Traditional reliability models for distribution grids often rely on static historical averages, overestimating the operational lifespan of power system assets by neglecting the dynamic interplay between electrical loading and microclimatic stressors. This paper addresses these limitations by introducing an extended analytical framework designed to integrate climate-driven stressors into traditional reliability assessments, capturing the synergistic effects of environmental forcing and asset aging. This methodology is operationalized through a novel simulation framework and a modular Python-based tool (Python version 3.10.20), integrating OpenDSS and Pandapower to perform high-fidelity reliability assessments. By calculating instantaneous failure rates and Mean Time Between Failures (MTBF) as functions of real-time environmental forcing—specifically temperature and humidity-induced stresses—the proposed system captures degradation dynamics that remain invisible to conventional models. The framework’s capabilities are demonstrated through a simulation on a rural distribution grid, which explicitly includes auxiliary digitalization components, such as Remote Terminal Units (RTUs), that are frequently overlooked in standard benchmarks. The results reveal that environmental forcing triggers a sharp contraction in the MTBF of critical active assets, proving that asset seniority alone is an insufficient proxy for grid vulnerability.
Ciavarella et al. (Sun,) studied this question.