Abstract: The displacement of synchronous generation by Inverter-Based Resources (IBRs) dismantles the electromagnetic foundation upon which power-system protection has rested for over a century. In both grid-following and grid-forming converters, fault responses are software-defined: sub-cycle current limiters cap fault contributions near rated values, while sequence currents are dictated by proprietary inner-loop control laws rather than machine flux dynamics. Consequently, the high-magnitude, predictable fault currents that overcurrent, distance, and differential schemes rely upon are absent, rendering conventional fixed settings simultaneously insensitive and insecure across varying penetration levels, topologies, and dispatch conditions.

This thesis presents the Self-Adaptive Model-Based Protection Systems (SAMBPS) framework to resolve protection degradation in converter-dominated networks. The core operating paradigm is confidence-gated adaptation: protection elements adapt thresholds and operating boundaries only when a physics-based estimate of prevailing system conditions satisfies rigorous statistical confidence criteria; otherwise, the logic deterministically defaults to bounded, conservative fail-safe behaviour. The framework is structured across fundamental protection layers—incorporating dynamic physical modelling of the protected zone, rapid sub-cycle parameter estimation, explicit confidence estimation, gated setting adaptation, and supervisory wide-area coordination.

Validated across heterogeneous networks hosting mixed grid-following and grid-forming sources, the thesis contributes new closed-loop adaptive algorithms that bridge local fast-relay physics with system-level state tracking, establishing a provably robust protection architecture that maintains dependability and security under high IBR penetration.

Event Details
Title: Self-Adaptive Model-Based Protection for Inverter-Dominated Power Networks (PhD Viva Voce)
Date: September 29, 2026 at 02:00 PM
Venue: Google Meet (https://meet.google.com/pcx-hriz-qcy)
Speaker: Mr. Anoop V Eluvathingal (EE14D001)
Guide: Dr. Swarup K S
Type: PHD seminar

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