As natural disasters intensify, timely dispatch of mobile battery energy storage (MBES), coordinated electricity gas operation and participatory demand response can substantially reduce outage and extent. Quantifying these benefits requires an integrated spatio-temporal model that embeds hazard dynamics, dynamic transit times (DTTs), dynamic transit price (DTP), probabilistic repair time (PRT) and operational uncertainties in dispatch and resource allocation. This study addresses that gap using Monte Carlo simulation (MCS) to model the spatio-temporal impact of windstorms on power lines and supporting more realistic planning for faster recovery. Repair is modelled probabilistically. The windstorm crosses one area and enters another at a different speed. Three resilience strategies are evaluated: integration of gas networks and energy hubs (EHs) with power grids; spatio-temporal optimisation of MBES deployment accounting for transit-time and cost variability due to traffic to accelerate load recovery; and an incentive-based demand response programme (DRP) for shiftable loads. The optimisation is posed as a MILP on an IEEE 33-bus network. Simulations cover four cases, with the most comprehensive combining all strategies. Results show that MBES, DRP and EHs act synergistically to reduce operating costs, decrease energy not supplied, and enhance the performance level as a resilience metric during disasters under severe conditions.
