Reliability Assessment of Distribution System Using Fuzzy Logic for Modelling of Transformer and Line Uncertainties

TL;DR

This paper introduces a fuzzy logic-based approach to assess distribution system reliability, effectively handling uncertainties in component failure data to improve reliability index estimations.

Contribution

It proposes a fuzzy logic method to model uncertainties in failure rates and outage durations, enhancing reliability assessment accuracy over traditional probabilistic methods.

Findings

Fuzzy logic effectively models uncertainties in failure data.

Reliability indices are improved by considering influential variables.

Simulation on IEEE RBTS Bus 2 demonstrates practical utility.

Abstract

Reliability assessment of distribution system, based on historical data and probabilistic methods, leads to an unreliable estimation of reliability indices since the data for the distribution components are usually inaccurate or unavailable. Fuzzy logic is an efficient method to deal with the uncertainty in reliability inputs. In this paper, the ENS index along with other commonly used indices in reliability assessment are evaluated for the distribution system using fuzzy logic. Accordingly, the influential variables on the failure rate and outage duration time of the distribution components, which are natural or human-made, are explained using proposed fuzzy membership functions. The reliability indices are calculated and compared for different cases of the system operations by simulation on the IEEE RBTS Bus 2. The results of simulation show how utilities can significantly improve the reliability of their distribution system by considering the risk of the influential variables.