Riyadh V2G Sovereign Digital Twin: A Physics-Integrated Framework for Municipal-Scale Vehicle-to-Grid Simulation with Cultural Calendar Modeling

The electrification of urban transport at sovereign scale introduces unprecedented stress on aging distribution-grid infrastructure, particularly in hot-climate cities where transformer thermal aging and air-conditioning-driven peak loads compound simultaneously. This paper presents the Riyadh V2G Sovereign Digital Twin, a 1:1-scale, physics-faithful simulation framework modeling the full Riyadh metropolitan grid — approximately 60,000 distribution transformers serving over one million electric vehicles across 14 municipalities — under vehicle-to-grid (V2G) dispatch scenarios. The framework integrates five physically coupled simulation layers: a Swing-Equation-based grid frequency model, an IEEE C57.91-compliant transformer thermal aging engine, a cascading failure propagation model with cold-load recovery dynamics, a three-archetype fleet mobility simulator incorporating Islamic cultural calendar patterns (Ramadan commute suppression, Saudi weekend mapping), and a locational marginal pricing engine with dynamic threshold transitions. All layers execute within a deterministic, vectorized orchestration pipeline guaranteeing bitwise reproducibility. The architecture strictly decouples the physics layer — which computes what is physically possible — from the policy layer — which decides what to do about it — enabling controlled experimentation with V2G dispatch strategies without compromising physical fidelity. This paper describes the system architecture, physics models, fleet mobility engine, infrastructure metering layer, and illustrative scenario results, demonstrating the framework's capability to answer "what-if" questions about city-scale V2G deployment before committing infrastructure capital.