transmission lines connected to inverter-based resources (IBRs). In this article, a single-ended intelligent protection of the transmission line in the zone between the grid and the PV farm is suggested. The method employs a fuzzy logic and random forest (RF)-based hybrid system to detect faults based on combined linear trend attributes of the 3-phase currents. The fault location is determined and the faulty phase is detected. RF feature selection is used to obtain the optimal linear trend feature. The performance of the methodology is examined for abnormal events such as faults, capacitor and load-switching operations simulated in PSCAD/EMTDC on IEEE 9-bus system obtained by varying various fault and switching parameters. Additionally, when validating the suggested strategy, consideration is given to the effects of conditions such as the presence of double circuit lines, PV capacity, sampling rate, data window length, noise, high impedance faults, CT saturation, compensation devices, evolving and cross-country faults, and far-end and near-end faults. The findings indicate that the suggested strategy can be used to deal with a variety of system configurations and situations while still safeguarding such complex power transmission networks.