Work

Ai-enhanced reliability centered maintenance for high voltage gas circuit breakers

Year: 2025

Type: article

Abstract: Circuit breakers (CBs) are critical for protection and switching in power systems, requiring effective maintenance strategies to ensure reliability and longevity. Traditional approaches, including time-based, preventive, and condition-based maintenance (CBM), can be costly and inefficient. Reliability-centered maintenance (RCM) offers a more strategic alternative by prioritizing maintenance based on equipment condition and system importance. This paper presents a novel AI-driven method for assessing the condition of high-voltage circuit breakers (HVCBs) and optimizing maintenance schedules, with a particular focus on contact erosion. The proposed framework comprises three stages, each incorporating progressively more data to enhance assessment accuracy. The methodology is validated in a real-world network, comparing CBM and RCM strategies. Results indicate that integrating AI with RCM improves maintenance planning, reduces costs, and enhances system reliability. This approach provides a cost-effective and data-driven solution for CB maintenance in power systems.

Source: International Journal of Electrical Power & Energy Systems

DOI: 10.1016/j.ijepes.2025.110919

Authors: Payam Hedayatnia, Mohammad Hamed Samimi, Milad Mohammadhosein, Kaveh Niayesh

Institutions: University of Tehran, Norwegian University of Science and Technology

Language: English

Topic: Reliability and Maintenance Optimization

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: gold

Estimated APC paid: $3,920