| Issue |
EPJ Web Conf.
Volume 372, 2026
Advanced Power Systems (APS 2026)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 8 | |
| Section | Intelligent, Digital and Resilient Power Systems | |
| DOI | https://doi.org/10.1051/epjconf/202637201003 | |
| Published online | 11 June 2026 | |
https://doi.org/10.1051/epjconf/202637201003
The future of electrical power grid protection: Adaptive, intelligent, and cyber-resilient architectures for dynamic systems
1 Department of Electric Power Engineering, Technical university of Košice, Letná 1/9, 040 01 Košice, Slovakia
2 Kálmán Kandó Faculty of Electrical Egineering, Óbuda University, Bécsi way 94-96 ´, 1034 Budapest, Hungary
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 11 June 2026
Abstract
The modernization of the electrical power grid, driven by high penetration of Distributed Energy Resources (DERs) and Inverter-Based Resources (IBRs), has rendered conventional phasor-based protection schemes inadequate. Bidirectional power flows, significantly limited fault current contributions, and diminished inertia fundamentally challenge the selectivity and reliability of traditional protective IEDs. To address these challenges, this paper proposes a paradigm shift towards a centralized, software-defined protection architecture designed as an intelligent overlay to existing infrastructure. The core of the proposed system lies in a dual-stream data acquisition framework: integrating real-time data from legacy digital relays with high-precision measurements from a specialized monitoring unit (as pioneered by Bencsik and Bobček). Central to this architecture is a ‘Value Approve’ mechanism, which utilizes advanced data validation techniques to ensure the integrity of measurements before processing. This enables an Adaptive Protection (AP) engine to dynamically reconfigure protection settings based on real-time topology and IBR penetration levels. A key innovation of this approach is the transition to a fully software-driven trip logic, allowing for the temporary bypassing of local hardware settings in favour of centralized, optimized decision- making. By leveraging Machine Learning for event prediction and Explainable AI (XAI) for transparency, the system mitigates the ‘black box’ risks associated with automated protection. Furthermore, the architecture integrates cyber-physical defence strategies compliant with IEC 62443 to secure the digitized communication backbone. The result is a verifiable, autonomous, and resilient protection system capable of managing the complexities of the future grid through software agility.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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