Tunnel Load Simulator: A Monte Carlo Framework for Synthetic Electrical Demand Modeling of Road Tunnels

Abstract

Road tunnels are energy-intensive infrastructures (lighting, ventilation, auxiliary systems), but the scarcity of operational datasets limits data-driven energy management research. This paper introduces Tunnel Load Simulator, an open-source Python package that generates synthetic electrical load profiles for road tunnels. It integrates traffic-dependent demand modeling, lighting and ventilation estimation, stochastic event generation, and Monte Carlo simulation in an efficient framework, configurable via GUI or simulation engine. Outputs include time-resolved demand profiles, KPIs, seasonal analyses, and probabilistic uncertainty envelopes. Validation confirms computational consistency, parameter sensitivity, and stable probabilistic outputs. Released under MIT License, the tool supports energy assessment, uncertainty quantification, ML dataset generation, digital twin prototyping, and educational use.