Segregation of fault rates and repair times inputs for low voltage distribution networks
Year: 2025
Type: article
Abstract: Reliability assessment of low voltage distribution networks is essential for effective utility planning, regulatory compliance, and the delivery of consistent and high quality service to customers. Traditional approaches to reliability evaluation often overlook the unique characteristics of different load areas, such as highly urban, urban, sub urban, and rural regions, which can result in less accurate and less actionable outcomes. This study introduces a comprehensive methodology that addresses this gap by segregating fault rates and repair times according to specific load area categories, ensuring that the distinct operational realities of each area are properly represented. At the core of the methodology is a probabilistic simulation framework, the Reliability Segregation Based Monte Carlo Simulation, which models network reliability by integrating area specific fault rates and repair times with daily load profiles and fault probability distributions. Simulation results demonstrate that the segregated approach leads to more accurate reliability assessments, with urban areas generally achieving better performance indices than rural areas. This methodology supports more effective resource allocation, targeted infrastructure investment, and regulatory reporting for utility operators. The practical implications are significant, as the approach provides a transparent and reproducible tool that enables utilities and regulators to make informed decisions about maintenance strategies, investment priorities, and customer service improvements. By highlighting the importance of spatial diversity and applying area specific reliability inputs, this research advances the field by offering a more nuanced and reliable framework for the assessment of low voltage distribution networks. Ultimately, this work contributes to improved operational efficiency and enhanced service quality for diverse communities.
Source: Ain Shams Engineering Journal
Institution: Universiti Malaysia Pahang Al-Sultan Abdullah
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
Awards: G3187939635, G3238629114
OpenAlex ID: W4415019709
