Robust Coordinated Reserve Optimization Method for Electricity–Gas Systems Considering Multi‐Source Coupling and Multiple Uncertainties

To address operational uncertainties in integrated energy systems (IES) while considering renewable energy utilization and carbon emissions, a two‐stage robust reserve scheduling model is proposed for existing electricity–gas systems. The model accounts for wind and photovoltaic power fluctuations and transmission‐line N − 1 contingencies, while incorporating a tiered carbon emission cost into day‐ahead scheduling. Electricity and gas reserves are jointly allocated in the day‐ahead stage and coordinated during intraday adjustment to balance operating costs, renewable curtailment, and load‐shedding risks. First‐order Taylor linearization, strong duality, and a Big‐M formulation are applied to reformulate the intraday subproblem, and the model is solved using a column‐and‐constraint generation algorithm. Case studies on a coupled electricity–gas test system indicate that coordinated reserve scheduling promotes wind and solar utilization, and alleviates load‐shedding risks under multiple uncertainties. Incorporation of carbon emission costs encourages lower emission dispatch, with corresponding changes in operating costs and reserve allocation. These findings reveal the trade‐offs among operational robustness, economic performance, and emission reduction, demonstrating the potential of coordinated electricity–gas reserves to support renewable energy integration and low‐carbon operation.