Interregional renewable-dominant power systems are increasingly constrained by limited transmission capacity and insufficient support capability in weak-grid areas. This paper proposes a coordinated planning method for transmission expansion and grid-forming energy storage. A two-stage stochastic mixed-integer optimization model is developed in which candidate corridor expansion and grid-forming storage siting and sizing are jointly determined in the planning stage, while conventional generation dispatch, renewable accommodation, storage charging and discharging, and interregional power flows are optimized in the operation stage under multiple load and renewable scenarios. Planning-level support constraints and operational support availability constraints are introduced to represent the structural and operational support roles of grid-forming storage in weak-grid areas. Case studies show that the optimal investment structure combines reinforcement of key transmission corridors with grid-forming storage deployment at critical nodes. Compared with the baseline scheme, the coordinated scheme reduces the annual total cost from CNY 6.842 billion to CNY 6.078 billion, decreases annual renewable curtailment from 426 thousand MWh to 121 thousand MWh, reduces annual unserved energy from 12.8 thousand MWh to 0.5 thousand MWh, and changes the planning-level support margins of weak-grid regions from negative to positive. Additional tail-risk stress tests under high-load and low-renewable conditions further show that the coordinated scheme preserves lower unserved energy and positive support margins. The results indicate that transmission expansion mainly improves interregional resource allocation, whereas grid-forming storage mainly enhances local support capability and operational flexibility. The twn o resources therefore exhibit strong complementarity across both spatial and temporal dimensions. The proposed method provides systematic decision support for renewable energy delivery, backbone grid reinforcement, and grid-forming storage planning.
Qiang et al. (Fri,) studied this question.