Coordinated Scheduling of Wind–Solar–Thermal– Storage Systems for Renewable Integration

To support national carbon neutrality goals, China's grid is rapidly decarbonizing. Confronting power volatility and renewable curtailment induced by large-scale wind/PV penetration, this paper introduces an optimal scheduling framework for multi-energy complementary systems integrating thermal, storage, and renewables. Considering the complexity of the multi-energy structure, which involves a large number of decision variables and operational constraints, the model is linearized, and a hierarchical optimization framework is employed. The upper-level model minimizes thermal, storage, and renewable operating costs, using storage for peak-shaving to reduce load fluctuation and enable renewable integration. The lower level minimizes the thermal and storage costs, and curtailment penalties to boost renewable utilization and operational economy. A decomposition-and-coordination solution methodology is adopted to achieve iterative coordination between the two model layers. Finally, the proposed strategy is validated through simulation studies based on an improved IEEE 39-bus test system under multiple scenarios. Simulation results confirm that the proposed methodology substantially improves renewable energy accommodation capacity and overall system economic efficiency, validating the model's effectiveness and practical applicability.