A review on the impact of weather conditions on the reliability of medium voltage distribution substations

The reliability of medium voltage (MV) distribution substations is critical to the stability and resilience of modern power systems. However, their performance is highly susceptible to environmental and meteorological factors, particularly under extreme weather conditions such as rainfall, storms, wind, and snow. This paper presents a comprehensive review of research examining the influence of weather phenomena on the reliability of MV substations. It outlines the fundamental reliability indices, explores the mechanisms by which different weather conditions affect system components, and discusses the emerging role of machine learning (ML) techniques in predictive reliability assessment. The review further identifies major research gaps including the lack of integrated weather modeling, limited regional transferability of existing models, and the need for interpretable AI-driven approaches. The findings emphasize that combining meteorological data with ML-based predictive models offers a promising path toward resilient and adaptive power distribution networks.