Abstract
The study focuses on the reliability assessment of distribution power networks operating at voltages up to 110 kV, addressing the challenges of increasing loads, aging infrastructure, and the integration of renewable energy sources. A novel method and model for reliability assessment are proposed, incorporating failure rates, recovery times, and topological characteristics of networks. The research identifies critical factors influencing network reliability, including the level of redundancy, operational conditions, and climatic impacts. Notable findings show that network points with multiple feeder connections demonstrate the highest reliability, exceeding 99.99 %, while those with single-transformer configurations are the most vulnerable to failures. The average failure rate for overhead lines is calculated at 1.29 failures per 100 km annually, with recovery times reaching up to 40 hours for critical nodes. The results are explained by the interplay of structural and operational factors, where redundancy significantly enhances reliability, and outdated equipment increases vulnerability. The study’s distinguishing feature lies in its use of Markov processes to dynamically model failures and recoveries, offering a comprehensive framework compared to traditional static methods. The practical applications of the results include improving network design through enhanced redundancy, optimizing maintenance strategies for critical elements, and supporting the integration of Smart Grid technologies. These findings contribute to the development of more resilient and efficient power distribution networks, adaptable to modern operational demands