Abstract: A trading decision method for a wind-photovoltaic-gas combined generation system participating in day-ahead and real-time markets was proposed based on Stackelberg game theory and distributed robust optimization theory, considering the distinct characteristics of these two markets. In the day-ahead stage, a bi-level optimization bidding game model was constructed with the combined system acting as the leader and jointly bidding with other conventional thermal units, while the independent system operator (ISO) acted as the follower to organize market joint clearing. In the real-time stage, based on the day-ahead dispatch schedule, a distributed robust optimization dispatch model for the combined system accounting for wind and photovoltaic output uncertainty was established by constructing wind and photovoltaic uncertainty sets using the 1-norm and ∞-norm. Simulation verification was conducted on a combined system comprising a 180 MW wind farm, a 70 MW photovoltaic power station, and a 120 MW gas-fired power station. The results demonstrate that compared with independent bidding, combined bidding reduces the real-time wind and photovoltaic output deviation penalty by 94.11% and increases the system total revenue by 2.68%.