Enhancing Reliability Performance in Distribution Networks Using Monte Carlo Simulation for Optimal Investment Option Selection

Limited financial resources significantly impact the ability of distribution system operators to prioritize maintenance, upgrade infrastructure, and integrate advanced technologies. To optimize resource allocation, a structured and detailed analysis is essential for maximizing reliability improvements within budget constraints. This paper presents a methodology for enhancing the reliability performance of semi-urban and rural distribution networks by identifying optimal investment strategies under financial limitations. Investment options are categorized into three groups: (1) installing new components where none previously existed, (2) replacing aging, higher-failure-rate equipment with new components, and (3) upgrading both network components and operational strategies. To determine the most effective investments, the selection process aims to minimize the System Average Interruption Duration Index (SAIDI) and Energy Not Supplied (ENS), while also considering an economic metric that quantifies reliability in monetary terms. The methodology was tested on networks with diverse consumer types, incorporating Monte Carlo simulation to account for uncertainties in component reliability indices and node loads. An optimization algorithm was developed, implemented, and validated using representative test networks, demonstrating its effectiveness in guiding investment decisions for improved distribution system reliability.