Development of a framework for safety and resilience in overhead power cables: Use of a fuzzy inference system for risk and reliability analysis

Abstract

Ensuring the safety, resilience, and reliability of overhead low-voltage (LV) and medium-voltage (MV) power cables in aging infrastructure is vital for maintaining essential services and mitigating risks in electrical power distribution systems. This study introduces a novel framework that integrates fault tree analysis (FTA)/failure mode and effect analysis (FMEA) and a fuzzy inference system (FIS) to systematically address performance variability and enhance the operational life of these critical assets while ensuring safety and resilience. This structured framework employs risk-informed decision-making as well as reliability-based safety and resilience assurance, incorporating international standards and best practices. Under this methodology, the FIS models uncertainties in asset performance, using expert-defined rules and membership functions to categorize risk levels and assess failure severity. A case study is performed on overhead MV power cables, specifically the "Racoon" all-aluminum alloy conductor (AAAC), demonstrating its practical implementation. The results reveal that for typical environmental conditions and design parameters, the yearly reliability of the conductor is nearly 1, indicating compliance with IEC standards. Furthermore, a risk matrix is developed using current carrying capacity (CCC), a failure mode obtained from the FTA as the probability of occurrence, and power shutdown duration (PSD) as the severity indicator. The risk matrix estimates the potential risk (PR) level based on CCC and PSD inputs. For example, for CCC = 260 A and PSD = 50 min, the resulting PR is 12.9, indicating a moderate risk exists. These risk levels guide appropriate resilience actions, ensuring proactive power cable management by identifying critical risks, prioritizing mitigation measures, and ensuring adaptability and compliance. This approach not only addresses the challenges of aging infrastructure but also contributes to long-term system integrity and operational reliability.